diff --git a/.gitignore b/.gitignore index 170d055..285194b 100644 --- a/.gitignore +++ b/.gitignore @@ -7,3 +7,4 @@ ref **/docs/_build/ **/docs/build/ **/__pycache__/** +.envrc diff --git a/.gitmodules b/.gitmodules deleted file mode 100644 index 3e6b36a..0000000 --- a/.gitmodules +++ /dev/null @@ -1,4 +0,0 @@ -[submodule "env_manager"] - path = env_manager - url = https://gitlab.com/solid-sinusoid/env_manager.git - branch = main diff --git a/add_repos.sh b/add_repos.sh new file mode 100755 index 0000000..a7b1134 --- /dev/null +++ b/add_repos.sh @@ -0,0 +1,72 @@ +#!/bin/bash + +# Check if a YAML file is provided +if [ $# -eq 0 ]; then + echo "Usage: $0 " + exit 1 +fi + +YAML_FILE=$1 + +# Ensure the YAML file exists +if [ ! -f "$YAML_FILE" ]; then + echo "File not found: $YAML_FILE" + exit 1 +fi + +# Function to extract values from YAML using yq (https://github.com/mikefarah/yq) +extract_yaml_value() { + local key=$1 + local repo_name=$2 + # Use brackets to handle keys with special characters + yq ".repositories[\"$repo_name\"].$key" "$YAML_FILE" | tr -d '"' +} + +# Check if yq is installed +if ! command -v yq &> /dev/null; then + echo "yq could not be found. Please install yq from https://github.com/mikefarah/yq" + exit 1 +fi + +# Debugging: Print the entire YAML content for verification +echo "Content of $YAML_FILE:" +cat "$YAML_FILE" + +# Parse the YAML file and process each repository +REPOSITORIES=$(yq '.repositories | keys_unsorted' "$YAML_FILE") + +# Debugging: Print the list of repositories in raw form +echo "Raw repositories list:" +echo "$REPOSITORIES" + +# Extract and clean up the list of repository names +REPOSITORIES=$(echo "$REPOSITORIES" | grep -v '^-\s*$' | tr -d '[]"' | tr ',' '\n' | sed '/^$/d') + +# Debugging: Print the cleaned list of repositories +echo "Cleaned repositories list:" +echo "$REPOSITORIES" + +for REPO_NAME in $REPOSITORIES; do + TYPE=$(extract_yaml_value "type" "$REPO_NAME") + URL=$(extract_yaml_value "url" "$REPO_NAME") + VERSION=$(extract_yaml_value "version" "$REPO_NAME") + + # Only process repositories of type 'git' + if [ "$TYPE" == "git" ]; then + PREFIX="src/$REPO_NAME" + + # Run the git subtree add command + echo "Adding repository '$REPO_NAME' with URL '$URL' and version '$VERSION' to prefix '$PREFIX'" + git subtree add --prefix="$PREFIX" "$URL" "$VERSION" --squash + + # Check if the command was successful + if [ $? -ne 0 ]; then + echo "Failed to add repository '$REPO_NAME'." + exit 1 + fi + else + echo "Skipping non-git repository '$REPO_NAME'." + fi +done + +echo "All repositories have been added successfully." \ No newline at end of file diff --git a/docs/ru/installation.md b/docs/ru/installation.md index 8ef31cc..76e9279 100644 --- a/docs/ru/installation.md +++ b/docs/ru/installation.md @@ -1,15 +1,15 @@ # Инструкция по установке фреймворка -**Важно!** Совместимо только с операционной системой Ubuntu 22.04. +**Важно!** Совместимо только с операционной системой Ubuntu 24.04. Ниже приведена последовательность шагов для настройки фреймворка. --- -## Шаг 1: Установка ROS2 Humble +## Шаг 1: Установка ROS2 Jazzy -Для начала установите [ROS2 Humble](https://docs.ros.org/en/humble/Installation/Ubuntu-Install-Debs.html). -Рекомендуется минимальная установка `ros-humble-ros-base`, а также пакет `ros-dev-tools`. +Для начала установите [ROS2 Jazzy](https://docs.ros.org/en/jazzy/Installation/Ubuntu-Install-Debs.html). +Рекомендуется минимальная установка `ros-jazzy-ros-base`, а также пакет `ros-dev-tools`. --- @@ -17,7 +17,7 @@ Перед продолжением убедитесь, что среда ROS2 активирована. Для этого выполните: ```sh -source /opt/ros/humble/setup.bash +source /opt/ros/jazzy/setup.bash ``` --- @@ -33,29 +33,14 @@ rosdep update ```sh cd mkdir -p robossembler-ws/src && cd robossembler-ws/src -git clone --recurse-submodules https://gitlab.com/robossembler/robossembler-ros2.git +git clone https://gitlab.com/robossembler/robossembler-ros2.git ``` -Далее необходимо собрать [`ros2_control`](https://github.com/ros-controls/ros2_control) из исходников, используя этот [форк](https://github.com/solid-sinusoid/ros2_control/tree/gz-ros2-cartesian-controllers). -Также доступна альтернатива с использованием [`vsctool`](https://github.com/dirk-thomas/vcstool), который входит в состав базовых пакетов ROS2. - Если вы решили использовать `vcstool`, нужные пакеты будут клонированы в тоже рабочее пространство, что и сам фреймворк. Команда для этого выглядит следующим образом: ```sh vcs import . < robossembler-ros2/repos/all-deps.repos ``` -Вы также можете установить все необходимые библиотеки Python, выполнив команду: -```shell -pip install -r robossembler-ros2/repos/requirements.txt -# Если Вы получили ошибку с установкой Shapely -sudo apt install libgeos-dev -``` - -> **[!ВНИМАНИЕ]** -> Убедитесь, что у вас установлен `git lfs`. В файле `requirements.txt` указан модуль `rbs_assets_library`, который содержит большие файлы и устанавливается как Python-модуль. - -Эти команды нужно выполнять в директории `robossembler-ws/src/`. - Установка зависимостей при помощи `rosdep` ```sh cd ~/robossembler-ws @@ -74,14 +59,66 @@ colcon build ```sh cd mkdir -p robossembler-ws/src && cd robossembler-ws/src -git clone --recurse-submodules https://gitlab.com/robossembler/robossembler-ros2.git +git clone https://gitlab.com/robossembler/robossembler-ros2.git # Или, если вы предпочитаете Radicle: -git clone --recurse-submodules https://seed.robossembler.org/z46gtVRpXaXrGQM7Fxiqu7pLy7kip.git robossembler-ros2 +git clone https://seed.robossembler.org/z46gtVRpXaXrGQM7Fxiqu7pLy7kip.git robossembler-ros2 rad clone rad:z46gtVRpXaXrGQM7Fxiqu7pLy7kip vcs import . < robossembler-ros2/repos/all-deps.repos -pip install -r robossembler-ros2/repos/requirements.txt cd .. rosdep install --from-paths src -y --ignore-src --rosdistro ${ROS_DISTRO} colcon build ``` +--- +## Установка зависимостей среды выполнения (runtime) Python + +Для корректной работы с Python-зависимостями в проекте необходимо создать виртуальное окружение в директории с рабочим пространством (workspace). + +### Создание виртуального окружения + +```sh +cd ~/robossembler-ws +sudo apt update && sudo apt install -y python3-virtualenv +virtualenv -p python3 .venv +``` + +После этого создается виртуальное окружение `.venv` в рабочем пространстве. Чтобы исключить его из сборки colcon, создадим файл `COLCON_IGNORE`: + +```sh +touch .venv/COLCON_IGNORE +``` + +### Использование виртуального окружения + +Для установки пакетов в виртуальное окружение его необходимо активировать: + +```sh +source .venv/bin/activate +``` + +После активации можно устанавливать зависимости из файла `requirements.txt`: + +```sh +pip install -r src/robossembler-ros2/repos/requirements.txt +``` + +Чтобы обеспечить доступ к установленным в виртуальное окружение библиотекам, необходимо добавить путь к ним в переменную окружения `PYTHONPATH`: + +```sh +export PYTHONPATH=$PYTHONPATH:$HOME/robossembler-ws/.venv/lib/python3.12/site-packages +``` + +Для автоматического применения этого пути при каждом запуске терминала рекомендуется добавить эту строку в файл `~/.bashrc`: + +```sh +echo 'export PYTHONPATH=$PYTHONPATH:$HOME/robossembler-ws/.venv/lib/python3.12/site-packages' >> ~/.bashrc +source ~/.bashrc +``` + +### Отключение виртуального окружения перед сборкой + +При сборке проекта colcon использует глобальные Python-библиотеки, поэтому перед сборкой необходимо деактивировать виртуальное окружение: + +```sh +deactivate +``` diff --git a/env_manager b/env_manager deleted file mode 160000 index d3d1935..0000000 --- a/env_manager +++ /dev/null @@ -1 +0,0 @@ -Subproject commit d3d19355683338c8c013fde5a7a5c6ebcd73d0f7 diff --git a/env_manager/.gitignore b/env_manager/.gitignore new file mode 100644 index 0000000..48734be --- /dev/null +++ b/env_manager/.gitignore @@ -0,0 +1,178 @@ +# Created by https://www.toptal.com/developers/gitignore/api/python,ros3 +# Edit at https://www.toptal.com/developers/gitignore?templates=python,ros3 + +### Python ### +# Byte-compiled / optimized / DLL files +**/__pycache__/ +**/*.py[cod] +**/*$py.class +**/*.cpython-*.pyc +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock + +# pdm +# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. +#pdm.lock +# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it +# in version control. +# https://pdm.fming.dev/#use-with-ide +.pdm.toml + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. For a more nuclear +# option (not recommended) you can uncomment the following to ignore the entire idea folder. +#.idea/ + +### Python Patch ### +# Poetry local configuration file - https://python-poetry.org/docs/configuration/#local-configuration +poetry.toml + +# ruff +.ruff_cache/ + +# LSP config files +pyrightconfig.json + +#!! ERROR: ros3 is undefined. Use list command to see defined gitignore types !!# + +# End of https://www.toptal.com/developers/gitignore/api/python,ros3 diff --git a/env_manager/docs/about/img/ar_textured_ground-1f72b8d6cb977cdca352bd6e81a3cd7d.png b/env_manager/docs/about/img/ar_textured_ground-1f72b8d6cb977cdca352bd6e81a3cd7d.png new file mode 100644 index 0000000..df47ede Binary files /dev/null and b/env_manager/docs/about/img/ar_textured_ground-1f72b8d6cb977cdca352bd6e81a3cd7d.png differ diff --git a/env_manager/docs/about/img/ar_textured_ground2-79b89f8247de2d0e663dad39e151eeac.png b/env_manager/docs/about/img/ar_textured_ground2-79b89f8247de2d0e663dad39e151eeac.png new file mode 100644 index 0000000..df5d2d8 Binary files /dev/null and b/env_manager/docs/about/img/ar_textured_ground2-79b89f8247de2d0e663dad39e151eeac.png differ diff --git a/env_manager/docs/about/img/rbs_texture_ground_and_spawned_objects-38c103bb6197006d9decdb54fec2404f.png b/env_manager/docs/about/img/rbs_texture_ground_and_spawned_objects-38c103bb6197006d9decdb54fec2404f.png new file mode 100644 index 0000000..7c3dcba Binary files /dev/null and b/env_manager/docs/about/img/rbs_texture_ground_and_spawned_objects-38c103bb6197006d9decdb54fec2404f.png differ diff --git a/env_manager/docs/about/img/scene_data_class_diagram-9c873943a7c4492b3254a24973e1fac2.png b/env_manager/docs/about/img/scene_data_class_diagram-9c873943a7c4492b3254a24973e1fac2.png new file mode 100644 index 0000000..aa7b626 Binary files /dev/null and b/env_manager/docs/about/img/scene_data_class_diagram-9c873943a7c4492b3254a24973e1fac2.png differ diff --git a/env_manager/docs/about/index.ru.md b/env_manager/docs/about/index.ru.md new file mode 100644 index 0000000..ee8fa08 --- /dev/null +++ b/env_manager/docs/about/index.ru.md @@ -0,0 +1,55 @@ +# Модуль управления виртуальными средами +--- + +При управлении роботами в симуляторе Gazebo через фреймворк ROS2 возникает необходимость конфигурировать не только робота-манипулятора, но и саму сцену. Однако стандартный подход, основанный на конфигурационных файлах Gazebo, зачастую оказывается избыточным и недостаточно гибким для динамических сценариев, к которым относится обучение с подкреплением. + +**env_manager** — это пакет, предназначенный для конфигурирования сцен в симуляторе Gazebo, предоставляющий более удобный и гибкий подход к созданию и настройке симуляционных сред. + +## Возможности пакета + +С последнего обновления модуль был полностью переработан. Если ранее его функции ограничивались указанием объектов, находящихся в среде, для работы в ROS2, то теперь он предоставляет инструменты для: +- полного конфигурирования сцены, +- настройки объектов наблюдения для ROS2. + +Конфигурация осуществляется с использованием **датаклассов** или **YAML-файлов**, что соответствует декларативному подходу описания сцены. Это делает процесс настройки интуитивно понятным и легко масштабируемым. Пример файла описания сцены, а также файл с конфигурацией по умолчанию доступны [здесь](https://gitlab.com/solid-sinusoid/env_manager/-/blob/b425a1b012bc8320bba7b68e5481da187d64d76e/rbs_runtime/config/default-scene-config.yaml). + +## Возможности конфигурации + +Модуль поддерживает добавление различных типов объектов в сцену, включая: +- **Модель** +- **Меш** +- **Бокс** +- **Цилиндр** +- **Сферу** + +Различие между "моделью" и "мешем" заключается в том, находится ли объект в библиотеке **rbs_assets_library** (подробнее о ней см. [соответствующий раздел](https://robossembler.org/docs/software/ros2#rbs_assets_library)). Дополнительно поддерживается **рандомизация объектов**, позволяющая случайным образом изменять их цвет и положение в сцене. + +Помимо объектов, с помощью пакета можно настраивать: +- **Источники света** +- **Сенсоры** +- **Роботов** +- **Рабочие поверхности** + +Каждый тип объекта обладает как параметрами размещения, так и параметрами рандомизации. Для камер предусмотрены настройки публикации данных: +- изображения глубины +- цветного изображения +- облаков точек. + +Параметры рандомизации могут включать в себя положение, ориентацию в заданных пользователем пределах, а также. Для рабочей поверхности также включается возможность рандомизации текстуры, а для робота имеется возможность рандомизировать его положения, в том числе конфигурацию и расположение базы робота. + +## Архитектура и спецификации + +Основная структура модуля включает обертки для добавления объектов в сцену. Полная спецификация доступных параметров и взаимосвязей между классами представлена в папке конфигураций. Для каждой категории объектов используются отдельные датаклассы, что упрощает организацию и модификацию параметров. + +Диаграмма классов конфигурации сцены представлена ниже: + +![scene_class_diagramm](./img/scene_data_class_diagram-9c873943a7c4492b3254a24973e1fac2.png) +*Диаграмма классов конфигурации сцены* + +## Примеры + +Ниже представлены различные сцены, созданные с использованием возможностей **env_manager**: + +| **Сценарий 1** | **Сценарий 2** | **Сценарий 3** | +|-----------------|-----------------|-----------------| +| ![one](./img/ar_textured_ground-1f72b8d6cb977cdca352bd6e81a3cd7d.png) | ![two](./img/ar_textured_ground2-79b89f8247de2d0e663dad39e151eeac.png) | ![three](./img/rbs_texture_ground_and_spawned_objects-38c103bb6197006d9decdb54fec2404f.png) | diff --git a/env_manager/docs/getting_started/getting_started.ru.md b/env_manager/docs/getting_started/getting_started.ru.md new file mode 100644 index 0000000..35af9b9 --- /dev/null +++ b/env_manager/docs/getting_started/getting_started.ru.md @@ -0,0 +1,48 @@ +# Начало работы с rbs_gym + +Пакет входит в проект Robossembler. Для установки пакета необходимо произвести установку всего проекта по [инструкции](https://gitlab.com/robossembler/robossembler-ros2/-/blob/b109c97b5c093e665135179668cb2091e6708387/docs/ru/installation.md) + +## Запуск тестовой среды + +Для запуска тестовой среды необходимо выполнить команду + +```sh +ros2 launch rbs_gym test_env.launch.py base_link_name:=base_link ee_link_name:=gripper_grasp_point control_space:=task control_strategy:=effort interactive:=false +``` + +Это продемонстрирует что все установилось и работает адекватно. Для визуализации можно воспользоваться графическим клиентом Gazebo в новом терминале: +```sh +ign gazebo -g +``` + +## Запуск обучения тестовой среды + +Запуск обучения производится следующей командой: + +```sh +ros2 launch rbs_gym train.launch.py base_link_name:=base_link ee_link_name:=gripper_grasp_point control_space:=task control_strategy:=effort interactive:=false +``` + +Команда запустит обучения алгоритмом SAC. Полный перечень аргументов можно посмотреть общим флагом `--show-args` применимым ко всем файлам запуска запускаемым посредством команды `ros2 launch`. + +```sh +ros2 launch rbs_gym train.launch.py --show-args +``` + +Метрики качества обучения можно наблюдать в папке `logs`, которая автоматически создастся в том месте откуда Вы запускали обучение агента. Для этого надо перейти в эту директорию и выполнить команду + +```sh +cd logs +aim up +``` + +Это выведет в консоль ссылку на веб интерфейс [Aim](https://aimstack.io/) который необходимо открыть в браузере. + +## Модификация сцены + +Обычно среда всегда прочно связана со сценой. Поэтому для модификации сцены часто также необходимо вносить правки и в среду + +Сцена задается как конфигурация [`env_manager`](../about/index.ru.md) пример конфигурации для сцены можно подглядеть [тут](../../rbs_gym/rbs_gym/envs/__init__.py) для тестовой среды + +В настоящий момент функционал активно разрабатывается в дальнейшем появится более удобный способ модификации сцены и модификации параметров среды с использованием [Hydra](https://hydra.cc/) + diff --git a/env_manager/env_manager/LICENSE b/env_manager/env_manager/LICENSE new file mode 100644 index 0000000..d645695 --- /dev/null +++ b/env_manager/env_manager/LICENSE @@ -0,0 +1,202 @@ + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/env_manager/env_manager/env_manager/__init__.py b/env_manager/env_manager/env_manager/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/env_manager/env_manager/env_manager/models/__init__.py b/env_manager/env_manager/env_manager/models/__init__.py new file mode 100644 index 0000000..2cef2a1 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/__init__.py @@ -0,0 +1,5 @@ +from .lights import * +from .objects import * +from .robots import * +from .sensors import * +from .terrains import * diff --git a/env_manager/env_manager/env_manager/models/configs/__init__.py b/env_manager/env_manager/env_manager/models/configs/__init__.py new file mode 100644 index 0000000..10201ce --- /dev/null +++ b/env_manager/env_manager/env_manager/models/configs/__init__.py @@ -0,0 +1,15 @@ +from .camera import CameraData +from .light import LightData +from .objects import ( + BoxObjectData, + CylinderObjectData, + MeshData, + ModelData, + ObjectData, + PlaneObjectData, + SphereObjectData, + ObjectRandomizerData, +) +from .robot import RobotData +from .terrain import TerrainData +from .scene import SceneData diff --git a/env_manager/env_manager/env_manager/models/configs/camera.py b/env_manager/env_manager/env_manager/models/configs/camera.py new file mode 100644 index 0000000..c76e8d9 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/configs/camera.py @@ -0,0 +1,111 @@ +from dataclasses import dataclass, field + +import numpy as np + + +@dataclass +class CameraData: + """ + CameraData stores the parameters and configuration settings for an RGB-D camera. + + Attributes: + ---------- + name : str + The name of the camera instance. Default is an empty string. + enable : bool + Boolean flag to enable or disable the camera. Default is True. + type : str + Type of the camera. Default is "rgbd_camera". + relative_to : str + The reference frame relative to which the camera is placed. Default is "base_link". + + width : int + The image width (in pixels) captured by the camera. Default is 128. + height : int + The image height (in pixels) captured by the camera. Default is 128. + image_format : str + The image format used (e.g., "R8G8B8"). Default is "R8G8B8". + update_rate : int + The rate (in Hz) at which the camera provides updates. Default is 10 Hz. + horizontal_fov : float + The horizontal field of view (in radians). Default is pi / 3.0. + vertical_fov : float + The vertical field of view (in radians). Default is pi / 3.0. + + clip_color : tuple[float, float] + The near and far clipping planes for the color camera. Default is (0.01, 1000.0). + clip_depth : tuple[float, float] + The near and far clipping planes for the depth camera. Default is (0.05, 10.0). + + noise_mean : float | None + The mean value of the Gaussian noise applied to the camera's data. Default is None (no noise). + noise_stddev : float | None + The standard deviation of the Gaussian noise applied to the camera's data. Default is None (no noise). + + publish_color : bool + Whether or not to publish color data from the camera. Default is False. + publish_depth : bool + Whether or not to publish depth data from the camera. Default is False. + publish_points : bool + Whether or not to publish point cloud data from the camera. Default is False. + + spawn_position : tuple[float, float, float] + The initial spawn position (x, y, z) of the camera relative to the reference frame. Default is (0, 0, 1). + spawn_quat_xyzw : tuple[float, float, float, float] + The initial spawn orientation of the camera in quaternion (x, y, z, w). Default is (0, 0.70710678118, 0, 0.70710678118). + + random_pose_rollouts_num : int + The number of random pose rollouts. Default is 1. + random_pose_mode : str + The mode for random pose generation (e.g., "orbit"). Default is "orbit". + random_pose_orbit_distance : float + The fixed distance from the object in "orbit" mode. Default is 1.0. + random_pose_orbit_height_range : tuple[float, float] + The range of vertical positions (z-axis) in "orbit" mode. Default is (0.1, 0.7). + random_pose_orbit_ignore_arc_behind_robot : float + The arc angle (in radians) behind the robot to ignore when generating random poses. Default is pi / 8. + random_pose_select_position_options : list[tuple[float, float, float]] + A list of preset position options for the camera in random pose mode. Default is an empty list. + random_pose_focal_point_z_offset : float + The offset in the z-direction of the focal point when generating random poses. Default is 0.0. + random_pose_rollout_counter : float + A counter tracking the number of rollouts completed for random poses. Default is 0.0. + """ + + name: str = field(default_factory=str) + enable: bool = field(default=True) + type: str = field(default="rgbd_camera") + relative_to: str = field(default="base_link") + + width: int = field(default=128) + height: int = field(default=128) + image_format: str = field(default="R8G8B8") + update_rate: int = field(default=10) + horizontal_fov: float = field(default=np.pi / 3.0) + vertical_fov: float = field(default=np.pi / 3.0) + + clip_color: tuple[float, float] = field(default=(0.01, 1000.0)) + clip_depth: tuple[float, float] = field(default=(0.05, 10.0)) + + noise_mean: float | None = None + noise_stddev: float | None = None + + publish_color: bool = field(default=False) + publish_depth: bool = field(default=False) + publish_points: bool = field(default=False) + + spawn_position: tuple[float, float, float] = field(default=(0.0, 0.0, 1.0)) + spawn_quat_xyzw: tuple[float, float, float, float] = field( + default=(0.0, 0.70710678118, 0.0, 0.70710678118) + ) + + random_pose_rollouts_num: int = field(default=1) + random_pose_mode: str = field(default="orbit") + random_pose_orbit_distance: float = field(default=1.0) + random_pose_orbit_height_range: tuple[float, float] = field(default=(0.1, 0.7)) + random_pose_orbit_ignore_arc_behind_robot: float = field(default=np.pi / 8) + random_pose_select_position_options: list[tuple[float, float, float]] = field( + default_factory=list + ) + random_pose_focal_point_z_offset: float = field(default=0.0) + random_pose_rollout_counter: float = field(default=0.0) diff --git a/env_manager/env_manager/env_manager/models/configs/light.py b/env_manager/env_manager/env_manager/models/configs/light.py new file mode 100644 index 0000000..ea15f52 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/configs/light.py @@ -0,0 +1,39 @@ +from dataclasses import dataclass, field + + +@dataclass +class LightData: + """ + LightData stores the configuration and settings for a light source in a simulation or rendering environment. + + Attributes: + ---------- + type : str + The type of the light source (e.g., "sun", "point", "spot"). Default is "sun". + direction : tuple[float, float, float] + The direction vector of the light source in (x, y, z). This is typically used for directional lights like the sun. + Default is (0.5, -0.25, -0.75). + random_minmax_elevation : tuple[float, float] + The minimum and maximum elevation angles (in radians) for randomizing the light's direction. + Default is (-0.15, -0.65). + color : tuple[float, float, float, float] + The RGBA color of the light source. Each value ranges from 0 to 1. Default is (1.0, 1.0, 1.0, 1.0), which represents white light. + distance : float + The effective distance of the light source. Default is 1000.0 units. + visual : bool + A flag indicating whether the light source is visually represented in the simulation (e.g., whether it casts visible rays). + Default is True. + radius : float + The radius of the light's influence (for point and spot lights). Default is 25.0 units. + model_rollouts_num : int + The number of rollouts for randomizing light configurations in different simulation runs. Default is 1. + """ + + type: str = field(default="sun") + direction: tuple[float, float, float] = field(default=(0.5, -0.25, -0.75)) + random_minmax_elevation: tuple[float, float] = field(default=(-0.15, -0.65)) + color: tuple[float, float, float, float] = field(default=(1.0, 1.0, 1.0, 1.0)) + distance: float = field(default=1000.0) + visual: bool = field(default=True) + radius: float = field(default=25.0) + model_rollouts_num: int = field(default=1) diff --git a/env_manager/env_manager/env_manager/models/configs/objects.py b/env_manager/env_manager/env_manager/models/configs/objects.py new file mode 100644 index 0000000..167423d --- /dev/null +++ b/env_manager/env_manager/env_manager/models/configs/objects.py @@ -0,0 +1,198 @@ +from dataclasses import dataclass, field + +from env_manager.utils.types import Pose + + +@dataclass +class ObjectRandomizerData: + """ + ObjectRandomizerData contains parameters for randomizing object properties during simulation. + + Attributes: + ---------- + count : int + The number of objects to randomize. Default is 0. + random_pose : bool + Flag indicating whether to randomize both the position and orientation of objects. Default is False. + random_position : bool + Flag indicating whether to randomize the position of objects. Default is False. + random_orientation : bool + Flag indicating whether to randomize the orientation of objects. Default is False. + random_model : bool + Flag indicating whether to randomize the model of the objects. Default is False. + random_spawn_position_segments : list + List of segments within which the object can be randomly spawned. Default is an empty list. + random_spawn_position_update_workspace_centre : bool + Flag indicating whether to update the workspace center during random spawning. Default is False. + random_spawn_volume : tuple[float, float, float] + The volume within which objects can be randomly spawned, defined by (x, y, z). Default is (0.5, 0.5, 0.5). + models_rollouts_num : int + The number of rollouts for randomizing models. Default is 0. + """ + + count: int = field(default=0) + random_pose: bool = field(default=False) + random_position: bool = field(default=False) + random_orientation: bool = field(default=False) + random_model: bool = field(default=False) + random_spawn_position_segments: list = field(default_factory=list) + random_spawn_position_update_workspace_centre: bool = field(default=False) + random_spawn_volume: tuple[float, float, float] = field(default=(0.5, 0.5, 0.5)) + models_rollouts_num: int = field(default=0) + random_color: bool = field(default=False) + + +@dataclass +class ObjectData: + """ + ObjectData stores the base properties for any object in the simulation environment. + + Attributes: + ---------- + name : str + The name of the object. Default is "object". + type : str + The type of the object (e.g., "sphere", "box"). Default is an empty string. + relative_to : str + The reference frame relative to which the object is positioned. Default is "world". + position : tuple[float, float, float] + The position of the object in (x, y, z) coordinates. Default is (0.0, 0.0, 0.0). + orientation : tuple[float, float, float, float] + The orientation of the object as a quaternion (x, y, z, w). Default is (1.0, 0.0, 0.0, 0.0). + static : bool + Flag indicating if the object is static in the simulation (immovable). Default is False. + randomize : ObjectRandomizerData + Object randomizer settings for generating randomized object properties. Default is an empty ObjectRandomizerData instance. + """ + + name: str = field(default="object") + type: str = field(default_factory=str) + relative_to: str = field(default="world") + position: tuple[float, float, float] = field(default=(0.0, 0.0, 0.0)) + orientation: tuple[float, float, float, float] = field(default=(1.0, 0.0, 0.0, 0.0)) + color: tuple[float, float, float, float] | None = field(default=None) + static: bool = field(default=False) + randomize: ObjectRandomizerData = field(default_factory=ObjectRandomizerData) + + +@dataclass +class PrimitiveObjectData(ObjectData): + """ + PrimitiveObjectData defines the base properties for primitive objects (e.g., spheres, boxes) in the simulation. + + Attributes: + ---------- + collision : bool + Flag indicating whether the object participates in collision detection. Default is True. + visual : bool + Flag indicating whether the object has a visual representation in the simulation. Default is True. + color : tuple[float, float, float, float] + The color of the object, represented in RGBA format. Default is (0.8, 0.8, 0.8, 1.0). + mass : float + The mass of the object. Default is 0.1. + """ + + collision: bool = field(default=True) + visual: bool = field(default=True) + mass: float = field(default=0.1) + + +@dataclass +class SphereObjectData(PrimitiveObjectData): + """ + SphereObjectData defines the specific properties for a spherical object in the simulation. + + Attributes: + ---------- + radius : float + The radius of the sphere. Default is 0.025. + friction : float + The friction coefficient of the sphere when in contact with surfaces. Default is 1.0. + """ + + radius: float = field(default=0.025) + friction: float = field(default=1.0) + + +@dataclass +class PlaneObjectData(PrimitiveObjectData): + """ + PlaneObjectData defines the specific properties for a planar object in the simulation. + + Attributes: + ---------- + size : tuple[float, float] + The size of the plane, defined by its width and length. Default is (1.0, 1.0). + direction : tuple[float, float, float] + The normal vector representing the direction the plane faces. Default is (0.0, 0.0, 1.0). + friction : float + The friction coefficient of the plane when in contact with other objects. Default is 1.0. + """ + + size: tuple = field(default=(1.0, 1.0)) + direction: tuple = field(default=(0.0, 0.0, 1.0)) + friction: float = field(default=1.0) + + +@dataclass +class CylinderObjectData(PrimitiveObjectData): + """ + CylinderObjectData defines the specific properties for a cylindrical object in the simulation. + + Attributes: + ---------- + radius : float + The radius of the cylinder. Default is 0.025. + length : float + The length of the cylinder. Default is 0.1. + friction : float + The friction coefficient of the cylinder when in contact with surfaces. Default is 1.0. + """ + + radius: float = field(default=0.025) + length: float = field(default=0.1) + friction: float = field(default=1.0) + + +@dataclass +class BoxObjectData(PrimitiveObjectData): + """ + BoxObjectData defines the specific properties for a box-shaped object in the simulation. + + Attributes: + ---------- + size : tuple[float, float, float] + The dimensions of the box in (width, height, depth). Default is (0.05, 0.05, 0.05). + friction : float + The friction coefficient of the box when in contact with surfaces. Default is 1.0. + """ + + size: tuple = field(default=(0.05, 0.05, 0.05)) + friction: float = field(default=1.0) + + +@dataclass +class ModelData(ObjectData): + """ + MeshObjectData defines the specific properties for a mesh-based object in the simulation. + + Attributes: + ---------- + texture : list[float] + A list of texture coordinates or texture properties applied to the mesh. Default is an empty list. + """ + + texture: list[float] = field(default_factory=list) + + +@dataclass +class MeshData(ModelData): + mass: float = field(default_factory=float) + inertia: tuple[float, float, float, float, float, float] = field( + default_factory=tuple + ) + cm: Pose = field(default_factory=Pose) + collision: str = field(default_factory=str) + visual: str = field(default_factory=str) + friction: float = field(default_factory=float) + density: float = field(default_factory=float) diff --git a/env_manager/env_manager/env_manager/models/configs/robot.py b/env_manager/env_manager/env_manager/models/configs/robot.py new file mode 100644 index 0000000..b2f90ca --- /dev/null +++ b/env_manager/env_manager/env_manager/models/configs/robot.py @@ -0,0 +1,103 @@ +from dataclasses import dataclass, field +from enum import Enum + + +@dataclass +class ToolData: + name: str = field(default_factory=str) + type: str = field(default_factory=str) + + +@dataclass +class GripperData(ToolData): + pass + + +@dataclass +class ParallelGripperData(GripperData): + pass + + +@dataclass +class MultifingerGripperData(GripperData): + pass + + +@dataclass +class VacuumGripperData(GripperData): + pass + + +class GripperEnum(Enum): + parallel = ParallelGripperData + mulrifinger = MultifingerGripperData + vacuum = VacuumGripperData + + +@dataclass +class RobotRandomizerData: + """ + RobotRandomizerData stores configuration parameters for randomizing robot properties during simulation. + + Attributes: + ---------- + pose : bool + Flag indicating whether to randomize the robot's pose (position and orientation). Default is False. + spawn_volume : tuple[float, float, float] + The volume within which the robot can be spawned, defined by (x, y, z) dimensions. Default is (1.0, 1.0, 0.0). + joint_positions : bool + Flag indicating whether to randomize the robot's joint positions. Default is False. + joint_positions_std : float + The standard deviation for randomizing the robot's joint positions. Default is 0.1. + joint_positions_above_object_spawn : bool + Flag indicating whether the robot's joint positions should be randomized to place the robot above the object's spawn position. Default is False. + joint_positions_above_object_spawn_elevation : float + The elevation above the object's spawn position when placing the robot's joints. Default is 0.2. + joint_positions_above_object_spawn_xy_randomness : float + The randomness in the x and y coordinates when placing the robot's joints above the object's spawn position. Default is 0.2. + """ + + pose: bool = field(default=False) + spawn_volume: tuple[float, float, float] = field(default=(1.0, 1.0, 0.0)) + joint_positions: bool = field(default=False) + joint_positions_std: float = field(default=0.1) + joint_positions_above_object_spawn: bool = field(default=False) + joint_positions_above_object_spawn_elevation: float = field(default=0.2) + joint_positions_above_object_spawn_xy_randomness: float = field(default=0.2) + + +@dataclass +class RobotData: + """ + RobotData stores the base properties and configurations for a robot in the simulation. + + Attributes: + ---------- + name : str + The name of the robot. Default is an empty string. + urdf_string : str + Optional parameter that can store a URDF. This parameter is overridden by the node parameters if set in the node configuration. + spawn_position : tuple[float, float, float] + The position where the robot will be spawned in (x, y, z) coordinates. Default is (0.0, 0.0, 0.0). + spawn_quat_xyzw : tuple[float, float, float, float] + The orientation of the robot in quaternion format (x, y, z, w) at spawn. Default is (0.0, 0.0, 0.0, 1.0). + joint_positions : list[float] + A list of the robot's joint positions. Default is an empty list. + with_gripper : bool + Flag indicating whether the robot is equipped with a gripper. Default is False. + gripper_joint_positions : list[float] | float + The joint positions for the gripper. Can be a list of floats or a single float. Default is an empty list. + randomizer : RobotRandomizerData + The randomization settings for the robot, allowing various properties to be randomized in simulation. Default is an instance of RobotRandomizerData. + """ + + name: str = field(default_factory=str) + urdf_string: str = field(default_factory=str) + spawn_position: tuple[float, float, float] = field(default=(0.0, 0.0, 0.0)) + spawn_quat_xyzw: tuple[float, float, float, float] = field( + default=(0.0, 0.0, 0.0, 1.0) + ) + joint_positions: list[float] = field(default_factory=list) + with_gripper: bool = field(default=False) + gripper_joint_positions: list[float] | float = field(default_factory=list) + randomizer: RobotRandomizerData = field(default_factory=RobotRandomizerData) diff --git a/env_manager/env_manager/env_manager/models/configs/scene.py b/env_manager/env_manager/env_manager/models/configs/scene.py new file mode 100644 index 0000000..94d078f --- /dev/null +++ b/env_manager/env_manager/env_manager/models/configs/scene.py @@ -0,0 +1,68 @@ +from dataclasses import dataclass, field + +from .camera import CameraData +from .light import LightData +from .objects import ObjectData +from .robot import RobotData +from .terrain import TerrainData + + +@dataclass +class PluginsData: + """ + PluginsData stores the configuration for various plugins used in the simulation environment. + + Attributes: + ---------- + scene_broadcaster : bool + Flag indicating whether the scene broadcaster plugin is enabled. Default is False. + user_commands : bool + Flag indicating whether the user commands plugin is enabled. Default is False. + fts_broadcaster : bool + Flag indicating whether the force torque sensor (FTS) broadcaster plugin is enabled. Default is False. + sensors_render_engine : str + The rendering engine used for sensors. Default is "ogre2". + """ + + scene_broadcaster: bool = field(default_factory=bool) + user_commands: bool = field(default_factory=bool) + fts_broadcaster: bool = field(default_factory=bool) + sensors_render_engine: str = field(default="ogre2") + + +@dataclass +class SceneData: + """ + SceneData contains the configuration and settings for the simulation scene. + + Attributes: + ---------- + physics_rollouts_num : int + The number of physics rollouts to perform in the simulation. Default is 0. + gravity : tuple[float, float, float] + The gravitational acceleration vector applied in the scene, represented as (x, y, z). Default is (0.0, 0.0, -9.80665). + gravity_std : tuple[float, float, float] + The standard deviation for the gravitational acceleration, represented as (x, y, z). Default is (0.0, 0.0, 0.0232). + robot : RobotData + The configuration data for the robot present in the scene. Default is an instance of RobotData. + terrain : TerrainData + The configuration data for the terrain in the scene. Default is an instance of TerrainData. + light : LightData + The configuration data for the lighting in the scene. Default is an instance of LightData. + objects : list[ObjectData] + A list of objects present in the scene, represented by their ObjectData configurations. Default is an empty list. + camera : list[CameraData] + A list of cameras in the scene, represented by their CameraData configurations. Default is an empty list. + plugins : PluginsData + The configuration data for various plugins utilized in the simulation environment. Default is an instance of PluginsData. + """ + + physics_rollouts_num: int = field(default=0) + gravity: tuple[float, float, float] = field(default=(0.0, 0.0, -9.80665)) + gravity_std: tuple[float, float, float] = field(default=(0.0, 0.0, 0.0232)) + robot: RobotData = field(default_factory=RobotData) + terrain: TerrainData = field(default_factory=TerrainData) + light: LightData = field(default_factory=LightData) + objects: list[ObjectData] = field(default_factory=list) + camera: list[CameraData] = field(default_factory=list) + plugins: PluginsData = field(default_factory=PluginsData) diff --git a/env_manager/env_manager/env_manager/models/configs/terrain.py b/env_manager/env_manager/env_manager/models/configs/terrain.py new file mode 100644 index 0000000..f240132 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/configs/terrain.py @@ -0,0 +1,33 @@ +from dataclasses import dataclass, field + + +@dataclass +class TerrainData: + """ + TerrainData stores the configuration for the terrain in the simulation environment. + + Attributes: + ---------- + name : str + The name of the terrain. Default is "ground". + type : str + The type of terrain (e.g., "flat", "hilly", "uneven"). Default is "flat". + spawn_position : tuple[float, float, float] + The position where the terrain will be spawned in the simulation, represented as (x, y, z). Default is (0, 0, 0). + spawn_quat_xyzw : tuple[float, float, float, float] + The orientation of the terrain at spawn, represented as a quaternion (x, y, z, w). Default is (0, 0, 0, 1). + size : tuple[float, float] + The size of the terrain, represented as (width, length). Default is (1.5, 1.5). + model_rollouts_num : int + The number of rollouts for randomizing terrain models. Default is 1. + """ + + name: str = field(default="ground") + type: str = field(default="flat") + spawn_position: tuple[float, float, float] = field(default=(0, 0, 0)) + spawn_quat_xyzw: tuple[float, float, float, float] = field(default=(0, 0, 0, 1)) + size: tuple[float, float] = field(default=(1.5, 1.5)) + ambient: tuple[float, float, float, float] = field(default=(0.8, 0.8, 0.8, 1.0)) + specular: tuple[float, float, float, float] = field(default=(0.8, 0.8, 0.8, 1.0)) + diffuse: tuple[float, float, float, float] = field(default=(0.8, 0.8, 0.8, 1.0)) + model_rollouts_num: int = field(default=1) diff --git a/env_manager/env_manager/env_manager/models/lights/__init__.py b/env_manager/env_manager/env_manager/models/lights/__init__.py new file mode 100644 index 0000000..f791750 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/lights/__init__.py @@ -0,0 +1,34 @@ +from enum import Enum +from gym_gz.scenario.model_wrapper import ModelWrapper + +from .random_sun import RandomSun +from .sun import Sun + + +# Enum для типов света +class LightType(Enum): + SUN = "sun" + RANDOM_SUN = "random_sun" + + +LIGHT_MODEL_CLASSES = { + LightType.SUN: Sun, + LightType.RANDOM_SUN: RandomSun, +} + + +def get_light_model_class(light_type: str) -> type[ModelWrapper]: + try: + light_enum = LightType(light_type) + return LIGHT_MODEL_CLASSES[light_enum] + except KeyError: + raise ValueError(f"Unsupported light type: {light_type}") + + +def is_light_type_randomizable(light_type: str) -> bool: + try: + light_enum = LightType(light_type) + return light_enum == LightType.RANDOM_SUN + except ValueError: + return False + diff --git a/env_manager/env_manager/env_manager/models/lights/random_sun.py b/env_manager/env_manager/env_manager/models/lights/random_sun.py new file mode 100644 index 0000000..e91f56c --- /dev/null +++ b/env_manager/env_manager/env_manager/models/lights/random_sun.py @@ -0,0 +1,240 @@ +import numpy as np +from gym_gz.scenario import model_wrapper +from gym_gz.utils.scenario import get_unique_model_name +from numpy.random import RandomState +from scenario import core as scenario +from scenario import core as scenario_core +from scenario import gazebo as scenario_gazebo + + +class RandomSun(model_wrapper.ModelWrapper): + """ + RandomSun is a class that creates a randomly positioned directional light (like the Sun) in a simulation world. + + Attributes: + ---------- + world : scenario_gazebo.World + The simulation world where the model is inserted. + name : str + The name of the sun model. Default is "sun". + minmax_elevation : tuple[float, float] + Minimum and maximum values for the random elevation angle of the sun. Default is (-0.15, -0.65). + distance : float + Distance from the origin to the sun in the simulation. Default is 800.0. + visual : bool + Flag indicating whether the sun should have a visual sphere in the simulation. Default is True. + radius : float + Radius of the visual sphere representing the sun. Default is 20.0. + color_minmax_r : tuple[float, float] + Range for the red component of the sun's light color. Default is (1.0, 1.0). + color_minmax_g : tuple[float, float] + Range for the green component of the sun's light color. Default is (1.0, 1.0). + color_minmax_b : tuple[float, float] + Range for the blue component of the sun's light color. Default is (1.0, 1.0). + specular : float + The specular factor for the sun's light. Default is 1.0. + attenuation_minmax_range : tuple[float, float] + Range for the light attenuation (falloff) distance. Default is (750.0, 15000.0). + attenuation_minmax_constant : tuple[float, float] + Range for the constant component of the light attenuation. Default is (0.5, 1.0). + attenuation_minmax_linear : tuple[float, float] + Range for the linear component of the light attenuation. Default is (0.001, 0.1). + attenuation_minmax_quadratic : tuple[float, float] + Range for the quadratic component of the light attenuation. Default is (0.0001, 0.01). + np_random : RandomState | None + Random state for generating random values. Default is None, in which case a new random generator is created. + + Raises: + ------- + RuntimeError: + Raised if the sun model fails to be inserted into the world. + + Methods: + -------- + get_sdf(): + Generates the SDF string for the sun model. + """ + + def __init__( + self, + world: scenario_gazebo.World, + name: str = "sun", + minmax_elevation: tuple[float, float] = (-0.15, -0.65), + distance: float = 800.0, + visual: bool = True, + radius: float = 20.0, + color_minmax_r: tuple[float, float] = (1.0, 1.0), + color_minmax_g: tuple[float, float] = (1.0, 1.0), + color_minmax_b: tuple[float, float] = (1.0, 1.0), + specular: float = 1.0, + attenuation_minmax_range: tuple[float, float] = (750.0, 15000.0), + attenuation_minmax_constant: tuple[float, float] = (0.5, 1.0), + attenuation_minmax_linear: tuple[float, float] = (0.001, 0.1), + attenuation_minmax_quadratic: tuple[float, float] = (0.0001, 0.01), + np_random: RandomState | None = None, + **kwargs, + ): + if np_random is None: + np_random = np.random.default_rng() + + # Get a unique model name + model_name = get_unique_model_name(world, name) + + # Get random yaw direction + direction = np_random.uniform(-1.0, 1.0, (2,)) + # Normalize yaw direction + direction = direction / np.linalg.norm(direction) + + # Get random elevation + direction = np.append( + direction, + np_random.uniform(minmax_elevation[0], minmax_elevation[1]), + ) + # Normalize again + direction = direction / np.linalg.norm(direction) + + # Initial pose + initial_pose = scenario_core.Pose( + ( + -direction[0] * distance, + -direction[1] * distance, + -direction[2] * distance, + ), + (1, 0, 0, 0), + ) + + # Create SDF string for the model + sdf = self.get_sdf( + model_name=model_name, + direction=tuple(direction), + visual=visual, + radius=radius, + color_minmax_r=color_minmax_r, + color_minmax_g=color_minmax_g, + color_minmax_b=color_minmax_b, + attenuation_minmax_range=attenuation_minmax_range, + attenuation_minmax_constant=attenuation_minmax_constant, + attenuation_minmax_linear=attenuation_minmax_linear, + attenuation_minmax_quadratic=attenuation_minmax_quadratic, + specular=specular, + np_random=np_random, + ) + + # Insert the model + ok_model = world.to_gazebo().insert_model_from_string( + sdf, initial_pose, model_name + ) + if not ok_model: + raise RuntimeError("Failed to insert " + model_name) + + # Get the model + model = world.get_model(model_name) + + # Initialize base class + model_wrapper.ModelWrapper.__init__(self, model=model) + + @classmethod + def get_sdf( + self, + model_name: str, + direction: tuple[float, float, float], + visual: bool, + radius: float, + color_minmax_r: tuple[float, float], + color_minmax_g: tuple[float, float], + color_minmax_b: tuple[float, float], + attenuation_minmax_range: tuple[float, float], + attenuation_minmax_constant: tuple[float, float], + attenuation_minmax_linear: tuple[float, float], + attenuation_minmax_quadratic: tuple[float, float], + specular: float, + np_random: RandomState, + ) -> str: + """ + Generates the SDF string for the sun model. + + Args: + ----- + model_name : str + The name of the model. + direction : Tuple[float, float, float] + The direction of the sun's light. + visual : bool + If True, a visual representation of the sun will be created. + radius : float + The radius of the visual representation. + color_minmax_r : Tuple[float, float] + Range for the red component of the light color. + color_minmax_g : Tuple[float, float] + Range for the green component of the light color. + color_minmax_b : Tuple[float, float] + Range for the blue component of the light color. + attenuation_minmax_range : Tuple[float, float] + Range for light attenuation distance. + attenuation_minmax_constant : Tuple[float, float] + Range for the constant attenuation factor. + attenuation_minmax_linear : Tuple[float, float] + Range for the linear attenuation factor. + attenuation_minmax_quadratic : Tuple[float, float] + Range for the quadratic attenuation factor. + specular : float + The specular reflection factor for the light. + np_random : RandomState + The random number generator used to sample random values for the parameters. + + Returns: + -------- + str: + The SDF string for the sun model. + """ + # Sample random values for parameters + color_r = np_random.uniform(color_minmax_r[0], color_minmax_r[1]) + color_g = np_random.uniform(color_minmax_g[0], color_minmax_g[1]) + color_b = np_random.uniform(color_minmax_b[0], color_minmax_b[1]) + attenuation_range = np_random.uniform( + attenuation_minmax_range[0], attenuation_minmax_range[1] + ) + attenuation_constant = np_random.uniform( + attenuation_minmax_constant[0], attenuation_minmax_constant[1] + ) + attenuation_linear = np_random.uniform( + attenuation_minmax_linear[0], attenuation_minmax_linear[1] + ) + attenuation_quadratic = np_random.uniform( + attenuation_minmax_quadratic[0], attenuation_minmax_quadratic[1] + ) + + return f''' + + true + + + {direction[0]} {direction[1]} {direction[2]} + + {attenuation_range} + {attenuation_constant} + {attenuation_linear} + {attenuation_quadratic} + + {color_r} {color_g} {color_b} 1 + {specular*color_r} {specular*color_g} {specular*color_b} 1 + true + + { + f""" + + + + {radius} + + + + {color_r} {color_g} {color_b} 1 + + false + + """ if visual else "" + } + + + ''' diff --git a/env_manager/env_manager/env_manager/models/lights/sun.py b/env_manager/env_manager/env_manager/models/lights/sun.py new file mode 100644 index 0000000..a10c565 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/lights/sun.py @@ -0,0 +1,191 @@ +import numpy as np +from gym_gz.scenario import model_wrapper +from gym_gz.utils.scenario import get_unique_model_name +from scenario import core as scenario_core +from scenario import gazebo as scenario_gazebo + + +class Sun(model_wrapper.ModelWrapper): + """ + Sun is a class that represents a directional light source in the simulation, similar to the Sun. + + It can have both visual and light properties, with customizable parameters such as color, direction, and attenuation. + + Attributes: + ---------- + world : scenario_gazebo.World + The Gazebo world where the sun model will be inserted. + name : str + The name of the sun model. Default is "sun". + direction : tuple[float, float, float] + The direction of the sunlight, normalized. Default is (0.5, -0.25, -0.75). + color : tuple[float, float, float, float] + The RGBA color values for the light's diffuse color. Default is (1.0, 1.0, 1.0, 1.0). + distance : float + The distance from the origin to the sun. Default is 800.0. + visual : bool + If True, a visual representation of the sun will be added. Default is True. + radius : float + The radius of the visual representation of the sun. Default is 20.0. + specular : float + The intensity of the specular reflection. Default is 1.0. + attenuation_range : float + The maximum range for the light attenuation. Default is 10000.0. + attenuation_constant : float + The constant attenuation factor. Default is 0.9. + attenuation_linear : float + The linear attenuation factor. Default is 0.01. + attenuation_quadratic : float + The quadratic attenuation factor. Default is 0.001. + + Raises: + ------- + RuntimeError: + If the sun model fails to be inserted into the Gazebo world. + + Methods: + -------- + get_sdf() -> str: + Generates the SDF string used to describe the sun model in the Gazebo simulation. + """ + + def __init__( + self, + world: scenario_gazebo.World, + name: str = "sun", + direction: tuple[float, float, float] = (0.5, -0.25, -0.75), + color: tuple[float, float, float, float] = (1.0, 1.0, 1.0, 1.0), + distance: float = 800.0, + visual: bool = True, + radius: float = 20.0, + specular: float = 1.0, + attenuation_range: float = 10000.0, + attenuation_constant: float = 0.9, + attenuation_linear: float = 0.01, + attenuation_quadratic: float = 0.001, + **kwargs, + ): + # Get a unique model name + model_name = get_unique_model_name(world, name) + + # Normalize direction + np_direction = np.array(direction) + np_direction = np_direction / np.linalg.norm(np_direction) + + # Initial pose + initial_pose = scenario_core.Pose( + ( + -np_direction[0] * distance, + -np_direction[1] * distance, + -np_direction[2] * distance, + ), + (1, 0, 0, 0), + ) + + # Create SDF string for the model + sdf = self.get_sdf( + model_name=model_name, + direction=tuple(np_direction), + color=color, + visual=visual, + radius=radius, + specular=specular, + attenuation_range=attenuation_range, + attenuation_constant=attenuation_constant, + attenuation_linear=attenuation_linear, + attenuation_quadratic=attenuation_quadratic, + ) + + # Insert the model + ok_model = world.to_gazebo().insert_model_from_string( + sdf, initial_pose, model_name + ) + if not ok_model: + raise RuntimeError("Failed to insert " + model_name) + + # Get the model + model = world.get_model(model_name) + + # Initialize base class + model_wrapper.ModelWrapper.__init__(self, model=model) + + @classmethod + def get_sdf( + cls, + model_name: str, + direction: tuple[float, float, float], + color: tuple[float, float, float, float], + visual: bool, + radius: float, + specular: float, + attenuation_range: float, + attenuation_constant: float, + attenuation_linear: float, + attenuation_quadratic: float, + ) -> str: + """ + Generates the SDF string for the sun model. + + Args: + ----- + model_name : str + The name of the sun model. + direction : tuple[float, float, float] + The direction vector for the sunlight. + color : tuple[float, float, float, float] + The RGBA color values for the sunlight. + visual : bool + Whether to include a visual representation of the sun (a sphere). + radius : float + The radius of the visual sphere. + specular : float + The specular reflection intensity. + attenuation_range : float + The range of the light attenuation. + attenuation_constant : float + The constant factor for the light attenuation. + attenuation_linear : float + The linear factor for the light attenuation. + attenuation_quadratic : float + The quadratic factor for the light attenuation. + + Returns: + -------- + str: + The SDF string for the sun model. + """ + + return f''' + + true + + + {direction[0]} {direction[1]} {direction[2]} + + {attenuation_range} + {attenuation_constant} + {attenuation_linear} + {attenuation_quadratic} + + {color[0]} {color[1]} {color[2]} 1 + {specular*color[0]} {specular*color[1]} {specular*color[2]} 1 + true + + { + f""" + + + + {radius} + + + + {color[0]} {color[1]} {color[2]} 1 + + false + + """ if visual else "" + } + + + ''' diff --git a/env_manager/env_manager/env_manager/models/objects/__init__.py b/env_manager/env_manager/env_manager/models/objects/__init__.py new file mode 100644 index 0000000..a1a70c6 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/objects/__init__.py @@ -0,0 +1,53 @@ +from enum import Enum + +from gym_gz.scenario.model_wrapper import ModelWrapper + +from .model import Model +from .mesh import Mesh +from .primitives import Box, Cylinder, Plane, Sphere +# from .random_object import RandomObject +from .random_primitive import RandomPrimitive + + +class ObjectType(Enum): + BOX = "box" + SPHERE = "sphere" + CYLINDER = "cylinder" + PLANE = "plane" + RANDOM_PRIMITIVE = "random_primitive" + RANDOM_MESH = "random_mesh" + MODEL = "model" + MESH = "mesh" + +OBJECT_MODEL_CLASSES = { + ObjectType.BOX: Box, + ObjectType.SPHERE: Sphere, + ObjectType.CYLINDER: Cylinder, + ObjectType.PLANE: Plane, + ObjectType.RANDOM_PRIMITIVE: RandomPrimitive, + # ObjectType.RANDOM_MESH: RandomObject, + ObjectType.MODEL: Model, + ObjectType.MESH: Mesh +} + + +RANDOMIZABLE_TYPES = { + ObjectType.RANDOM_PRIMITIVE, + ObjectType.RANDOM_MESH, +} + + +def get_object_model_class(object_type: str) -> type[ModelWrapper]: + try: + object_enum = ObjectType(object_type) + return OBJECT_MODEL_CLASSES[object_enum] + except KeyError: + raise ValueError(f"Unsupported object type: {object_type}") + + +def is_object_type_randomizable(object_type: str) -> bool: + try: + object_enum = ObjectType(object_type) + return object_enum in RANDOMIZABLE_TYPES + except ValueError: + return False diff --git a/env_manager/env_manager/env_manager/models/objects/mesh.py b/env_manager/env_manager/env_manager/models/objects/mesh.py new file mode 100644 index 0000000..f467dfd --- /dev/null +++ b/env_manager/env_manager/env_manager/models/objects/mesh.py @@ -0,0 +1,183 @@ +import numpy as np +import trimesh +from gym_gz.scenario import model_wrapper +from gym_gz.utils.scenario import get_unique_model_name +from scenario import core as scenario_core +from scenario import gazebo as scenario_gazebo +from trimesh import Trimesh + +from env_manager.utils.types import Point + +InertiaTensor = tuple[float, float, float, float, float, float] + + +class Mesh(model_wrapper.ModelWrapper): + """ """ + + def __init__( + self, + world: scenario_gazebo.World, + name: str = "object", + type: str = "mesh", + relative_to: str = "world", + position: tuple[float, float, float] = (0, 0, 0), + orientation: tuple[float, float, float, float] = (1, 0, 0, 0), + color: tuple[float, float, float, float] | None = None, + static: bool = False, + texture: list[float] = [], + mass: float = 0.0, + inertia: InertiaTensor | None = None, + cm: Point | None = None, + collision: str = "", + visual: str = "", + friction: float = 0.0, + density: float = 0.0, + **kwargs, + ): + # Get a unique model name + model_name = get_unique_model_name(world, name) + + # Initial pose + initial_pose = scenario_core.Pose(position, orientation) + + # Calculate inertia parameters for provided mesh file if not exist + if not inertia and collision and density: + mass, cm, inertia = self.calculate_inertia(collision, density) + else: + raise RuntimeError( + f"Please provide collision mesh filepath for model {name} to calculate inertia" + ) + + if not color: + color = tuple(np.random.uniform(0.0, 1.0, (3,))) + color = (color[0], color[1], color[2], 1.0) + + # Create SDF string for the model + sdf = self.get_sdf( + name=name, + static=static, + collision=collision, + visual=visual, + mass=mass, + inertia=inertia, + friction=friction, + color=color, + center_of_mass=cm, + gui_only=True, + ) + + # Insert the model + ok_model = world.to_gazebo().insert_model_from_string( + sdf, initial_pose, model_name + ) + if not ok_model: + raise RuntimeError(f"Failed to insert {model_name}") + # Get the model + model = world.get_model(model_name) + + # Initialize base class + super().__init__(model=model) + + def calculate_inertia(self, file_path, density): + mesh = trimesh.load(file_path) + + if not isinstance(mesh, Trimesh): + raise RuntimeError("Please provide correct stl mesh filepath") + + volume = mesh.volume + mass: float = volume * density + center_of_mass: Point = tuple(mesh.center_mass) + inertia = mesh.moment_inertia + eigenvalues = np.linalg.eigvals(inertia) + inertia_tensor: InertiaTensor = ( + inertia[0, 0], + inertia[0, 1], + inertia[0, 2], + inertia[1, 1], + inertia[1, 2], + inertia[2, 2], + ) + return mass, center_of_mass, inertia_tensor + + @classmethod + def get_sdf( + cls, + name: str, + static: bool, + collision: str, + visual: str, + mass: float, + inertia: InertiaTensor, + friction: float, + color: tuple[float, float, float, float], + center_of_mass: Point, + gui_only: bool, + ) -> str: + """ + Generates the SDF string for the box model. + + Args: + - mesh_args (MeshPureData): Object that contain data of provided mesh data + + Returns: + The SDF string that defines the box model in Gazebo. + """ + return f''' + + {"true" if static else "false"} + + { + f""" + + + + {collision} + + + + + + {friction} + {friction} + 0 0 0 + 0.0 + 0.0 + + + + + """ if collision else "" + } + { + f""" + + + + {visual} + + + + {color[0]} {color[1]} {color[2]} {color[3]} + {color[0]} {color[1]} {color[2]} {color[3]} + {color[0]} {color[1]} {color[2]} {color[3]} + + {1.0 - color[3]} + {'1 false' if gui_only else ''} + + """ if visual else "" + } + + {mass} + {center_of_mass[0]} {center_of_mass[1]} {center_of_mass[2]} 0 0 0 + + {inertia[0]} + {inertia[1]} + {inertia[2]} + {inertia[3]} + {inertia[4]} + {inertia[5]} + + + + + ''' diff --git a/env_manager/env_manager/env_manager/models/objects/model.py b/env_manager/env_manager/env_manager/models/objects/model.py new file mode 100644 index 0000000..1f6de89 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/objects/model.py @@ -0,0 +1,75 @@ +from gym_gz.scenario import model_wrapper +from gym_gz.utils.scenario import get_unique_model_name +from rbs_assets_library import get_model_file +from scenario import core as scenario_core +from scenario import gazebo as scenario_gazebo + + +class Model(model_wrapper.ModelWrapper): + """ + Represents a 3D mesh model in the Gazebo simulation environment. + This class is responsible for loading and inserting a mesh model + into the Gazebo world with specified attributes. + + Args: + world (scenario_gazebo.World): The Gazebo world where the mesh model will be inserted. + name (str, optional): The name of the mesh model. Defaults to "object". + position (tuple[float, float, float], optional): The position of the mesh in the world. Defaults to (0, 0, 0). + orientation (tuple[float, float, float, float], optional): The orientation of the mesh in quaternion format. Defaults to (1, 0, 0, 0). + gui_only (bool, optional): If True, the visual representation of the mesh will only appear in the GUI. Defaults to False. + **kwargs: Additional keyword arguments. + + Raises: + RuntimeError: If the mesh model fails to be inserted into the Gazebo world. + + Methods: + get_sdf(model_name: str) -> str: + Generates the SDF string used to describe the mesh model in the Gazebo simulation. + """ + + def __init__( + self, + world: scenario_gazebo.World, + name: str = "object", + position: tuple[float, float, float] = (0, 0, 0), + orientation: tuple[float, float, float, float] = (1, 0, 0, 0), + gui_only: bool = False, + **kwargs, + ): + # Get a unique model name + model_name = get_unique_model_name(world, name) + + # Initial pose + initial_pose = scenario_core.Pose(position, orientation) + + # Create SDF string for the model + sdf = self.get_sdf( + model_name=name, + ) + + # Insert the model + ok_model = world.to_gazebo().insert_model(sdf, initial_pose, model_name) + if not ok_model: + raise RuntimeError("Failed to insert " + model_name) + + # Get the model + model = world.get_model(model_name) + + # Initialize base class + super().__init__(model=model) + + @classmethod + def get_sdf( + cls, + model_name: str, + ) -> str: + """ + Generates the SDF string for the specified mesh model. + + Args: + model_name (str): The name of the mesh model to generate the SDF for. + + Returns: + str: The SDF string that defines the mesh model in Gazebo. + """ + return get_model_file(model_name) diff --git a/env_manager/env_manager/env_manager/models/objects/primitives/__init__.py b/env_manager/env_manager/env_manager/models/objects/primitives/__init__.py new file mode 100644 index 0000000..0dcf311 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/objects/primitives/__init__.py @@ -0,0 +1,4 @@ +from .box import Box +from .cylinder import Cylinder +from .plane import Plane +from .sphere import Sphere diff --git a/env_manager/env_manager/env_manager/models/objects/primitives/box.py b/env_manager/env_manager/env_manager/models/objects/primitives/box.py new file mode 100644 index 0000000..fae02bb --- /dev/null +++ b/env_manager/env_manager/env_manager/models/objects/primitives/box.py @@ -0,0 +1,176 @@ +import numpy as np +from gym_gz.scenario import model_wrapper +from gym_gz.utils.scenario import get_unique_model_name +from scenario import core as scenario_core +from scenario import gazebo as scenario_gazebo + + +class Box(model_wrapper.ModelWrapper): + """ + The Box class represents a 3D box model in the Gazebo simulation environment. + It includes physical and visual properties such as size, mass, color, and collision properties. + + Attributes: + world (scenario_gazebo.World): The Gazebo world where the box model will be inserted. + name (str): The name of the box model. Default is "box". + position (tuple[float, float, float]): The position of the box in the world. Default is (0, 0, 0). + orientation (tuple[float, float, float, float]): The orientation of the box in quaternion format. Default is (1, 0, 0, 0). + size (tuple[float, float, float]): The size of the box (width, length, height). Default is (0.05, 0.05, 0.05). + mass (float): The mass of the box in kilograms. Default is 0.1. + static (bool): If True, the box will be immovable and static. Default is False. + collision (bool): If True, the box will have collision properties. Default is True. + friction (float): The friction coefficient for the box’s surface. Default is 1.0. + visual (bool): If True, the box will have a visual representation. Default is True. + gui_only (bool): If True, the visual representation of the box will only appear in the GUI, not in the simulation physics. Default is False. + color (tuple[float, float, float, float]): The RGBA color of the box. Default is (0.8, 0.8, 0.8, 1.0). + + Raises: + RuntimeError: + If the box model fails to be inserted into the Gazebo world. + + Methods: + -------- + get_sdf() -> str: + Generates the SDF string used to describe the box model in the Gazebo simulation. + """ + + def __init__( + self, + world: scenario_gazebo.World, + name: str = "box", + position: tuple[float, float, float] = (0, 0, 0), + orientation: tuple[float, float, float, float] = (1, 0, 0, 0), + size: tuple[float, float, float] = (0.05, 0.05, 0.05), + mass: float = 0.1, + static: bool = False, + collision: bool = True, + friction: float = 1.0, + visual: bool = True, + gui_only: bool = False, + color: tuple[float, float, float, float] | None = None, + **kwargs, + ): + # Get a unique model name + model_name = get_unique_model_name(world, name) + + # Initial pose + initial_pose = scenario_core.Pose(position, orientation) + + if not color: + color = tuple(np.random.uniform(0.0, 1.0, (3,))) + color = (color[0], color[1], color[2], 1.0) + + # Create SDF string for the model + sdf = self.get_sdf( + model_name=model_name, + size=size, + mass=mass, + static=static, + collision=collision, + friction=friction, + visual=visual, + gui_only=gui_only, + color=color, + ) + + # Insert the model + ok_model = world.to_gazebo().insert_model_from_string( + sdf, initial_pose, model_name + ) + if not ok_model: + raise RuntimeError(f"Failed to insert {model_name}") + + # Get the model + model = world.get_model(model_name) + + # Initialize base class + super().__init__(model=model) + + @classmethod + def get_sdf( + cls, + model_name: str, + size: tuple[float, float, float], + mass: float, + static: bool, + collision: bool, + friction: float, + visual: bool, + gui_only: bool, + color: tuple[float, float, float, float], + ) -> str: + """ + Generates the SDF string for the box model. + + Args: + model_name (str): The name of the box model. + size (tuple[float, float, float]): The dimensions of the box (width, length, height). + mass (float): The mass of the box. + static (bool): If True, the box will be static and immovable. + collision (bool): If True, the box will have collision properties. + friction (float): The friction coefficient for the box. + visual (bool): If True, the box will have a visual representation. + gui_only (bool): If True, the box's visual representation will only appear in the GUI and will not affect physics. + color (tuple[float, float, float, float]): The RGBA color of the box. + + Returns: + The SDF string that defines the box model in Gazebo. + """ + return f''' + + {"true" if static else "false"} + + { + f""" + + + + {size[0]} {size[1]} {size[2]} + + + + + + {friction} + {friction} + 0 0 0 + 0.0 + 0.0 + + + + + """ if collision else "" + } + { + f""" + + + + {size[0]} {size[1]} {size[2]} + + + + {color[0]} {color[1]} {color[2]} {color[3]} + {color[0]} {color[1]} {color[2]} {color[3]} + {color[0]} {color[1]} {color[2]} {color[3]} + + {1.0 - color[3]} + {'1 false' if gui_only else ''} + + """ if visual else "" + } + + {mass} + + {(size[1]**2 + size[2]**2) * mass / 12} + {(size[0]**2 + size[2]**2) * mass / 12} + {(size[0]**2 + size[1]**2) * mass / 12} + 0.0 + 0.0 + 0.0 + + + + + ''' diff --git a/env_manager/env_manager/env_manager/models/objects/primitives/cylinder.py b/env_manager/env_manager/env_manager/models/objects/primitives/cylinder.py new file mode 100644 index 0000000..38df76f --- /dev/null +++ b/env_manager/env_manager/env_manager/models/objects/primitives/cylinder.py @@ -0,0 +1,173 @@ +import numpy as np +from gym_gz.scenario import model_wrapper +from gym_gz.utils.scenario import get_unique_model_name +from scenario import core as scenario_core +from scenario import gazebo as scenario_gazebo + + +class Cylinder(model_wrapper.ModelWrapper): + """ + The Cylinder class represents a cylindrical model in the Gazebo simulation environment. + + Attributes: + world (scenario_gazebo.World): The Gazebo world where the cylinder model will be inserted. + name (str): The name of the cylinder model. Default is "cylinder". + position (tuple[float, float, float]): The position of the cylinder in the world. Default is (0, 0, 0). + orientation (tuple[float, float, float, float]): The orientation of the cylinder in quaternion format. Default is (1, 0, 0, 0). + radius (float): The radius of the cylinder. Default is 0.025. + length (float): The length/height of the cylinder. Default is 0.1. + mass (float): The mass of the cylinder in kilograms. Default is 0.1. + static (bool): If True, the cylinder will be immovable. Default is False. + collision (bool): If True, the cylinder will have collision properties. Default is True. + friction (float): The friction coefficient for the cylinder's surface. Default is 1.0. + visual (bool): If True, the cylinder will have a visual representation. Default is True. + gui_only (bool): If True, the visual representation of the cylinder will only appear in the GUI, not in the simulation physics. Default is False. + color (tuple[float, float, float, float]): The RGBA color of the cylinder. Default is (0.8, 0.8, 0.8, 1.0). + + Raises: + RuntimeError: If the cylinder model fails to be inserted into the Gazebo world. + + """ + + def __init__( + self, + world: scenario_gazebo.World, + name: str = "cylinder", + position: tuple[float, float, float] = (0, 0, 0), + orientation: tuple[float, float, float, float] = (1, 0, 0, 0), + radius: float = 0.025, + length: float = 0.1, + mass: float = 0.1, + static: bool = False, + collision: bool = True, + friction: float = 1.0, + visual: bool = True, + gui_only: bool = False, + color: tuple[float, float, float, float] | None = None, + **kwargs, + ): + model_name = get_unique_model_name(world, name) + + initial_pose = scenario_core.Pose(position, orientation) + + if not color: + color = tuple(np.random.uniform(0.0, 1.0, (3,))) + color = (color[0], color[1], color[2], 1.0) + + sdf = self.get_sdf( + model_name=model_name, + radius=radius, + length=length, + mass=mass, + static=static, + collision=collision, + friction=friction, + visual=visual, + gui_only=gui_only, + color=color, + ) + + ok_model = world.to_gazebo().insert_model_from_string( + sdf, initial_pose, model_name + ) + if not ok_model: + raise RuntimeError(f"Failed to insert {model_name}") + + model = world.get_model(model_name) + + super().__init__(model=model) + + @classmethod + def get_sdf( + cls, + model_name: str, + radius: float, + length: float, + mass: float, + static: bool, + collision: bool, + friction: float, + visual: bool, + gui_only: bool, + color: tuple[float, float, float, float], + ) -> str: + """ + Generates the SDF string for the cylinder model. + + Args: + model_name (str): The name of the model. + radius (float): The radius of the cylinder. + length (float): The length or height of the cylinder. + mass (float): The mass of the cylinder in kilograms. + static (bool): If True, the cylinder will remain immovable in the simulation. + collision (bool): If True, adds collision properties to the cylinder. + friction (float): The friction coefficient for the cylinder's surface. + visual (bool): If True, a visual representation of the cylinder will be created. + gui_only (bool): If True, the visual representation will only appear in the GUI, without impacting the simulation's physics. + color (tuple[float, float, float, float]): The RGBA color of the cylinder, where each value is between 0 and 1. + + Returns: + str: The SDF string representing the cylinder model + """ + inertia_xx_yy = (3 * radius**2 + length**2) * mass / 12 + + return f''' + + {"true" if static else "false"} + + { + f""" + + + + {radius} + {length} + + + + + + {friction} + {friction} + 0 0 0 + 0.0 + 0.0 + + + + + """ if collision else "" + } + { + f""" + + + + {radius} + {length} + + + + {color[0]} {color[1]} {color[2]} {color[3]} + {color[0]} {color[1]} {color[2]} {color[3]} + {color[0]} {color[1]} {color[2]} {color[3]} + + {1.0-color[3]} + {'1 false' if gui_only else ''} + + """ if visual else "" + } + + {mass} + + {inertia_xx_yy} + {inertia_xx_yy} + {(mass*radius**2)/2} + 0.0 + 0.0 + 0.0 + + + + + ''' diff --git a/env_manager/env_manager/env_manager/models/objects/primitives/plane.py b/env_manager/env_manager/env_manager/models/objects/primitives/plane.py new file mode 100644 index 0000000..ffbeefb --- /dev/null +++ b/env_manager/env_manager/env_manager/models/objects/primitives/plane.py @@ -0,0 +1,100 @@ +from gym_gz.scenario import model_wrapper +from gym_gz.utils.scenario import get_unique_model_name +from scenario import core as scenario_core +from scenario import gazebo as scenario_gazebo + + +class Plane(model_wrapper.ModelWrapper): + """ + The Plane class represents a plane model in the Gazebo simulation environment. + It allows for defining a flat surface with collision and visual properties, as well as its orientation and friction settings. + + Attributes: + world (scenario_gazebo.World): The Gazebo world where the plane model will be inserted. + name (str): The name of the plane model. Default is "plane". + position (tuple[float, float, float]): The position of the plane in the world. Default is (0, 0, 0). + orientation (tuple[float, float, float, float]): The orientation of the plane in quaternion format. Default is (1, 0, 0, 0). + size (tuple[float, float]): The size of the plane along the x and y axes. Default is (1.0, 1.0). + direction (tuple[float, float, float]): The normal vector representing the plane's direction. Default is (0.0, 0.0, 1.0), representing a horizontal plane. + collision (bool): If True, the plane will have collision properties. Default is True. + friction (float): The friction coefficient for the plane's surface. Default is 1.0. + visual (bool): If True, the plane will have a visual representation. Default is True. + + Raises: + RuntimeError: If the plane model fails to be inserted into the Gazebo world. + """ + + def __init__( + self, + world: scenario_gazebo.World, + name: str = "plane", + position: tuple[float, float, float] = (0, 0, 0), + orientation: tuple[float, float, float, float] = (1, 0, 0, 0), + size: tuple[float, float] = (1.0, 1.0), + direction: tuple[float, float, float] = (0.0, 0.0, 1.0), + collision: bool = True, + friction: float = 1.0, + visual: bool = True, + **kwargs, + ): + model_name = get_unique_model_name(world, name) + + initial_pose = scenario_core.Pose(position, orientation) + + sdf = f''' + + true + + { + f""" + + + + {direction[0]} {direction[1]} {direction[2]} + {size[0]} {size[1]} + + + + + + {friction} + {friction} + 0 0 0 + 0.0 + 0.0 + + + + + """ if collision else "" + } + { + f""" + + + + {direction[0]} {direction[1]} {direction[2]} + {size[0]} {size[1]} + + + + 0.8 0.8 0.8 1 + 0.8 0.8 0.8 1 + 0.8 0.8 0.8 1 + + + """ if visual else "" + } + + + ''' + + ok_model = world.to_gazebo().insert_model_from_string( + sdf, initial_pose, model_name + ) + if not ok_model: + raise RuntimeError(f"Failed to insert {model_name}") + + model = world.get_model(model_name) + + super().__init__(model=model) diff --git a/env_manager/env_manager/env_manager/models/objects/primitives/sphere.py b/env_manager/env_manager/env_manager/models/objects/primitives/sphere.py new file mode 100644 index 0000000..1fa2761 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/objects/primitives/sphere.py @@ -0,0 +1,176 @@ +import numpy as np +from gym_gz.scenario import model_wrapper +from gym_gz.utils.scenario import get_unique_model_name +from scenario import core as scenario_core +from scenario import gazebo as scenario_gazebo + + +class Sphere(model_wrapper.ModelWrapper): + """ + A Sphere model for Gazebo simulation. + + This class represents a spherical object that can be inserted into a Gazebo world. + The sphere can be customized by specifying its physical properties, such as radius, mass, + collision parameters, friction, and visual attributes. + + Attributes: + world (scenario_gazebo.World): The Gazebo world where the sphere model will be inserted. + name (str): The name of the sphere model. Defaults to "sphere". + position (tuple[float, float, float]): The position of the sphere in the world. Defaults to (0, 0, 0). + orientation (tuple[float, float, float, float]): The orientation of the sphere in quaternion format. Defaults to (1, 0, 0, 0). + radius (float): The radius of the sphere. Defaults to 0.025. + mass (float): The mass of the sphere. Defaults to 0.1. + static (bool): If True, the sphere will be static in the simulation. Defaults to False. + collision (bool): If True, the sphere will have collision properties. Defaults to True. + friction (float): The friction coefficient of the sphere's surface. Defaults to 1.0. + visual (bool): If True, the sphere will have a visual representation. Defaults to True. + gui_only (bool): If True, the visual will only appear in the GUI. Defaults to False. + color (tuple[float, float, float, float]): The RGBA color of the sphere. Defaults to (0.8, 0.8, 0.8, 1.0). + + Raises: + RuntimeError: If the sphere fails to be inserted into the Gazebo world. + """ + + def __init__( + self, + world: scenario_gazebo.World, + name: str = "sphere", + position: tuple[float, float, float] = (0, 0, 0), + orientation: tuple[float, float, float, float] = (1, 0, 0, 0), + radius: float = 0.025, + mass: float = 0.1, + static: bool = False, + collision: bool = True, + friction: float = 1.0, + visual: bool = True, + gui_only: bool = False, + color: tuple[float, float, float, float] | None = None, + **kwargs, + ): + # Get a unique model name + model_name = get_unique_model_name(world, name) + + # Initial pose + initial_pose = scenario_core.Pose(position, orientation) + + if not color: + color = tuple(np.random.uniform(0.0, 1.0, (3,))) + color = (color[0], color[1], color[2], 1.0) + + # Create SDF string for the model + sdf = self.get_sdf( + model_name=model_name, + radius=radius, + mass=mass, + static=static, + collision=collision, + friction=friction, + visual=visual, + gui_only=gui_only, + color=color, + ) + + # Insert the model + ok_model = world.to_gazebo().insert_model_from_string( + sdf, initial_pose, model_name + ) + if not ok_model: + raise RuntimeError(f"Failed to insert {model_name}") + + # Get the model + model = world.get_model(model_name) + + # Initialize base class + super().__init__(model=model) + + @classmethod + def get_sdf( + cls, + model_name: str, + radius: float, + mass: float, + static: bool, + collision: bool, + friction: float, + visual: bool, + gui_only: bool, + color: tuple[float, float, float, float], + ) -> str: + """ + Generates the SDF (Simulation Description Format) string for the sphere model. + + Args: + model_name (str): The name of the model. + radius (float): The radius of the sphere. + mass (float): The mass of the sphere. + static (bool): Whether the sphere is static in the simulation. + collision (bool): Whether the sphere should have collision properties. + friction (float): The friction coefficient for the sphere. + visual (bool): Whether the sphere should have a visual representation. + gui_only (bool): Whether the visual representation is only visible in the GUI. + color (tuple[float, float, float, float]): The RGBA color of the sphere. + + Returns: + str: The SDF string representing the sphere. + """ + # Inertia is identical for all axes + inertia_xx_yy_zz = (mass * radius**2) * 2 / 5 + + return f''' + + {"true" if static else "false"} + + { + f""" + + + + {radius} + + + + + + {friction} + {friction} + 0 0 0 + 0.0 + 0.0 + + + + + """ if collision else "" + } + { + f""" + + + + {radius} + + + + {color[0]} {color[1]} {color[2]} {color[3]} + {color[0]} {color[1]} {color[2]} {color[3]} + {color[0]} {color[1]} {color[2]} {color[3]} + + {1.0 - color[3]} + {'1 false' if gui_only else ''} + + """ if visual else "" + } + + {mass} + + {inertia_xx_yy_zz} + {inertia_xx_yy_zz} + {inertia_xx_yy_zz} + 0.0 + 0.0 + 0.0 + + + + + ''' diff --git a/env_manager/env_manager/env_manager/models/objects/random_object.py b/env_manager/env_manager/env_manager/models/objects/random_object.py new file mode 100644 index 0000000..5f399c6 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/objects/random_object.py @@ -0,0 +1,84 @@ +from gym_gz.scenario import model_wrapper +from gym_gz.utils.scenario import get_unique_model_name +from numpy.random import RandomState +from scenario import core as scenario_core +from scenario import gazebo as scenario_gazebo + +from env_manager.models.utils import ModelCollectionRandomizer + + +class RandomObject(model_wrapper.ModelWrapper): + """ + Represents a randomly selected 3D object model in the Gazebo simulation environment. + This class allows for the insertion of various models based on a collection of model paths, + utilizing a randomization strategy for the chosen model. + + Args: + world (scenario_gazebo.World): The Gazebo world where the random object model will be inserted. + name (str, optional): The name of the random object model. Defaults to "object". + position (tuple[float, float, float], optional): The position of the object in the world. Defaults to (0, 0, 0). + orientation (tuple[float, float, float, float], optional): The orientation of the object in quaternion format. Defaults to (1, 0, 0, 0). + model_paths (str | None, optional): Paths to the model files. Must be set; raises an error if None. + owner (str, optional): The owner of the model collection. Defaults to "GoogleResearch". + collection (str, optional): The collection of models to choose from. Defaults to "Google Scanned Objects". + server (str, optional): The server URL for the model collection. Defaults to "https://fuel.ignitionrobotics.org". + server_version (str, optional): The version of the server to use. Defaults to "1.0". + unique_cache (bool, optional): If True, enables caching of unique models. Defaults to False. + reset_collection (bool, optional): If True, resets the model collection for new selections. Defaults to False. + np_random (RandomState | None, optional): An instance of RandomState for random number generation. Defaults to None. + **kwargs: Additional keyword arguments. + + Raises: + RuntimeError: If the model path is not set or if the random object model fails to be inserted into the Gazebo world. + """ + + def __init__( + self, + world: scenario_gazebo.World, + name: str = "object", + position: tuple[float, float, float] = (0, 0, 0), + orientation: tuple[float, float, float, float] = (1, 0, 0, 0), + model_paths: str | None = None, + owner: str = "GoogleResearch", + collection: str = "Google Scanned Objects", + server: str = "https://fuel.ignitionrobotics.org", + server_version: str = "1.0", + unique_cache: bool = False, + reset_collection: bool = False, + np_random: RandomState | None = None, + **kwargs, + ): + # Get a unique model name + if model_paths is None: + raise RuntimeError("Set model path for continue") + model_name = get_unique_model_name(world, name) + + # Initial pose + initial_pose = scenario_core.Pose(position, orientation) + + model_collection_randomizer = ModelCollectionRandomizer( + model_paths=model_paths, + owner=owner, + collection=collection, + server=server, + server_version=server_version, + unique_cache=unique_cache, + reset_collection=reset_collection, + np_random=np_random, + ) + + # Note: using default arguments here + modified_sdf_file = model_collection_randomizer.random_model() + + # Insert the model + ok_model = world.to_gazebo().insert_model( + modified_sdf_file, initial_pose, model_name + ) + if not ok_model: + raise RuntimeError("Failed to insert " + model_name) + + # Get the model + model = world.get_model(model_name) + + # Initialize base class + model_wrapper.ModelWrapper.__init__(self, model=model) diff --git a/env_manager/env_manager/env_manager/models/objects/random_primitive.py b/env_manager/env_manager/env_manager/models/objects/random_primitive.py new file mode 100644 index 0000000..58510b1 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/objects/random_primitive.py @@ -0,0 +1,164 @@ +import numpy as np +from gym_gz.scenario import model_wrapper +from gym_gz.utils.scenario import get_unique_model_name +from numpy.random import RandomState +from scenario import core as scenario_core +from scenario import gazebo as scenario_gazebo + +from . import Box, Cylinder, Sphere + + +class RandomPrimitive(model_wrapper.ModelWrapper): + """ + Represents a randomly generated primitive shape (box, cylinder, or sphere) in the Gazebo simulation environment. + This class allows for the insertion of various primitive models based on the user's specifications or randomly chosen. + + Args: + world (scenario_gazebo.World): The Gazebo world where the primitive model will be inserted. + name (str, optional): The name of the primitive model. Defaults to "primitive". + use_specific_primitive ((str | None), optional): If specified, the exact type of primitive to create ('box', 'cylinder', or 'sphere'). Defaults to None, which will randomly select a primitive type. + position (tuple[float, float, float], optional): The position of the primitive in the world. Defaults to (0, 0, 0). + orientation (tuple[float, float, float, float], optional): The orientation of the primitive in quaternion format. Defaults to (1, 0, 0, 0). + static (bool, optional): If True, the primitive will be static and immovable. Defaults to False. + collision (bool, optional): If True, the primitive will have collision properties. Defaults to True. + visual (bool, optional): If True, the primitive will have a visual representation. Defaults to True. + gui_only (bool, optional): If True, the visual representation will only appear in the GUI and not in the simulation physics. Defaults to False. + np_random (RandomState | None, optional): An instance of RandomState for random number generation. If None, a default random generator will be used. Defaults to None. + **kwargs: Additional keyword arguments. + + Raises: + RuntimeError: If the primitive model fails to be inserted into the Gazebo world. + TypeError: If the specified primitive type is not supported. + """ + + def __init__( + self, + world: scenario_gazebo.World, + name: str = "primitive", + use_specific_primitive: (str | None) = None, + position: tuple[float, float, float] = (0, 0, 0), + orientation: tuple[float, float, float, float] = (1, 0, 0, 0), + static: bool = False, + collision: bool = True, + visual: bool = True, + gui_only: bool = False, + np_random: RandomState | None = None, + **kwargs, + ): + if np_random is None: + np_random = np.random.default_rng() + + # Get a unique model name + model_name = get_unique_model_name(world, name) + + # Initial pose + initial_pose = scenario_core.Pose(position, orientation) + + # Create SDF string for the model + sdf = self.get_sdf( + model_name=model_name, + use_specific_primitive=use_specific_primitive, + static=static, + collision=collision, + visual=visual, + gui_only=gui_only, + np_random=np_random, + ) + + # Insert the model + ok_model = world.to_gazebo().insert_model_from_string( + sdf, initial_pose, model_name + ) + if not ok_model: + raise RuntimeError("Failed to insert " + model_name) + + # Get the model + model = world.get_model(model_name) + + # Initialize base class + model_wrapper.ModelWrapper.__init__(self, model=model) + + @classmethod + def get_sdf( + cls, + model_name: str, + use_specific_primitive: (str | None), + static: bool, + collision: bool, + visual: bool, + gui_only: bool, + np_random: RandomState, + ) -> str: + """ + Generates the SDF (Simulation Description Format) string for the specified primitive model. + + This method can create the SDF representation for a box, cylinder, or sphere based on the provided parameters. + If a specific primitive type is not provided, one will be randomly selected. + + Args: + model_name (str): The name of the model being generated. + use_specific_primitive ((str | None)): The specific type of primitive to create ('box', 'cylinder', or 'sphere'). If None, a random primitive will be chosen. + static (bool): If True, the primitive will be static and immovable. + collision (bool): If True, the primitive will have collision properties. + visual (bool): If True, the primitive will have a visual representation. + gui_only (bool): If True, the visual representation will only appear in the GUI and will not affect physics. + np_random (RandomState): An instance of RandomState for random number generation. + + Returns: + str: The SDF string that defines the specified primitive model, including its physical and visual properties. + + Raises: + TypeError: If the specified primitive type is not supported. + + """ + if use_specific_primitive is not None: + primitive = use_specific_primitive + else: + primitive = np_random.choice(["box", "cylinder", "sphere"]) + + mass = np_random.uniform(0.05, 0.25) + friction = np_random.uniform(0.75, 1.5) + color = tuple(np_random.uniform(0.0, 1.0, (3,))) + color: tuple[float, float, float, float] = (color[0], color[1], color[2], 1.0) + + if "box" == primitive: + return Box.get_sdf( + model_name=model_name, + size=tuple(np_random.uniform(0.04, 0.06, (3,))), + mass=mass, + static=static, + collision=collision, + friction=friction, + visual=visual, + gui_only=gui_only, + color=color, + ) + elif "cylinder" == primitive: + return Cylinder.get_sdf( + model_name=model_name, + radius=np_random.uniform(0.01, 0.0375), + length=np_random.uniform(0.025, 0.05), + mass=mass, + static=static, + collision=collision, + friction=friction, + visual=visual, + gui_only=gui_only, + color=color, + ) + elif "sphere" == primitive: + return Sphere.get_sdf( + model_name=model_name, + radius=np_random.uniform(0.01, 0.0375), + mass=mass, + static=static, + collision=collision, + friction=friction, + visual=visual, + gui_only=gui_only, + color=color, + ) + else: + raise TypeError( + f"Type '{use_specific_primitive}' in not a supported primitive. Pleasure use 'box', 'cylinder' or 'sphere." + ) diff --git a/env_manager/env_manager/env_manager/models/robots/__init__.py b/env_manager/env_manager/env_manager/models/robots/__init__.py new file mode 100644 index 0000000..c690e8c --- /dev/null +++ b/env_manager/env_manager/env_manager/models/robots/__init__.py @@ -0,0 +1,16 @@ +from enum import Enum + +from .rbs_arm import RbsArm +from .robot import RobotWrapper + + +class RobotEnum(Enum): + RBS_ARM = "rbs_arm" + + +def get_robot_model_class(robot_model: str) -> type[RobotWrapper]: + model_mapping = { + RobotEnum.RBS_ARM.value: RbsArm, + } + + return model_mapping.get(robot_model, RbsArm) diff --git a/env_manager/env_manager/env_manager/models/robots/rbs_arm.py b/env_manager/env_manager/env_manager/models/robots/rbs_arm.py new file mode 100644 index 0000000..0fb8294 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/robots/rbs_arm.py @@ -0,0 +1,156 @@ +from gym_gz.utils.scenario import get_unique_model_name +from rclpy.node import Node +from robot_builder.parser.urdf import URDF_parser +from robot_builder.elements.robot import Robot + +from scenario import core as scenario_core +from scenario import gazebo as scenario_gazebo + +from .robot import RobotWrapper + + +class RbsArm(RobotWrapper): + """ + A class representing a robotic arm built using the `robot_builder` library. + + This class is responsible for creating a robotic arm model within a Gazebo simulation environment. + It allows for the manipulation of joint positions for both the arm and the gripper. + + Attributes: + - DEFAULT_ARM_JOINT_POSITIONS (list[float]): The default joint positions for the arm. + - OPEN_GRIPPER_JOINT_POSITIONS (list[float]): The joint positions for the gripper in the open state. + - CLOSED_GRIPPER_JOINT_POSITIONS (list[float]): The joint positions for the gripper in the closed state. + - DEFAULT_GRIPPER_JOINT_POSITIONS (list[float]): The default joint positions for the gripper. + + Args: + - world (scenario_gazebo.World): The Gazebo world where the robot model will be inserted. + - node (Node): The ROS2 node associated with the robotic arm. + - urdf_string (str): The URDF string defining the robot. + - name (str, optional): The name of the robotic arm. Defaults to "rbs_arm". + - position (tuple[float, float, float], optional): The initial position of the robot in the world. Defaults to (0.0, 0.0, 0.0). + - orientation (tuple[float, float, float, float], optional): The initial orientation of the robot in quaternion format. Defaults to (1.0, 0, 0, 0). + - initial_arm_joint_positions (list[float] | float, optional): The initial joint positions for the arm. Defaults to `DEFAULT_ARM_JOINT_POSITIONS`. + - initial_gripper_joint_positions (list[float] | float, optional): The initial joint positions for the gripper. Defaults to `DEFAULT_GRIPPER_JOINT_POSITIONS`. + + Raises: + - RuntimeError: If the robot model fails to be inserted into the Gazebo world. + """ + + DEFAULT_ARM_JOINT_POSITIONS: list[float] = [ + 0.0, + 0.5, + 3.14159, + 1.5, + 0.0, + 1.4, + 0.0, + ] + + OPEN_GRIPPER_JOINT_POSITIONS: list[float] = [ + 0.064, + ] + + CLOSED_GRIPPER_JOINT_POSITIONS: list[float] = [ + 0.0, + ] + + DEFAULT_GRIPPER_JOINT_POSITIONS: list[float] = CLOSED_GRIPPER_JOINT_POSITIONS + + def __init__( + self, + world: scenario_gazebo.World, + node: Node, + urdf_string: str, + name: str = "rbs_arm", + position: tuple[float, float, float] = (0.0, 0.0, 0.0), + orientation: tuple[float, float, float, float] = (1.0, 0, 0, 0), + initial_arm_joint_positions: list[float] | float = DEFAULT_ARM_JOINT_POSITIONS, + initial_gripper_joint_positions: list[float] + | float = DEFAULT_GRIPPER_JOINT_POSITIONS, + ): + # Get a unique model name + model_name = get_unique_model_name(world, name) + + # Setup initial pose + initial_pose = scenario_core.Pose(position, orientation) + + # Insert the model + ok_model = world.insert_model_from_string(urdf_string, initial_pose, model_name) + if not ok_model: + raise RuntimeError("Failed to insert " + model_name) + + # Get the model + model = world.get_model(model_name) + + # Parse robot to get metadata + self._robot: Robot = URDF_parser.load_string(urdf_string) + + self.__initial_gripper_joint_positions = ( + [float(initial_gripper_joint_positions)] + * len(self._robot.gripper_actuated_joint_names) + if isinstance(initial_gripper_joint_positions, (int, float)) + else initial_gripper_joint_positions + ) + + self.__initial_arm_joint_positions = ( + [float(initial_arm_joint_positions)] * len(self._robot.actuated_joint_names) + if isinstance(initial_arm_joint_positions, (int, float)) + else initial_arm_joint_positions + ) + + # Set initial joint configuration + self.set_initial_joint_positions(model) + super().__init__(model=model) + + @property + def robot(self) -> Robot: + """Returns the robot metadata parsed from the URDF string. + + Returns: + Robot: The robot instance containing metadata. + """ + return self._robot + + @property + def initial_arm_joint_positions(self) -> list[float]: + """Returns the initial joint positions for the arm. + + Returns: + list[float]: The initial joint positions for the arm. + """ + return self.__initial_arm_joint_positions + + @property + def initial_gripper_joint_positions(self) -> list[float]: + """Returns the initial joint positions for the gripper. + + Returns: + list[float]: The initial joint positions for the gripper. + """ + return self.__initial_gripper_joint_positions + + def set_initial_joint_positions(self, model): + """Sets the initial positions for the robot's joints. + + This method resets the joint positions of both the arm and gripper to their specified initial values. + + Args: + model: The model representation of the robot within the Gazebo environment. + + Raises: + RuntimeError: If resetting the joint positions fails for any of the joints. + """ + model = model.to_gazebo() + + joint_position_data = [ + (self.__initial_arm_joint_positions, self._robot.actuated_joint_names), + ] + if self._robot.gripper_actuated_joint_names: + joint_position_data.append( + (self.__initial_gripper_joint_positions, self._robot.gripper_actuated_joint_names) + ) + + for positions, joint_names in joint_position_data: + print(f"Setting joint positions for {joint_names}: {positions}") + if not model.reset_joint_positions(positions, joint_names): + raise RuntimeError(f"Failed to set initial positions of {joint_names}'s joints") diff --git a/env_manager/env_manager/env_manager/models/robots/robot.py b/env_manager/env_manager/env_manager/models/robots/robot.py new file mode 100644 index 0000000..fdfa062 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/robots/robot.py @@ -0,0 +1,95 @@ +from gym_gz.scenario import model_wrapper +from robot_builder.elements.robot import Robot +from scenario import gazebo as scenario_gazebo +from abc import abstractmethod + + +class RobotWrapper(model_wrapper.ModelWrapper): + """ + An abstract base class for robot models in a Gazebo simulation. + + This class extends the ModelWrapper from gym_gz and provides a structure for creating + robot models with specific configurations, including joint positions for arms and grippers. + + Args: + world (scenario_gazebo.World, optional): The Gazebo world where the robot model will be inserted. + urdf_string (str, optional): The URDF (Unified Robot Description Format) string defining the robot. + name (str, optional): The name of the robot model. Defaults to None. + position (tuple[float, float, float], optional): The initial position of the robot in the world. Defaults to None. + orientation (tuple[float, float, float, float], optional): The initial orientation of the robot in quaternion format. Defaults to None. + initial_arm_joint_positions (list[float] | float, optional): The initial joint positions for the arm. Defaults to an empty list. + initial_gripper_joint_positions (list[float] | float, optional): The initial joint positions for the gripper. Defaults to an empty list. + model (model_wrapper.ModelWrapper, optional): An existing model instance to initialize the wrapper. Must be provided. + **kwargs: Additional keyword arguments. + + Raises: + ValueError: If the model parameter is not provided. + """ + def __init__( + self, + world: scenario_gazebo.World | None = None, + urdf_string: str | None = None, + name: str | None = None, + position: tuple[float, float, float] | None = None, + orientation: tuple[float, float, float, float] | None = None, + initial_arm_joint_positions: list[float] | float = [], + initial_gripper_joint_positions: list[float] | float = [], + model: model_wrapper.ModelWrapper | None = None, + **kwargs, + ): + if model is not None: + super().__init__(model=model) + else: + raise ValueError("Model should be defined for the parent class") + + @property + @abstractmethod + def robot(self) -> Robot: + """Returns the robot instance containing metadata. + + This property must be implemented by subclasses to return the specific robot metadata. + + Returns: + Robot: The robot instance. + """ + pass + + + @property + @abstractmethod + def initial_gripper_joint_positions(self) -> list[float]: + """Returns the initial joint positions for the gripper. + + This property must be implemented by subclasses to provide the initial positions of the gripper joints. + + Returns: + list[float]: The initial joint positions for the gripper. + """ + pass + + @property + @abstractmethod + def initial_arm_joint_positions(self) -> list[float]: + """Returns the initial joint positions for the arm. + + This property must be implemented by subclasses to provide the initial positions of the arm joints. + + Returns: + list[float]: The initial joint positions for the arm. + """ + pass + + @abstractmethod + def set_initial_joint_positions(self, model): + """Sets the initial positions for the robot's joints. + + This method must be implemented by subclasses to reset the joint positions of the robot + to their specified initial values. + + Args: + model: The model representation of the robot within the Gazebo environment. + + Raises: + RuntimeError: If resetting the joint positions fails. + """ + pass diff --git a/env_manager/env_manager/env_manager/models/sensors/__init__.py b/env_manager/env_manager/env_manager/models/sensors/__init__.py new file mode 100644 index 0000000..0cbbbe7 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/sensors/__init__.py @@ -0,0 +1 @@ +from .camera import Camera diff --git a/env_manager/env_manager/env_manager/models/sensors/camera.py b/env_manager/env_manager/env_manager/models/sensors/camera.py new file mode 100644 index 0000000..63e1616 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/sensors/camera.py @@ -0,0 +1,436 @@ +import os +from threading import Thread + +from gym_gz.scenario import model_wrapper +from gym_gz.utils.scenario import get_unique_model_name +from scenario import core as scenario_core +from scenario import gazebo as scenario_gazebo + +# from env_manager.models.utils import ModelCollectionRandomizer + + +class Camera(model_wrapper.ModelWrapper): + """ + Represents a camera model in a Gazebo simulation. + + This class extends the ModelWrapper from gym_gz to define a camera model that can be inserted + into the Gazebo world. It supports different types of cameras and can bridge ROS2 topics for + camera data. + + Args: + world (scenario_gazebo.World): The Gazebo world where the camera will be inserted. + name (str, optional): The name of the camera model. If None, a unique name is generated. + position (tuple[float, float, float], optional): The initial position of the camera. Defaults to (0, 0, 0). + orientation (tuple[float, float, float, float], optional): The initial orientation of the camera in quaternion. Defaults to (1, 0, 0, 0). + static (bool, optional): If True, the camera is a static model. Defaults to True. + camera_type (str, optional): The type of camera to create. Defaults to "rgbd_camera". + width (int, optional): The width of the camera image. Defaults to 212. + height (int, optional): The height of the camera image. Defaults to 120. + image_format (str, optional): The format of the camera image. Defaults to "R8G8B8". + update_rate (int, optional): The update rate for the camera sensor. Defaults to 15. + horizontal_fov (float, optional): The horizontal field of view for the camera. Defaults to 1.567821. + vertical_fov (float, optional): The vertical field of view for the camera. Defaults to 1.022238. + clip_color (tuple[float, float], optional): The near and far clipping distances for color. Defaults to (0.02, 1000.0). + clip_depth (tuple[float, float], optional): The near and far clipping distances for depth. Defaults to (0.02, 10.0). + noise_mean (float, optional): The mean of the noise added to the camera images. Defaults to None. + noise_stddev (float, optional): The standard deviation of the noise added to the camera images. Defaults to None. + ros2_bridge_color (bool, optional): If True, a ROS2 bridge for color images is created. Defaults to False. + ros2_bridge_depth (bool, optional): If True, a ROS2 bridge for depth images is created. Defaults to False. + ros2_bridge_points (bool, optional): If True, a ROS2 bridge for point cloud data is created. Defaults to False. + visibility_mask (int, optional): The visibility mask for the camera sensor. Defaults to 0. + visual (str, optional): The type of visual representation for the camera. Defaults to None. + + Raises: + ValueError: If the visual mesh or textures cannot be found. + RuntimeError: If the camera model fails to insert into the Gazebo world. + """ + def __init__( + self, + world: scenario_gazebo.World, + name: str | None = None, + position: tuple[float, float, float] = (0, 0, 0), + orientation: tuple[float, float, float, float] = (1, 0, 0, 0), + static: bool = True, + camera_type: str = "rgbd_camera", + width: int = 212, + height: int = 120, + image_format: str = "R8G8B8", + update_rate: int = 15, + horizontal_fov: float = 1.567821, + vertical_fov: float = 1.022238, + clip_color: tuple[float, float] = (0.02, 1000.0), + clip_depth: tuple[float, float] = (0.02, 10.0), + noise_mean: float | None = None, + noise_stddev: float | None = None, + ros2_bridge_color: bool = False, + ros2_bridge_depth: bool = False, + ros2_bridge_points: bool = False, + visibility_mask: int = 0, + visual: str | None = None, + ): + # Get a unique model name + if name is not None: + model_name = get_unique_model_name(world, name) + else: + model_name = get_unique_model_name(world, camera_type) + self._model_name = model_name + self._camera_type = camera_type + + # Initial pose + initial_pose = scenario_core.Pose(position, orientation) + + use_mesh: bool = False + mesh_path_visual: str = "" + + albedo_map = None + normal_map = None + roughness_map = None + metalness_map = None + # Get resources for visual (if enabled) + # if visual: + # if "intel_realsense_d435" == visual: + # use_mesh = True + # + # # Get path to the model and the important directories + # model_path = ModelCollectionRandomizer.get_collection_paths( + # owner="OpenRobotics", + # collection="", + # model_name="Intel RealSense D435", + # )[0] + # + # mesh_dir = os.path.join(model_path, "meshes") + # texture_dir = os.path.join(model_path, "materials", "textures") + # + # # Get path to the mesh + # mesh_path_visual = os.path.join(mesh_dir, "realsense.dae") + # # Make sure that it exists + # if not os.path.exists(mesh_path_visual): + # raise ValueError( + # f"Visual mesh '{mesh_path_visual}' for Camera model is not a valid file." + # ) + # + # # Find PBR textures + # if texture_dir: + # # List all files + # texture_files = os.listdir(texture_dir) + # + # # Extract the appropriate files + # for texture in texture_files: + # texture_lower = texture.lower() + # if "basecolor" in texture_lower or "albedo" in texture_lower: + # albedo_map = os.path.join(texture_dir, texture) + # elif "normal" in texture_lower: + # normal_map = os.path.join(texture_dir, texture) + # elif "roughness" in texture_lower: + # roughness_map = os.path.join(texture_dir, texture) + # elif ( + # "specular" in texture_lower or "metalness" in texture_lower + # ): + # metalness_map = os.path.join(texture_dir, texture) + # + # if not (albedo_map and normal_map and roughness_map and metalness_map): + # raise ValueError("Not all textures for Camera model were found.") + + # Create SDF string for the model + sdf = f''' + + {static} + + + {model_name} + true + {update_rate} + + + {width} + {height} + {image_format} + + {horizontal_fov} + {vertical_fov} + + {clip_color[0]} + {clip_color[1]} + + { + f""" + + {clip_depth[0]} + {clip_depth[1]} + + """ if "rgbd" in model_name else "" + } + { + f""" + gaussian + {noise_mean} + {noise_stddev} + """ if noise_mean is not None and noise_stddev is not None else "" + } + {visibility_mask} + + true + + { + f""" + + -0.01 0 0 0 1.5707963 0 + + + 0.02 + 0.02 + + + + 0.0 0.8 0.0 + 0.0 0.8 0.0 + 0.0 0.8 0.0 + + + + -0.05 0 0 0 0 0 + + + 0.06 0.05 0.05 + + + + 0.0 0.8 0.0 + 0.0 0.8 0.0 + 0.0 0.8 0.0 + + + """ if visual and not use_mesh else "" + } + { + f""" + + 0.0615752 + + 9.108e-05 + 0.0 + 0.0 + 2.51e-06 + 0.0 + 8.931e-05 + + + + 0 0 0 0 0 1.5707963 + + + {mesh_path_visual} + + RealSense +
false
+ + + + + 1 1 1 1 + 1 1 1 1 + + + {albedo_map} + {normal_map} + {roughness_map} + {metalness_map} + + + + + """ if visual and use_mesh else "" + } + + + ''' + + # Insert the model + ok_model = world.to_gazebo().insert_model_from_string( + sdf, initial_pose, model_name + ) + if not ok_model: + raise RuntimeError("Failed to insert " + model_name) + + # Get the model + model = world.get_model(model_name) + + # Initialize base class + model_wrapper.ModelWrapper.__init__(self, model=model) + + if ros2_bridge_color or ros2_bridge_depth or ros2_bridge_points: + self.__threads = [] + self.__threads.append( + Thread( + target=self.construct_ros2_bridge, + args=( + self.info_topic, + "sensor_msgs/msg/CameraInfo", + "gz.msgs.CameraInfo", + ), + daemon=True, + ) + ) + if ros2_bridge_color: + self.__threads.append( + Thread( + target=self.construct_ros2_bridge, + args=( + self.color_topic, + "sensor_msgs/msg/Image", + "gz.msgs.Image", + ), + daemon=True, + ) + ) + + if ros2_bridge_depth: + self.__threads.append( + Thread( + target=self.construct_ros2_bridge, + args=( + self.depth_topic, + "sensor_msgs/msg/Image", + "gz.msgs.Image", + ), + daemon=True, + ) + ) + + if ros2_bridge_points: + self.__threads.append( + Thread( + target=self.construct_ros2_bridge, + args=( + self.points_topic, + "sensor_msgs/msg/PointCloud2", + "gz.msgs.PointCloudPacked", + ), + daemon=True, + ) + ) + + for thread in self.__threads: + thread.start() + + def __del__(self): + """Cleans up threads when the Camera object is deleted.""" + if hasattr(self, "__threads"): + for thread in self.__threads: + thread.join() + + @classmethod + def construct_ros2_bridge(cls, topic: str, ros_msg: str, ign_msg: str): + """ + Constructs and runs a ROS2 bridge command for a given topic. + + Args: + topic (str): The topic to bridge. + ros_msg (str): The ROS2 message type to use. + ign_msg (str): The Ignition message type to use. + """ + node_name = "parameter_bridge" + topic.replace("/", "_") + command = ( + f"ros2 run ros_gz_bridge parameter_bridge {topic}@{ros_msg}[{ign_msg} " + + f"--ros-args --remap __node:={node_name} --ros-args -p use_sim_time:=true" + ) + os.system(command) + + @classmethod + def get_frame_id(cls, model_name: str) -> str: + """ + Gets the frame ID for the camera model. + + Args: + model_name (str): The name of the camera model. + + Returns: + str: The frame ID. + """ + return f"{model_name}/{model_name}_link/camera" + + @property + def frame_id(self) -> str: + """Returns the frame ID of the camera.""" + return self.get_frame_id(self._model_name) + + @classmethod + def get_color_topic(cls, model_name: str, camera_type: str) -> str: + """ + Gets the color topic for the camera. + + Args: + model_name (str): The name of the camera model. + camera_type (str): The type of the camera. + + Returns: + str: The color topic. + """ + return f"/{model_name}/image" if "rgbd" in camera_type else f"/{model_name}" + + @property + def color_topic(self) -> str: + """Returns the color topic for the camera.""" + return self.get_color_topic(self._model_name, self._camera_type) + + @classmethod + def get_depth_topic(cls, model_name: str, camera_type: str) -> str: + """ + Gets the depth topic for the camera. + + Args: + model_name (str): The name of the camera model. + camera_type (str): The type of the camera. + + Returns: + str: The depth topic. + """ + return ( + f"/{model_name}/depth_image" if "rgbd" in camera_type else f"/{model_name}" + ) + + @property + def depth_topic(self) -> str: + """Returns the depth topic for the camera.""" + return self.get_depth_topic(self._model_name, self._camera_type) + + @classmethod + def get_points_topic(cls, model_name: str) -> str: + """ + Gets the points topic for the camera. + + Args: + model_name (str): The name of the camera model. + + Returns: + str: /{model_name}/points. + """ + return f"/{model_name}/points" + + @property + def points_topic(self) -> str: + """Returns the points topic for the camera.""" + return self.get_points_topic(self._model_name) + + @property + def info_topic(self): + """Returns the camera info topic.""" + return f"/{self._model_name}/camera_info" + + @classmethod + def get_link_name(cls, model_name: str) -> str: + """ + Gets the link name for the camera model. + + Args: + model_name (str): The name of the camera model. + + Returns: + str: {model_name}_link. + """ + return f"{model_name}_link" + + @property + def link_name(self) -> str: + """Returns the link name for the camera.""" + return self.get_link_name(self._model_name) diff --git a/env_manager/env_manager/env_manager/models/terrains/__init__.py b/env_manager/env_manager/env_manager/models/terrains/__init__.py new file mode 100644 index 0000000..9829bf3 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/terrains/__init__.py @@ -0,0 +1,25 @@ +# from gym_gz.scenario.model_wrapper import ModelWrapper + +from .ground import Ground + + +# def get_terrain_model_class(terrain_type: str) -> type[ModelWrapper]: +# # TODO: Refactor into enum +# +# if "flat" == terrain_type: +# return Ground +# elif "random_flat" == terrain_type: +# return RandomGround +# elif "lunar_heightmap" == terrain_type: +# return LunarHeightmap +# elif "lunar_surface" == terrain_type: +# return LunarSurface +# elif "random_lunar_surface" == terrain_type: +# return RandomLunarSurface +# else: +# raise AttributeError(f"Unsupported terrain [{terrain_type}]") +# +# +# def is_terrain_type_randomizable(terrain_type: str) -> bool: +# +# return "random_flat" == terrain_type or "random_lunar_surface" == terrain_type diff --git a/env_manager/env_manager/env_manager/models/terrains/ground.py b/env_manager/env_manager/env_manager/models/terrains/ground.py new file mode 100644 index 0000000..09044a3 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/terrains/ground.py @@ -0,0 +1,104 @@ +from gym_gz.scenario import model_wrapper +from gym_gz.utils.scenario import get_unique_model_name +from scenario import core as scenario_core +from scenario import gazebo as scenario_gazebo + + +class Ground(model_wrapper.ModelWrapper): + """ + Represents a ground model in a Gazebo simulation. + + This class extends the ModelWrapper from gym_gz to define a ground model that can be + inserted into the Gazebo world. The ground is defined by its size, position, orientation, + and friction properties. + + Args: + world (scenario_gazebo.World): The Gazebo world where the ground will be inserted. + name (str, optional): The name of the ground model. Defaults to "ground". + position (tuple[float, float, float], optional): The initial position of the ground. Defaults to (0, 0, 0). + orientation (tuple[float, float, float, float], optional): The initial orientation of the ground in quaternion. Defaults to (1, 0, 0, 0). + size (tuple[float, float], optional): The size of the ground plane. Defaults to (1.5, 1.5). + collision_thickness (float, optional): The thickness of the collision surface. Defaults to 0.05. + friction (float, optional): The friction coefficient for the ground surface. Defaults to 5.0. + ambient (tuple[float, float, float, float], optional): The ambient color of the material. Defaults to (0.8, 0.8, 0.8, 1.0). + specular (tuple[float, float, float, float], optional): The specular color of the material. Defaults to (0.8, 0.8, 0.8, 1.0). + diffuse (tuple[float, float, float, float], optional): The diffuse color of the material. Defaults to (0.8, 0.8, 0.8, 1.0). + **kwargs: Additional keyword arguments for future extensions. + + Raises: + RuntimeError: If the ground model fails to insert into the Gazebo world. + """ + + def __init__( + self, + world: scenario_gazebo.World, + name: str = "ground", + position: tuple[float, float, float] = (0, 0, 0), + orientation: tuple[float, float, float, float] = (1, 0, 0, 0), + size: tuple[float, float] = (1.5, 1.5), + collision_thickness=0.05, + friction: float = 5.0, + ambient: tuple[float, float, float, float] = (0.8, 0.8, 0.8, 1.0), + specular: tuple[float, float, float, float] = (0.8, 0.8, 0.8, 1.0), + diffuse: tuple[float, float, float, float] = (0.8, 0.8, 0.8, 1.0), + **kwargs, + ): + # Get a unique model name + model_name = get_unique_model_name(world, name) + + # Initial pose + initial_pose = scenario_core.Pose(position, orientation) + + # Create SDF string for the model with the provided material properties + sdf = f""" + + true + + + + + 0 0 1 + {size[0]} {size[1]} + + + + + + {friction} + {friction} + 0 0 0 + 0.0 + 0.0 + + + + + + + + 0 0 1 + {size[0]} {size[1]} + + + + {' '.join(map(str, ambient))} + {' '.join(map(str, diffuse))} + {' '.join(map(str, specular))} + + + + + """ + + # Insert the model + ok_model = world.to_gazebo().insert_model_from_string( + sdf, initial_pose, model_name + ) + if not ok_model: + raise RuntimeError("Failed to insert " + model_name) + + # Get the model + model = world.get_model(model_name) + + # Initialize base class + model_wrapper.ModelWrapper.__init__(self, model=model) diff --git a/env_manager/env_manager/env_manager/models/terrains/random_ground.py b/env_manager/env_manager/env_manager/models/terrains/random_ground.py new file mode 100644 index 0000000..948b376 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/terrains/random_ground.py @@ -0,0 +1,137 @@ +import os +import numpy as np + +from gym_gz.scenario import model_wrapper +from gym_gz.utils.scenario import get_unique_model_name +from scenario import core as scenario_core +from scenario import gazebo as scenario_gazebo + +from rbs_assets_library import get_textures_path + + +class RandomGround(model_wrapper.ModelWrapper): + def __init__( + self, + world: scenario_gazebo.World, + name: str = "random_ground", + position: tuple[float, float, float] = (0, 0, 0), + orientation: tuple[float, float, float, float] = (1, 0, 0, 0), + size: tuple[float, float] = (1.0, 1.0), + friction: float = 5.0, + texture_dir: str | None = None, + **kwargs, + ): + + np_random = np.random.default_rng() + + # Get a unique model name + model_name = get_unique_model_name(world, name) + + # Initial pose + initial_pose = scenario_core.Pose(position, orientation) + + # Get textures from ENV variable if not directly specified + if not texture_dir: + texture_dir = os.environ.get("TEXTURE_DIRS", default="") + if not texture_dir: + texture_dir = get_textures_path() + + # Find random PBR texture + albedo_map = None + normal_map = None + roughness_map = None + metalness_map = None + if texture_dir: + if ":" in texture_dir: + textures = [] + for d in texture_dir.split(":"): + textures.extend([os.path.join(d, f) for f in os.listdir(d)]) + else: + # Get list of the available textures + textures = os.listdir(texture_dir) + + # Choose a random texture from these + random_texture_dir = str(np_random.choice(textures)) + + random_texture_dir = texture_dir + random_texture_dir + + # List all files + texture_files = os.listdir(random_texture_dir) + + # Extract the appropriate files + for texture in texture_files: + texture_lower = texture.lower() + if "color" in texture_lower or "albedo" in texture_lower: + albedo_map = os.path.join(random_texture_dir, texture) + elif "normal" in texture_lower: + normal_map = os.path.join(random_texture_dir, texture) + elif "roughness" in texture_lower: + roughness_map = os.path.join(random_texture_dir, texture) + elif "specular" in texture_lower or "metalness" in texture_lower: + metalness_map = os.path.join(random_texture_dir, texture) + + # Create SDF string for the model + sdf = f""" + + true + + + + + 0 0 1 + {size[0]} {size[1]} + + + + + + {friction} + {friction} + 0 0 0 + 0.0 + 0.0 + + + + + + + + 0 0 1 + {size[0]} {size[1]} + + + + 1 1 1 1 + 1 1 1 1 + 1 1 1 1 + + + {"%s" + % albedo_map if albedo_map is not None else ""} + {"%s" + % normal_map if normal_map is not None else ""} + {"%s" + % roughness_map if roughness_map is not None else ""} + {"%s" + % metalness_map if metalness_map is not None else ""} + + + + + + + """ + + # Insert the model + ok_model = world.to_gazebo().insert_model_from_string( + sdf, initial_pose, model_name + ) + if not ok_model: + raise RuntimeError("Failed to insert " + model_name) + + # Get the model + model = world.get_model(model_name) + + # Initialize base class + model_wrapper.ModelWrapper.__init__(self, model=model) diff --git a/env_manager/env_manager/env_manager/models/utils/__init__.py b/env_manager/env_manager/env_manager/models/utils/__init__.py new file mode 100644 index 0000000..1c438a3 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/utils/__init__.py @@ -0,0 +1,2 @@ +# from .model_collection_randomizer import ModelCollectionRandomizer +from .xacro2sdf import xacro2sdf diff --git a/env_manager/env_manager/env_manager/models/utils/model_collection_randomizer.py b/env_manager/env_manager/env_manager/models/utils/model_collection_randomizer.py new file mode 100644 index 0000000..428a7a5 --- /dev/null +++ b/env_manager/env_manager/env_manager/models/utils/model_collection_randomizer.py @@ -0,0 +1,1266 @@ +import glob +import os + +import numpy as np +import trimesh +from gym_gz.utils import logger +from numpy.random import RandomState +from pcg_gazebo.parsers import parse_sdf +from pcg_gazebo.parsers.sdf import create_sdf_element +from scenario import gazebo as scenario_gazebo + +# Note: only models with mesh geometry are supported + + +class ModelCollectionRandomizer: + """ + A class to randomize and manage paths for model collections in simulation environments. + + This class allows for the selection and management of model paths, enabling features + like caching, blacklisting, and random sampling from a specified collection. + + Attributes: + _class_model_paths (list[str] | None): Class-level cache for model paths. + __sdf_base_name (str): The base name for the SDF model file. + __configured_sdf_base_name (str): The base name for the modified SDF model file. + __blacklisted_base_name (str): The base name used for blacklisted models. + __collision_mesh_dir (str): Directory where collision meshes are stored. + __collision_mesh_file_type (str): The file type of the collision meshes. + __original_scale_base_name (str): The base name for original scale metadata files. + _unique_cache (bool): Whether to use a unique cache for model paths. + _enable_blacklisting (bool): Whether to enable blacklisting of unusable models. + _model_paths (list[str] | None): Instance-specific model paths if unique cache is enabled. + np_random (RandomState): Numpy random state for random sampling. + """ + + _class_model_paths = None + __sdf_base_name = "model.sdf" + __configured_sdf_base_name = "model_modified.sdf" + __blacklisted_base_name = "BLACKLISTED" + __collision_mesh_dir = "meshes/collision/" + __collision_mesh_file_type = "stl" + __original_scale_base_name = "original_scale.txt" + + def __init__( + self, + model_paths=None, + owner="GoogleResearch", + collection="Google Scanned Objects", + server="https://fuel.ignitionrobotics.org", + server_version="1.0", + unique_cache=False, + reset_collection=False, + enable_blacklisting=True, + np_random: RandomState | None = None, + ): + """ + Initializes the ModelCollectionRandomizer. + + Args: + model_paths (list[str] | None): List of model paths to initialize with. + owner (str): The owner of the model collection (default is "GoogleResearch"). + collection (str): The name of the model collection (default is "Google Scanned Objects"). + server (str): The server URL for the model collection (default is "https://fuel.ignitionrobotics.org"). + server_version (str): The server version to use (default is "1.0"). + unique_cache (bool): Whether to use a unique cache for the instance (default is False). + reset_collection (bool): Whether to reset the class-level model paths (default is False). + enable_blacklisting (bool): Whether to enable blacklisting of models (default is True). + np_random (RandomState | None): Numpy random state for random operations (default is None). + + Raises: + ValueError: If an invalid model path is provided. + """ + + # If enabled, the newly created objects of this class will use its own individual cache + # for model paths and must discover/download them on its own + self._unique_cache = unique_cache + + # Flag that determines if models that cannot be used are blacklisted + self._enable_blacklisting = enable_blacklisting + + # If enabled, the cache of the class used to store model paths among instances will be reset + if reset_collection and not self._unique_cache: + self._class_model_paths = None + + # Get file path to all models from + # a) `model_paths` arg + # b) local cache owner (if `owner` has some models, i.e `collection` is already downloaded) + # c) Fuel collection (if `owner` has no models in local cache) + if model_paths is not None: + # Use arg + if self._unique_cache: + self._model_paths = model_paths + else: + self._class_model_paths = model_paths + else: + # Use local cache or Fuel + if self._unique_cache: + self._model_paths = self.get_collection_paths( + owner=owner, + collection=collection, + server=server, + server_version=server_version, + ) + elif self._class_model_paths is None: + # Executed only once, unless the paths are reset with `reset_collection` arg + self._class_model_paths = self.get_collection_paths( + owner=owner, + collection=collection, + server=server, + server_version=server_version, + ) + + # Initialise rng with (with seed is desired) + if np_random is not None: + self.np_random = np_random + else: + self.np_random = np.random.default_rng() + + @classmethod + def get_collection_paths( + cls, + owner="GoogleResearch", + collection="Google Scanned Objects", + server="https://fuel.ignitionrobotics.org", + server_version="1.0", + model_name: str = "", + ) -> list[str]: + """ + Retrieves model paths from the local cache or downloads them from a specified server. + + The method first checks the local cache for models belonging to the specified owner. + If no models are found, it attempts to download the models from the specified Fuel server. + + Args: + cls: The class reference. + owner (str): The owner of the model collection (default is "GoogleResearch"). + collection (str): The name of the model collection (default is "Google Scanned Objects"). + server (str): The server URL for the model collection (default is "https://fuel.ignitionrobotics.org"). + server_version (str): The server version to use (default is "1.0"). + model_name (str): The name of the specific model to fetch (default is an empty string). + + Returns: + list[str]: A list of paths to the retrieved models. + + Raises: + RuntimeError: If the download command fails or if no models are found after the download. + """ + + # First check the local cache (for performance) + # Note: This unfortunately does not check if models belong to the specified collection + # TODO: Make sure models belong to the collection if sampled from local cache + model_paths = scenario_gazebo.get_local_cache_model_paths( + owner=owner, name=model_name + ) + if len(model_paths) > 0: + return model_paths + + # Else download the models from Fuel and then try again + if collection: + download_uri = "%s/%s/%s/collections/%s" % ( + server, + server_version, + owner, + collection, + ) + elif model_name: + download_uri = "%s/%s/%s/models/%s" % ( + server, + server_version, + owner, + model_name, + ) + download_command = 'ign fuel download -v 3 -t model -j %s -u "%s"' % ( + os.cpu_count(), + download_uri, + ) + os.system(download_command) + + model_paths = scenario_gazebo.get_local_cache_model_paths( + owner=owner, name=model_name + ) + if 0 == len(model_paths): + logger.error( + 'URI "%s" is not valid and does not contain any models that are \ + owned by the owner of the collection' + % download_uri + ) + pass + + return model_paths + + def random_model( + self, + min_scale=0.125, + max_scale=0.175, + min_mass=0.05, + max_mass=0.25, + min_friction=0.75, + max_friction=1.5, + decimation_fraction_of_visual=0.25, + decimation_min_faces=40, + decimation_max_faces=200, + max_faces=40000, + max_vertices=None, + component_min_faces_fraction=0.1, + component_max_volume_fraction=0.35, + fix_mtl_texture_paths=True, + skip_blacklisted=True, + return_sdf_path=True, + ) -> str: + """ + Selects and configures a random model from the collection. + + The method attempts to find a valid model, applying randomization + and returning the path to the configured SDF file or the model directory. + + Args: + min_scale (float): Minimum scale for the model. + max_scale (float): Maximum scale for the model. + min_mass (float): Minimum mass for the model. + max_mass (float): Maximum mass for the model. + min_friction (float): Minimum friction coefficient. + max_friction (float): Maximum friction coefficient. + decimation_fraction_of_visual (float): Fraction of visual decimation. + decimation_min_faces (int): Minimum number of faces for decimation. + decimation_max_faces (int): Maximum number of faces for decimation. + max_faces (int): Maximum faces for the model. + max_vertices (int, optional): Maximum vertices for the model. + component_min_faces_fraction (float): Minimum face fraction for components. + component_max_volume_fraction (float): Maximum volume fraction for components. + fix_mtl_texture_paths (bool): Whether to fix MTL texture paths. + skip_blacklisted (bool): Whether to skip blacklisted models. + return_sdf_path (bool): If True, return the configured SDF file path. + + Returns: + str: Path to the configured SDF file or model directory. + + Raises: + RuntimeError: If a valid model cannot be found after multiple attempts. + """ + + # Loop until a model is found, checked for validity, configured and returned + # If any of these steps fail, sample another model and try again + # Note: Due to this behaviour, the function could stall if all models are invalid + # TODO: Add a simple timeout to random sampling of valid model (# of attempts or time-based) + while True: + # Get path to a random model from the collection + model_path = self.get_random_model_path() + + # Check if the model is already blacklisted and skip if desired + if skip_blacklisted and self.is_blacklisted(model_path): + continue + + # Check is the model is already configured + if self.is_configured(model_path): + # If so, break the loop + break + + # Process the model and break loop only if it is valid + if self.process_model( + model_path, + decimation_fraction_of_visual=decimation_fraction_of_visual, + decimation_min_faces=decimation_min_faces, + decimation_max_faces=decimation_max_faces, + max_faces=max_faces, + max_vertices=max_vertices, + component_min_faces_fraction=component_min_faces_fraction, + component_max_volume_fraction=component_max_volume_fraction, + fix_mtl_texture_paths=fix_mtl_texture_paths, + ): + break + + # Apply randomization + self.randomize_configured_model( + model_path, + min_scale=min_scale, + max_scale=max_scale, + min_friction=min_friction, + max_friction=max_friction, + min_mass=min_mass, + max_mass=max_mass, + ) + + if return_sdf_path: + # Return path to the configured SDF file + return self.get_configured_sdf_path(model_path) + else: + # Return path to the model directory + return model_path + + def process_all_models( + self, + decimation_fraction_of_visual=0.025, + decimation_min_faces=8, + decimation_max_faces=400, + max_faces=40000, + max_vertices=None, + component_min_faces_fraction=0.1, + component_max_volume_fraction=0.35, + fix_mtl_texture_paths=True, + ): + """ + Processes all models in the collection, applying configuration and decimation. + + This method iterates over each model in the collection, applying visual decimation + and checking for validity. If a model cannot be processed successfully, it is + blacklisted. The method tracks and prints the number of processed models and + the count of blacklisted models at the end of execution. + + Args: + decimation_fraction_of_visual (float): Fraction of visual decimation to apply. + Default is 0.025. + decimation_min_faces (int): Minimum number of faces for decimation. Default is 8. + decimation_max_faces (int): Maximum number of faces for decimation. Default is 400. + max_faces (int): Maximum faces allowed for the model. Default is 40000. + max_vertices (int, optional): Maximum vertices allowed for the model. Default is None. + component_min_faces_fraction (float): Minimum face fraction for components during + processing. Default is 0.1. + component_max_volume_fraction (float): Maximum volume fraction for components during + processing. Default is 0.35. + fix_mtl_texture_paths (bool): Whether to fix MTL texture paths for the models. + Default is True. + + Returns: + None: This method modifies the models in place and does not return a value. + + Prints: + - The status of each processed model along with its index. + - The total number of blacklisted models after processing all models. + + Raises: + None: The method does not raise exceptions but may log issues if models cannot be + processed. + """ + if self._unique_cache: + model_paths = self._model_paths + else: + model_paths = self._class_model_paths + + blacklist_model_counter = 0 + for i in range(len(model_paths)): + if not self.process_model( + model_paths[i], + decimation_fraction_of_visual=decimation_fraction_of_visual, + decimation_min_faces=decimation_min_faces, + decimation_max_faces=decimation_max_faces, + max_faces=max_faces, + max_vertices=max_vertices, + component_min_faces_fraction=component_min_faces_fraction, + component_max_volume_fraction=component_max_volume_fraction, + fix_mtl_texture_paths=fix_mtl_texture_paths, + ): + blacklist_model_counter += 1 + + print('Processed model %i/%i "%s"' % (i, len(model_paths), model_paths[i])) + + print("Number of blacklisted models: %i" % blacklist_model_counter) + + def process_model( + self, + model_path, + decimation_fraction_of_visual=0.25, + decimation_min_faces=40, + decimation_max_faces=200, + max_faces=40000, + max_vertices=None, + component_min_faces_fraction=0.1, + component_max_volume_fraction=0.35, + fix_mtl_texture_paths=True, + ) -> bool: + """ + Processes a specified model to configure it for simulation, applying geometry + decimation and checking for various validity criteria. + + This method parses the SDF (Simulation Description Format) of the specified + model, processes its components, checks for geometry validity, and updates + inertial properties as needed. The processed model is then saved back to + an SDF file. + + Args: + model_path (str): Path to the model to be processed. + decimation_fraction_of_visual (float): Fraction of visual geometry to retain + during decimation. Default is 0.25. + decimation_min_faces (int): Minimum number of faces allowed in the decimated + visual geometry. Default is 40. + decimation_max_faces (int): Maximum number of faces allowed in the decimated + visual geometry. Default is 200. + max_faces (int): Maximum number of faces for the entire model. Default is 40000. + max_vertices (Optional[int]): Maximum number of vertices for the model. Default is None. + component_min_faces_fraction (float): Minimum face fraction for components to + be considered valid during processing. Default is 0.1. + component_max_volume_fraction (float): Maximum volume fraction for components + to be considered valid during processing. Default is 0.35. + fix_mtl_texture_paths (bool): Whether to fix texture paths in MTL files for + mesh formats. Default is True. + + Returns: + bool: Returns True if the model was processed successfully; otherwise, + returns False if any validity checks fail or if processing issues are encountered. + + Raises: + None: The method does not raise exceptions but may return False if processing + fails due to model invalidity. + + Notes: + - The model is blacklisted if it fails to meet the specified criteria for + geometry and inertial properties. + - The method updates the SDF of the model with processed geometries and + inertial properties. + """ + + # Parse the SDF of the model + sdf = parse_sdf(self.get_sdf_path(model_path)) + + # Process the model(s) contained in the SDF + for model in sdf.models: + # Process the link(s) of each model + for link in model.links: + # Get rid of the existing collisions prior to simplifying it + link.collisions.clear() + + # Values for the total inertial properties of current link + # These values will be updated for each body that the link contains + total_mass = 0.0 + total_inertia = [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0]] + common_centre_of_mass = [0.0, 0.0, 0.0] + + # Go through the visuals and process them + for visual in link.visuals: + # Get path to the mesh of the link's visual + mesh_path = self.get_mesh_path(model_path, visual) + + # If desired, fix texture path in 'mtl' files for '.obj' mesh format + if fix_mtl_texture_paths: + self.fix_mtl_texture_paths( + model_path, mesh_path, model.attributes["name"] + ) + + # Load the mesh (without materials) + mesh = trimesh.load(mesh_path, force="mesh", skip_materials=True) + + # Check if model has too much geometry (blacklist if needed) + if not self.check_excessive_geometry( + mesh, model_path, max_faces=max_faces, max_vertices=max_vertices + ): + return False + + # Check if model has disconnected geometry/components (blacklist if needed) + if not self.check_disconnected_components( + mesh, + model_path, + component_min_faces_fraction=component_min_faces_fraction, + component_max_volume_fraction=component_max_volume_fraction, + ): + return False + + # Compute inertial properties for this mesh + ( + total_mass, + total_inertia, + common_centre_of_mass, + ) = self.sum_inertial_properties( + mesh, total_mass, total_inertia, common_centre_of_mass + ) + + # Add decimated collision geometry to the SDF + self.add_collision( + mesh, + link, + model_path, + fraction_of_visual=decimation_fraction_of_visual, + min_faces=decimation_min_faces, + max_faces=decimation_max_faces, + ) + + # Write original scale (size) into the SDF + # This is used for later reference during randomization (for scale limits) + self.write_original_scale(mesh, model_path) + + # Make sure the link has valid inertial properties (blacklist if needed) + if not self.check_inertial_properties( + model_path, total_mass, total_inertia + ): + return False + + # Write inertial properties to the SDF of the link + self.write_inertial_properties( + link, total_mass, total_inertia, common_centre_of_mass + ) + + # Write the configured SDF into a file + sdf.export_xml(self.get_configured_sdf_path(model_path)) + return True + + def add_collision( + self, + mesh, + link, + model_path, + fraction_of_visual=0.05, + min_faces=8, + max_faces=750, + friction=1.0, + ): + """ + Adds collision geometry to a specified link in a model, using a simplified + version of the provided mesh. + + This method creates a collision mesh by decimating the visual geometry of + the model, generating an SDF (Simulation Description Format) element for + the collision, and adding it to the specified link. + + Args: + mesh (trimesh.Trimesh): The original mesh geometry from which the + collision geometry will be created. + link (Link): The link to which the collision geometry will be added. + model_path (str): The path to the model where the collision mesh will + be stored. + fraction_of_visual (float): The fraction of the visual mesh to retain + for the collision mesh. Default is 0.05. + min_faces (int): The minimum number of faces allowed in the collision + mesh after decimation. Default is 8. + max_faces (int): The maximum number of faces allowed in the collision + mesh after decimation. Default is 750. + friction (float): The friction coefficient to be applied to the collision + surface. Default is 1.0. + + Returns: + None: This method does not return a value. + + Notes: + - The collision mesh is generated through quadratic decimation of the + original visual mesh based on the specified parameters. + - The created collision mesh is stored in the same directory as the + model, and its path is relative to the model path. + - The method updates the link's SDF with the collision geometry and + surface properties. + """ + + # Determine name of path to the collision geometry + collision_name = ( + link.attributes["name"] + "_collision_" + str(len(link.collisions)) + ) + collision_mesh_path = self.get_collision_mesh_path(model_path, collision_name) + + # Determine number of faces to keep after the decimation + face_count = min( + max(fraction_of_visual * len(mesh.faces), min_faces), max_faces + ) + + # Simplify mesh via decimation + collision_mesh = mesh.simplify_quadratic_decimation(face_count) + + # Export the collision mesh to the appropriate location + os.makedirs(os.path.dirname(collision_mesh_path), exist_ok=True) + collision_mesh.export( + collision_mesh_path, file_type=self.__collision_mesh_file_type + ) + + # Create collision SDF element + collision = create_sdf_element("collision") + + # Add collision geometry to the SDF + collision.geometry.mesh = create_sdf_element("mesh") + collision.geometry.mesh.uri = os.path.relpath( + collision_mesh_path, start=model_path + ) + + # Add surface friction to the SDF of collision (default to 1 and randomize later) + collision.surface = create_sdf_element("surface") + collision.surface.friction = create_sdf_element("friction", "surface") + collision.surface.friction.ode = create_sdf_element("ode", "collision") + collision.surface.friction.ode.mu = friction + collision.surface.friction.ode.mu2 = friction + + # Add it to the SDF of the link + collision_name = os.path.basename(collision_mesh_path).split(".")[0] + link.add_collision(collision_name, collision) + + def sum_inertial_properties( + self, mesh, total_mass, total_inertia, common_centre_of_mass, density=1.0 + ) -> tuple[float, float, float]: + # Arbitrary density is used here + # The mass will be randomized once it is fully computed for a link + mesh.density = density + + # Tmp variable to store the mass of all previous geometry, used to determine centre of mass + mass_of_others = total_mass + + # For each additional mesh, simply add the mass and inertia + total_mass += mesh.mass + total_inertia += mesh.moment_inertia + + # Compute a common centre of mass between all previous geometry and the new mesh + common_centre_of_mass = [ + mass_of_others * common_centre_of_mass[0] + mesh.mass * mesh.center_mass[0], + mass_of_others * common_centre_of_mass[1] + mesh.mass * mesh.center_mass[1], + mass_of_others * common_centre_of_mass[2] + mesh.mass * mesh.center_mass[2], + ] / total_mass + + return total_mass, total_inertia, common_centre_of_mass + + def randomize_configured_model( + self, + model_path, + min_scale=0.05, + max_scale=0.25, + min_mass=0.1, + max_mass=3.0, + min_friction=0.75, + max_friction=1.5, + ): + """ + Randomizes the scale, mass, and friction properties of a configured model + in the specified SDF file. + + This method modifies the properties of each link in the model, applying + random values within specified ranges for scale, mass, and friction. + The randomized values overwrite the original settings in the configured + SDF file. + + Args: + model_path (str): The path to the model directory containing the + configured SDF file. + min_scale (float): The minimum scale factor for randomization. + Default is 0.05. + max_scale (float): The maximum scale factor for randomization. + Default is 0.25. + min_mass (float): The minimum mass for randomization. Default is 0.1. + max_mass (float): The maximum mass for randomization. Default is 3.0. + min_friction (float): The minimum friction coefficient for randomization. + Default is 0.75. + max_friction (float): The maximum friction coefficient for randomization. + Default is 1.5. + + Returns: + None: This method does not return a value. + + Notes: + - The configured SDF file is updated in place, meaning the original + properties are overwritten with the new randomized values. + - The randomization is applied to each link in the model, ensuring + a diverse range of physical properties. + """ + + # Get path to the configured SDF file + configured_sdf_path = self.get_configured_sdf_path(model_path) + + # Parse the configured SDF that needs to be randomized + sdf = parse_sdf(configured_sdf_path) + + # Process the model(s) contained in the SDF + for model in sdf.models: + # Process the link(s) of each model + for link in model.links: + # Randomize scale of the link + self.randomize_scale( + model_path, link, min_scale=min_scale, max_scale=max_scale + ) + + # Randomize inertial properties of the link + self.randomize_inertial(link, min_mass=min_mass, max_mass=max_mass) + + # Randomize friction of the link + self.randomize_friction( + link, min_friction=min_friction, max_friction=max_friction + ) + + # Overwrite the configured SDF file with randomized values + sdf.export_xml(configured_sdf_path) + + def randomize_scale(self, model_path, link, min_scale=0.05, max_scale=0.25): + """ + Randomizes the scale of a link's geometry within a specified range. + + This method modifies the scale of the visual and collision geometry + of a link in the model. The scale is randomized using a uniform + distribution within the given minimum and maximum scale values. + Additionally, the link's inertial properties (mass and inertia) + are recalculated based on the new scale. + + Args: + model_path (str): The path to the model directory, used to + read the original scale of the mesh. + link (Link): The link object containing the visual and collision + geometries to be scaled. + min_scale (float): The minimum scale factor for randomization. + Default is 0.05. + max_scale (float): The maximum scale factor for randomization. + Default is 0.25. + + Returns: + bool: Returns `False` if the link has more than one visual, + indicating that scaling is not supported. Returns `None` + if the scaling is successful. + + Notes: + - This method currently supports only links that contain a + single mesh geometry. + - The mass of the link is scaled by the cube of the scale factor, + while the inertial properties are scaled by the fifth power of + the scale factor. + - The scale values are applied uniformly to all dimensions (x, y, z). + """ + + # Note: This function currently supports only scaling of links with single mesh geometry + if len(link.visuals) > 1: + return False + + # Get a random scale for the size of mesh + random_scale = self.np_random.uniform(min_scale, max_scale) + + # Determine a scale factor that will result in such scale for the size of mesh + original_mesh_scale = self.read_original_scale(model_path) + scale_factor = random_scale / original_mesh_scale + + # Determine scale factor for inertial properties based on random scale and current scale + current_scale = link.visuals[0].geometry.mesh.scale.value[0] + inertial_scale_factor = scale_factor / current_scale + + # Write scale factor into SDF for visual and collision geometry + link.visuals[0].geometry.mesh.scale = [scale_factor] * 3 + link.collisions[0].geometry.mesh.scale = [scale_factor] * 3 + + # Recompute inertial properties according to the scale + link.inertial.pose.x *= inertial_scale_factor + link.inertial.pose.y *= inertial_scale_factor + link.inertial.pose.z *= inertial_scale_factor + + # Mass is scaled n^3 + link.mass = link.mass.value * inertial_scale_factor**3 + + # Inertia is scaled n^5 + inertial_scale_factor_n5 = inertial_scale_factor**5 + link.inertia.ixx = link.inertia.ixx.value * inertial_scale_factor_n5 + link.inertia.iyy = link.inertia.iyy.value * inertial_scale_factor_n5 + link.inertia.izz = link.inertia.izz.value * inertial_scale_factor_n5 + link.inertia.ixy = link.inertia.ixy.value * inertial_scale_factor_n5 + link.inertia.ixz = link.inertia.ixz.value * inertial_scale_factor_n5 + link.inertia.iyz = link.inertia.iyz.value * inertial_scale_factor_n5 + + def randomize_inertial( + self, link, min_mass=0.1, max_mass=3.0 + ) -> tuple[float, float]: + """ + Randomizes the mass and updates the inertial properties of a link. + + This method assigns a random mass to the link within the specified + range and recalculates its inertial properties based on the new mass. + + Args: + link (Link): The link object whose mass and inertial properties + will be randomized. + min_mass (float): The minimum mass for randomization. Default is 0.1. + max_mass (float): The maximum mass for randomization. Default is 3.0. + + Returns: + tuple[float, float]: A tuple containing the new mass and the + mass scale factor used to update the inertial properties. + + Notes: + - The method modifies the link's mass and updates its + inertial properties (ixx, iyy, izz, ixy, ixz, iyz) based on the + ratio of the new mass to the original mass. + """ + + random_mass = self.np_random.uniform(min_mass, max_mass) + mass_scale_factor = random_mass / link.mass.value + + link.mass = random_mass + link.inertia.ixx = link.inertia.ixx.value * mass_scale_factor + link.inertia.iyy = link.inertia.iyy.value * mass_scale_factor + link.inertia.izz = link.inertia.izz.value * mass_scale_factor + link.inertia.ixy = link.inertia.ixy.value * mass_scale_factor + link.inertia.ixz = link.inertia.ixz.value * mass_scale_factor + link.inertia.iyz = link.inertia.iyz.value * mass_scale_factor + + def randomize_friction(self, link, min_friction=0.75, max_friction=1.5): + """ + Randomizes the friction coefficients of a link's collision surfaces. + + This method assigns random friction values to each collision surface + of the link within the specified range. + + Args: + link (Link): The link object whose collision surfaces' friction + coefficients will be randomized. + min_friction (float): The minimum friction coefficient for + randomization. Default is 0.75. + max_friction (float): The maximum friction coefficient for + randomization. Default is 1.5. + + Notes: + - The friction coefficients are applied to both the + 'mu' and 'mu2' attributes of the collision surface's friction + properties. + """ + + for collision in link.collisions: + random_friction = self.np_random.uniform(min_friction, max_friction) + + collision.surface.friction.ode.mu = random_friction + collision.surface.friction.ode.mu2 = random_friction + + def write_inertial_properties(self, link, mass, inertia, centre_of_mass): + """ + Writes the specified mass and inertial properties to a link. + + This method updates the link's mass, inertia tensor, and + centre of mass based on the provided values. + + Args: + link (Link): The link object to be updated with new inertial properties. + mass (float): The mass to set for the link. + inertia (list[list[float]]): A 3x3 list representing the + inertia tensor of the link. + centre_of_mass (list[float]): A list containing the x, y, z + coordinates of the link's centre of mass. + + Notes: + - The method directly modifies the link's mass and inertia properties, + as well as its inertial pose, which is set to the specified centre of mass. + """ + + link.mass = mass + + link.inertia.ixx = inertia[0][0] + link.inertia.iyy = inertia[1][1] + link.inertia.izz = inertia[2][2] + link.inertia.ixy = inertia[0][1] + link.inertia.ixz = inertia[0][2] + link.inertia.iyz = inertia[1][2] + + link.inertial.pose = [ + centre_of_mass[0], + centre_of_mass[1], + centre_of_mass[2], + 0.0, + 0.0, + 0.0, + ] + + def write_original_scale(self, mesh, model_path): + """ + Writes the original scale of the mesh to a file. + + This method records the scale of the provided mesh into a text file, + which can be used later for reference during randomization or scaling + operations. + + Args: + mesh (Mesh): The mesh object whose original scale is to be recorded. + model_path (str): The path to the model directory where the + original scale file will be saved. + + Notes: + - The scale is written as a string representation of the mesh's + scale property. + - The file is created or overwritten at the location returned + by the `get_original_scale_path` method. + """ + + file = open(self.get_original_scale_path(model_path), "w") + file.write(str(mesh.scale)) + file.close() + + def read_original_scale(self, model_path) -> float: + """ + Reads the original scale of a model from a file. + + This method retrieves the original scale value that was previously + saved for a specific model. The scale is expected to be stored as + a string in a file, and this method converts it back to a float. + + Args: + model_path (str): The path to the model directory from which + to read the original scale. + + Returns: + float: The original scale of the model. + + Raises: + ValueError: If the contents of the scale file cannot be converted to a float. + """ + + file = open(self.get_original_scale_path(model_path), "r") + original_scale = file.read() + file.close() + + return float(original_scale) + + def check_excessive_geometry( + self, mesh, model_path, max_faces=40000, max_vertices=None + ) -> bool: + """ + Checks if the mesh exceeds the specified geometry limits. + + This method evaluates the number of faces and vertices in the + given mesh. If the mesh exceeds the defined limits for faces + or vertices, it blacklists the model and returns False. + + Args: + mesh (Mesh): The mesh object to be checked for excessive geometry. + model_path (str): The path to the model directory for logging purposes. + max_faces (int, optional): The maximum allowed number of faces. + Defaults to 40000. + max_vertices (int, optional): The maximum allowed number of vertices. + Defaults to None. + + Returns: + bool: True if the mesh does not exceed the limits; otherwise, False. + """ + + if max_faces is not None: + num_faces = len(mesh.faces) + if num_faces > max_faces: + self.blacklist_model( + model_path, reason="Excessive geometry (%d faces)" % num_faces + ) + return False + + if max_vertices is not None: + num_vertices = len(mesh.vertices) + if num_vertices > max_vertices: + self.blacklist_model( + model_path, reason="Excessive geometry (%d vertices)" % num_vertices + ) + return False + + return True + + def check_disconnected_components( + self, + mesh, + model_path, + component_min_faces_fraction=0.05, + component_max_volume_fraction=0.1, + ) -> bool: + """ + Checks for disconnected components within the mesh. + + This method identifies connected components within the mesh. If + there are multiple components, it evaluates their relative volumes. + If any component exceeds the specified volume fraction threshold, + the model is blacklisted. + + Args: + mesh (Mesh): The mesh object to be evaluated for disconnected components. + model_path (str): The path to the model directory for logging purposes. + component_min_faces_fraction (float, optional): The minimum fraction + of faces required for a component to be considered. Defaults to 0.05. + component_max_volume_fraction (float, optional): The maximum allowed + volume fraction for a component. Defaults to 0.1. + + Returns: + bool: True if the mesh has no significant disconnected components; + otherwise, False. + """ + + # Get a list of all connected components inside the mesh + # Consider components only with `component_min_faces_fraction` percent faces + min_faces = round(component_min_faces_fraction * len(mesh.faces)) + connected_components = trimesh.graph.connected_components( + mesh.face_adjacency, min_len=min_faces + ) + + # If more than 1 objects were detected, consider also relative volume of the meshes + if len(connected_components) > 1: + total_volume = mesh.volume + + large_component_counter = 0 + for component in connected_components: + submesh = mesh.copy() + mask = np.zeros(len(mesh.faces), dtype=np.bool) + mask[component] = True + submesh.update_faces(mask) + + volume_fraction = submesh.volume / total_volume + if volume_fraction > component_max_volume_fraction: + large_component_counter += 1 + + if large_component_counter > 1: + self.blacklist_model( + model_path, + reason="Disconnected components (%d instances)" + % len(connected_components), + ) + return False + + return True + + def check_inertial_properties(self, model_path, mass, inertia) -> bool: + """ + Checks the validity of inertial properties for a model. + + This method evaluates whether the mass and the principal moments of + inertia are valid. If any of these values are below a specified threshold, + the model is blacklisted. + + Args: + model_path (str): The path to the model directory for logging purposes. + mass (float): The mass of the model to be checked. + inertia (list of list of float): A 2D list representing the inertia matrix. + + Returns: + bool: True if the inertial properties are valid; otherwise, False. + """ + if ( + mass < 1e-10 + or inertia[0][0] < 1e-10 + or inertia[1][1] < 1e-10 + or inertia[2][2] < 1e-10 + ): + self.blacklist_model(model_path, reason="Invalid inertial properties") + return False + + return True + + def get_random_model_path(self) -> str: + """ + Retrieves a random model path from the available models. + + This method selects and returns a random model path. The selection + depends on whether a unique cache is being used or not. + + Returns: + str: A randomly selected model path. + """ + if self._unique_cache: + return self.np_random.choice(self._model_paths) + else: + return self.np_random.choice(self._class_model_paths) + + def get_collision_mesh_path(self, model_path, collision_name) -> str: + """ + Constructs the path for the collision mesh file. + + This method generates and returns the file path for a collision + mesh based on the model path and the name of the collision. + + Args: + model_path (str): The path to the model directory. + collision_name (str): The name of the collision geometry. + + Returns: + str: The full path to the collision mesh file. + """ + return os.path.join( + model_path, + self.__collision_mesh_dir, + collision_name + "." + self.__collision_mesh_file_type, + ) + + def get_sdf_path(self, model_path) -> str: + """ + Constructs the path for the SDF (Simulation Description Format) file. + + This method generates and returns the file path for the SDF file + corresponding to the given model path. + + Args: + model_path (str): The path to the model directory. + + Returns: + str: The full path to the SDF file. + """ + return os.path.join(model_path, self.__sdf_base_name) + + def get_configured_sdf_path(self, model_path) -> str: + """ + Constructs the path for the configured SDF file. + + This method generates and returns the file path for the configured + SDF file that includes any modifications made to the original model. + + Args: + model_path (str): The path to the model directory. + + Returns: + str: The full path to the configured SDF file. + """ + return os.path.join(model_path, self.__configured_sdf_base_name) + + def get_blacklisted_path(self, model_path) -> str: + """ + Constructs the path for the blacklisted model file. + + This method generates and returns the file path where information + about blacklisted models is stored. + + Args: + model_path (str): The path to the model directory. + + Returns: + str: The full path to the blacklisted model file. + """ + return os.path.join(model_path, self.__blacklisted_base_name) + + def get_mesh_path(self, model_path, visual_or_collision) -> str: + """ + Constructs the path for the mesh associated with a visual or collision. + + This method retrieves the URI from the specified visual or collision + object and constructs the full path to the corresponding mesh file. + + Args: + model_path (str): The path to the model directory. + visual_or_collision (object): An object containing the geometry + information for either visual or collision. + + Returns: + str: The full path to the mesh file. + + Notes: + This method may require adjustments for specific collections or models. + """ + # TODO: This might need fixing for certain collections/models + mesh_uri = visual_or_collision.geometry.mesh.uri.value + return os.path.join(model_path, mesh_uri) + + def get_original_scale_path(self, model_path) -> str: + """ + Constructs the path for the original scale file. + + This method generates and returns the file path for the file + that stores the original scale of the model. + + Args: + model_path (str): The path to the model directory. + + Returns: + str: The full path to the original scale file. + """ + return os.path.join(model_path, self.__original_scale_base_name) + + def blacklist_model(self, model_path, reason="Unknown"): + """ + Blacklists a model by writing its path and the reason to a file. + + If blacklisting is enabled, this method writes the specified reason + for blacklisting the model to a designated file. It also logs the + blacklisting action. + + Args: + model_path (str): The path to the model directory. + reason (str): The reason for blacklisting the model. Default is "Unknown". + """ + if self._enable_blacklisting: + bl_file = open(self.get_blacklisted_path(model_path), "w") + bl_file.write(reason) + bl_file.close() + logger.warn( + '%s model "%s". Reason: %s.' + % ( + "Blacklisting" if self._enable_blacklisting else "Skipping", + model_path, + reason, + ) + ) + + def is_blacklisted(self, model_path) -> bool: + """ + Checks if a model is blacklisted. + + This method checks if the blacklisted file for a given model exists, + indicating that the model has been blacklisted. + + Args: + model_path (str): The path to the model directory. + + Returns: + bool: True if the model is blacklisted; otherwise, False. + """ + return os.path.isfile(self.get_blacklisted_path(model_path)) + + def is_configured(self, model_path) -> bool: + """ + Checks if a model is configured. + + This method checks if the configured SDF file for a given model + exists, indicating that the model has been processed and configured. + + Args: + model_path (str): The path to the model directory. + + Returns: + bool: True if the model is configured; otherwise, False. + """ + return os.path.isfile(self.get_configured_sdf_path(model_path)) + + def fix_mtl_texture_paths(self, model_path, mesh_path, model_name): + """ + Fixes the texture paths in the associated MTL file of an OBJ model. + + This method modifies the texture paths in the MTL file associated + with a given OBJ file to ensure they are correctly linked to + the model's textures. It also ensures that the texture files are + uniquely named by prepending the model's name to avoid conflicts. + + Args: + model_path (str): The path to the model directory where textures are located. + mesh_path (str): The path to the OBJ file for which the MTL file needs fixing. + model_name (str): The name of the model, used to make texture file names unique. + + Notes: + - This method scans the model directory for texture files, identifies + the relevant MTL file, and updates any texture paths in that MTL file. + - If a texture file's name does not include the model's name, the method + renames it to include the model's name. + - The method only processes MTL files linked to OBJ files. + """ + # The `.obj` files use mtl + if mesh_path.endswith(".obj"): + # Find all textures located in the model path, used later to relative linking + texture_files = glob.glob(os.path.join(model_path, "**", "textures", "*.*")) + + # Find location of mtl file, if any + mtllib_file = None + with open(mesh_path, "r") as file: + for line in file: + if "mtllib" in line: + mtllib_file = line.split(" ")[-1].strip() + break + + if mtllib_file is not None: + mtllib_file = os.path.join(os.path.dirname(mesh_path), mtllib_file) + + fin = open(mtllib_file, "r") + data = fin.read() + for line in data.splitlines(): + if "map_" in line: + # Find the name of the texture/map in the mtl + map_file = line.split(" ")[-1].strip() + + # Find the first match of the texture/map file + for texture_file in texture_files: + if os.path.basename( + texture_file + ) == map_file or os.path.basename( + texture_file + ) == os.path.basename(map_file): + # Make the file unique to the model (unless it already is) + if model_name in texture_file: + new_texture_file_name = texture_file + else: + new_texture_file_name = texture_file.replace( + map_file, model_name + "_" + map_file + ) + + os.rename(texture_file, new_texture_file_name) + + # Apply the correct relative path + data = data.replace( + map_file, + os.path.relpath( + new_texture_file_name, + start=os.path.dirname(mesh_path), + ), + ) + break + fin.close() + + # Write in the correct data + fout = open(mtllib_file, "w") + fout.write(data) + fout.close() diff --git a/env_manager/env_manager/env_manager/models/utils/xacro2sdf.py b/env_manager/env_manager/env_manager/models/utils/xacro2sdf.py new file mode 100644 index 0000000..2a682ee --- /dev/null +++ b/env_manager/env_manager/env_manager/models/utils/xacro2sdf.py @@ -0,0 +1,37 @@ + +import subprocess +import tempfile +from typing import Dict, Optional, Tuple + +import xacro + + +def xacro2sdf( + input_file_path: str, mappings: Dict, model_path_remap: Optional[Tuple[str, str]] +) -> str: + """Convert xacro (URDF variant) with given arguments to SDF and return as a string.""" + + # Convert all values in mappings to strings + for keys, values in mappings.items(): + mappings[keys] = str(values) + + # Convert xacro to URDF + urdf_xml = xacro.process(input_file_name=input_file_path, mappings=mappings) + + # Create temporary file for URDF (`ign sdf -p` accepts only files) + with tempfile.NamedTemporaryFile() as tmp_urdf: + with open(tmp_urdf.name, "w") as urdf_file: + urdf_file.write(urdf_xml) + + # Convert to SDF + result = subprocess.run( + ["ign", "sdf", "-p", tmp_urdf.name], stdout=subprocess.PIPE + ) + sdf_xml = result.stdout.decode("utf-8") + + # Remap package name to model name, such that meshes can be located by Ignition + if model_path_remap is not None: + sdf_xml = sdf_xml.replace(model_path_remap[0], model_path_remap[1]) + + # Return as string + return sdf_xml diff --git a/env_manager/env_manager/env_manager/scene/__init__.py b/env_manager/env_manager/env_manager/scene/__init__.py new file mode 100644 index 0000000..421848f --- /dev/null +++ b/env_manager/env_manager/env_manager/scene/__init__.py @@ -0,0 +1 @@ +from .scene import Scene diff --git a/env_manager/env_manager/env_manager/scene/scene.py b/env_manager/env_manager/env_manager/scene/scene.py new file mode 100644 index 0000000..a42e4f8 --- /dev/null +++ b/env_manager/env_manager/env_manager/scene/scene.py @@ -0,0 +1,1480 @@ +from dataclasses import asdict + +import numpy as np +import rclpy +from geometry_msgs.msg import Point as RosPoint +from geometry_msgs.msg import Quaternion as RosQuat +from gym_gz.scenario.model_wrapper import ModelWrapper +from rbs_assets_library import get_model_meshes_info +from rcl_interfaces.srv import GetParameters +from rclpy.node import Node, Parameter +from scenario.bindings.gazebo import GazeboSimulator, PhysicsEngine_dart, World +from scipy.spatial import distance +from scipy.spatial.transform import Rotation +from visualization_msgs.msg import Marker, MarkerArray + +from env_manager.models.terrains.random_ground import RandomGround + +from ..models import Box, Camera, Cylinder, Ground, Mesh, Model, Plane, Sphere, Sun +from ..models.configs import CameraData, ObjectData, SceneData +from ..models.robots import get_robot_model_class +from ..utils import Tf2Broadcaster, Tf2DynamicBroadcaster +from ..utils.conversions import quat_to_wxyz +from ..utils.gazebo import ( + transform_move_to_model_pose, + transform_move_to_model_position, +) +from ..utils.types import Point, Pose + + +# TODO: Split scene randomizer and scene +class Scene: + """ + Manages the simulation scene during runtime, including object and environment randomization. + + The Scene class initializes and manages various components in a Gazebo simulation + environment, such as robots, cameras, lights, and terrain. It also provides methods + for scene setup, parameter retrieval, and scene initialization. + + Attributes: + gazebo (GazeboSimulator): An instance of the Gazebo simulator. + robot (RobotData): The robot data configuration. + cameras (list[CameraData]): List of camera configurations. + objects (list[ObjectData]): List of object configurations in the scene. + node (Node): The ROS 2 node for communication. + light (LightData): The light configuration for the scene. + terrain (TerrainData): The terrain configuration for the scene. + world (World): The Gazebo world instance. + """ + + def __init__( + self, + node: Node, + gazebo: GazeboSimulator, + scene: SceneData, + robot_urdf_string: str, + ) -> None: + """ + Initializes the Scene object with the necessary components and parameters. + + Args: + - node (Node): The ROS 2 node for managing communication and parameters. + - gazebo (GazeboSimulator): An instance of the Gazebo simulator to manage the simulation. + - scene (SceneData): A data object containing configuration for the scene. + - robot_urdf_string (str): The URDF string of the robot model. + """ + self.gazebo = gazebo + self.robot = scene.robot + self.cameras = scene.camera + self.objects = scene.objects + self.node = node + self.light = scene.light + self.terrain = scene.terrain + self.__scene_initialized = False + self.__plugin_scene_broadcaster = True + self.__plugin_user_commands = True + self.__fts_enable = True + self.__plugint_sensor_render_engine = "ogre2" + self.world: World = gazebo.get_world() + + self.__objects_unique_names = {} + self.object_models: list[ModelWrapper] = [] + self.__object_positions: dict[str, Point] = {} + self.__objects_workspace_centre: Point = (0.0, 0.0, 0.0) + + if not robot_urdf_string: + self.param_client = node.create_client( + GetParameters, "/robot_state_publisher/get_parameters" + ) + self.get_parameter_sync() + # scene.robot.urdf_string = ( + # node.get_parameter("robot_description") + # .get_parameter_value() + # .string_value + # ) + else: + scene.robot.urdf_string = robot_urdf_string + + self.tf2_broadcaster = Tf2Broadcaster(node=node) + self.tf2_broadcaster_dyn = Tf2DynamicBroadcaster(node=node) + + self.__workspace_center = (0.0, 0.0, 0.0) + self.__workspace_dimensions = (1.5, 1.5, 1.5) + + half_width = self.__workspace_dimensions[0] / 2 + half_height = self.__workspace_dimensions[1] / 2 + half_depth = self.__workspace_dimensions[2] / 2 + + self.__workspace_min_bound = ( + self.__workspace_center[0] - half_width, + self.__workspace_center[1] - half_height, + self.__workspace_center[2] - half_depth, + ) + self.__workspace_max_bound = ( + self.__workspace_center[0] + half_width, + self.__workspace_center[1] + half_height, + self.__workspace_center[2] + half_depth, + ) + + # self.marker_array = MarkerArray() + + def get_parameter_sync(self): + """ + Retrieves the `robot_description` parameter synchronously, waiting for the asynchronous call to complete. + """ + while not self.param_client.wait_for_service(timeout_sec=5.0): + self.node.get_logger().info( + "Service /robot_state_publisher/get_parameters is unavailable, waiting ..." + ) + + request = self.create_get_parameters_request() + future = self.param_client.call_async(request) + + rclpy.spin_until_future_complete(self.node, future) + + if future.result() is None: + raise RuntimeError("Failed to retrieve the robot_description parameter") + + response = future.result() + if not response.values or not response.values[0].string_value: + raise RuntimeError("The robot_description parameter is missing or empty") + + value = response.values[0] + self.node.get_logger().info( + "Succesfully got parameter response from robot_state_publisher" + ) + param = Parameter( + "robot_description", Parameter.Type.STRING, value.string_value + ) + self.robot.urdf_string = value.string_value + self.node.set_parameters([param]) + + def create_get_parameters_request(self) -> GetParameters.Request: + """ + Creates a request to get the parameters from the robot state publisher. + + Returns: + GetParameters.Request: A request object containing the parameter name to retrieve. + """ + return GetParameters.Request(names=["robot_description"]) + + def init_scene(self): + """ + Initializes the simulation scene by adding the terrain, lights, robots, and objects. + + This method pauses the Gazebo simulation, sets up the physics engine, and + configures the environment and components as defined in the SceneData. + + Note: + This method must be called after the Scene object has been initialized + and before running the simulation. + """ + + self.gazebo_paused_run() + + self.init_world_plugins() + + self.world.set_physics_engine(PhysicsEngine_dart) + + self.add_terrain() + self.add_light() + self.add_robot() + for obj in self.objects: + self.add_object(obj) + for camera in self.cameras: + self.add_camera(camera) + + self.__scene_initialized = True + + def reset_scene(self): + """ + Resets the scene to its initial state by resetting the robot joint positions + and randomizing the positions of objects and cameras. + + This method performs the following actions: + - Resets the joint positions of the robot. + - Clears previously stored object positions. + - For each object in the scene, if randomization is enabled, + randomizes its position; otherwise, resets it to its original pose. + - Randomizes the pose of enabled cameras if their pose has expired. + + Note: + This method assumes that the objects and cameras have been properly initialized + and that their properties (like randomization and pose expiration) are set correctly. + """ + self.reset_robot_joint_positions() + + object_randomized = set() + self.__object_positions.clear() + for object in self.objects: + if object.name in object_randomized: + continue + # TODO: Add color randomization (something that affects the runtime during the second spawn of an object) + # if object.randomize.random_color: + # self.randomize_object_color(object) + if object.randomize.random_pose: + self.randomize_object_position(object) + else: + self.reset_objects_pose(object) + object_randomized.add(object.name) + + for camera in self.cameras: + if camera.enable and self.is_camera_pose_expired(camera): + self.randomize_camera_pose(camera=camera) + + def init_world_plugins(self): + """ + Initializes and inserts world plugins into the Gazebo simulator for various functionalities. + + This method configures the following plugins based on the internal settings: + - **SceneBroadcaster**: Inserts the scene broadcaster plugin to enable GUI clients to receive + updates about the scene. This is only done if the scene broadcaster is enabled. + - **UserCommands**: Inserts the user commands plugin to allow user interactions with the scene. + - **Sensors**: Inserts the sensors plugin if any cameras are enabled. The rendering engine for + sensors can be specified. + - **ForceTorque**: Inserts the Force Torque Sensor plugin if enabled. + + The method pauses the Gazebo simulation after inserting plugins to ensure that changes take effect. + + Note: + If plugins are already active, this method does not reinsert them. + """ + # SceneBroadcaster + if self.__plugin_scene_broadcaster: + if not self.gazebo.scene_broadcaster_active(self.world.to_gazebo().name()): + self.node.get_logger().info( + "Inserting world plugins for broadcasting scene to GUI clients..." + ) + self.world.to_gazebo().insert_world_plugin( + "gz-sim-scene-broadcaster-system", + "gz::sim::systems::SceneBroadcaster", + ) + + self.gazebo_paused_run() + + # UserCommands + if self.__plugin_user_commands: + self.node.get_logger().info( + "Inserting world plugins to enable user commands..." + ) + self.world.to_gazebo().insert_world_plugin( + "gz-sim-user-commands-system", + "gz::sim::systems::UserCommands", + ) + + self.gazebo_paused_run() + + # Sensors + self._camera_enable = False + for camera in self.cameras: + if camera.enable: + self._camera_enable = True + + if self._camera_enable: + self.node.get_logger().info( + f"Inserting world plugins for sensors with {self.__plugint_sensor_render_engine} rendering engine..." + ) + self.world.to_gazebo().insert_world_plugin( + "libgz-sim-sensors-system.so", + "gz::sim::systems::Sensors", + "" + f"{self.__plugint_sensor_render_engine}" + "", + ) + + if self.__fts_enable: + self.world.to_gazebo().insert_world_plugin( + "gz-sim-forcetorque-system", + "gz::sim::systems::ForceTorque", + ) + + self.gazebo_paused_run() + + def add_robot(self): + """ + Configure and insert the robot into the simulation. + + This method performs the following actions: + - Retrieves the robot model class based on the robot's name. + - Instantiates the robot model with specified parameters including position, orientation, + URDF string, and initial joint positions for both the arm and gripper. + - Ensures that the instantiated robot's name is unique and returns the actual name used. + - Enables contact detection for all gripper links (fingers) of the robot. + - Pauses the Gazebo simulation to apply the changes. + - Resets the robot's joints to their default positions. + + Note: + The method assumes that the robot name is valid and that the associated model class + can be retrieved. If the robot's URDF string or joint positions are not correctly specified, + this may lead to errors during robot instantiation. + + Raises: + RuntimeError: If the robot model class cannot be retrieved for the specified robot name. + """ + + robot_model_class = get_robot_model_class(self.robot.name) + + # Instantiate robot class based on the selected model + self.robot_wrapper = robot_model_class( + world=self.world, + name=self.robot.name, + node=self.node, + position=self.robot.spawn_position, + orientation=quat_to_wxyz(self.robot.spawn_quat_xyzw), + urdf_string=self.robot.urdf_string, + initial_arm_joint_positions=self.robot.joint_positions, + initial_gripper_joint_positions=self.robot.gripper_joint_positions, + ) + + # The desired name is passed as arg on creation, however, a different name might be selected to be unique + # Therefore, return the name back to the task + self.robot_name = self.robot_wrapper.name() + + # Enable contact detection for all gripper links (fingers) + robot_gazebo = self.robot_wrapper.to_gazebo() + robot_gazebo.enable_contacts() + + self.gazebo_paused_run() + + # Reset robot joints to the defaults + self.reset_robot_joint_positions() + + def add_camera(self, camera: CameraData): + """ + Configure and insert a camera into the simulation, placing it with respect to the robot. + + The method performs the following steps: + - Determines the appropriate position and orientation of the camera based on whether it is + relative to the world or to the robot. + - Creates an instance of the `Camera` class with the specified parameters, including + position, orientation, type, dimensions, image formatting, update rate, field of view, + clipping properties, noise characteristics, and ROS 2 bridge publishing options. + - Pauses the Gazebo simulation to apply changes. + - Attaches the camera to the robot if the camera's reference is not the world. + - Broadcasts the transformation (TF) of the camera relative to the robot. + + Args: + - camera (CameraData): The camera data containing configuration options including: + + Raises: + - Exception: If the camera cannot be attached to the robot. + + Notes: + The method expects the camera data to be correctly configured. If the camera's + `relative_to` field does not match any existing model in the world, it will raise an + exception when attempting to attach the camera to the robot. + """ + + if self.world.to_gazebo().name() == camera.relative_to: + camera_position = camera.spawn_position + camera_quat_wxyz = quat_to_wxyz(camera.spawn_quat_xyzw) + else: + # Transform the pose of camera to be with respect to robot - but still represented in world reference frame for insertion into the world + camera_position, camera_quat_wxyz = transform_move_to_model_pose( + world=self.world, + position=camera.spawn_position, + quat=quat_to_wxyz(camera.spawn_quat_xyzw), + target_model=self.robot_wrapper, + target_link=camera.relative_to, + xyzw=False, + ) + + # Create camera + self.camera_wrapper = Camera( + name=camera.name, + world=self.world, + position=camera_position, + orientation=camera_quat_wxyz, + camera_type=camera.type, + width=camera.width, + height=camera.height, + image_format=camera.image_format, + update_rate=camera.update_rate, + horizontal_fov=camera.horizontal_fov, + vertical_fov=camera.vertical_fov, + clip_color=camera.clip_color, + clip_depth=camera.clip_depth, + noise_mean=camera.noise_mean, + noise_stddev=camera.noise_stddev, + ros2_bridge_color=camera.publish_color, + ros2_bridge_depth=camera.publish_depth, + ros2_bridge_points=camera.publish_points, + ) + + self.gazebo_paused_run() + + # Attach to robot if needed + if self.world.to_gazebo().name() != camera.relative_to: + if not self.robot_wrapper.to_gazebo().attach_link( + camera.relative_to, + self.camera_wrapper.name(), + self.camera_wrapper.link_name, + ): + raise Exception("Cannot attach camera link to robot") + + self.__is_camera_attached = True + + self.gazebo_paused_run() + + # Broadcast tf + self.tf2_broadcaster.broadcast_tf( + parent_frame_id=camera.relative_to, + child_frame_id=self.camera_wrapper.frame_id, + translation=camera.spawn_position, + rotation=camera.spawn_quat_xyzw, + xyzw=True, + ) + + def add_object(self, obj: ObjectData): + """ + Configure and insert an object into the simulation. + + Args: + obj (ObjectData): The object data containing configuration options. + + Raises: + NotImplementedError: If the specified type is not supported. + """ + obj_dict = asdict(obj) + obj_dict["world"] = self.world + + try: + object_wrapper = self._create_object_wrapper(obj, obj_dict) + self._register_object(obj, object_wrapper) + self._enable_contact_detection(object_wrapper) + + self.node.get_logger().info( + f"Added object: {obj.name}, relative_to: {obj.relative_to}" + ) + self.node.get_logger().info( + f"Position: {obj.position}, Orientation: {obj.orientation}" + ) + + self._initialize_tf_and_markers(obj, object_wrapper) + + except Exception as ex: + self.node.get_logger().warn(f"Model could not be inserted. Reason: {ex}") + + def _create_object_wrapper(self, obj: ObjectData, obj_dict: dict) -> ModelWrapper: + """Create the appropriate object wrapper based on the type.""" + if obj.type != "": + return self._create_by_type(obj.type, obj_dict) + else: + return self._create_by_data_class(obj, obj_dict) + + def _create_by_type(self, obj_type: str, obj_dict: dict) -> ModelWrapper: + match obj_type: + case "box": + return Box(**obj_dict) + case "plane": + return Plane(**obj_dict) + case "sphere": + return Sphere(**obj_dict) + case "cylinder": + return Cylinder(**obj_dict) + case "model": + return Model(**obj_dict) + case "mesh": + return Mesh(**obj_dict) + case _: + raise NotImplementedError(f"Unsupported object type: {obj_type}") + + def _create_by_data_class(self, obj: ObjectData, obj_dict: dict) -> ModelWrapper: + from ..models.configs import ( + BoxObjectData, + CylinderObjectData, + MeshData, + ModelData, + PlaneObjectData, + SphereObjectData, + ) + + match obj: + case BoxObjectData(): + return Box(**obj_dict) + case PlaneObjectData(): + return Plane(**obj_dict) + case SphereObjectData(): + return Sphere(**obj_dict) + case CylinderObjectData(): + return Cylinder(**obj_dict) + case ModelData(): + return Model(**obj_dict) + case MeshData(): + return Mesh(**obj_dict) + case _: + raise NotImplementedError("Unsupported object data class") + + def _register_object(self, obj: ObjectData, wrapper: ModelWrapper): + model_name = wrapper.name() + self.__objects_unique_names.setdefault(obj.name, []).append(model_name) + self.__object_positions[model_name] = obj.position + self.object_models.append(wrapper.model) + + def _enable_contact_detection(self, wrapper: ModelWrapper): + for link_name in wrapper.link_names(): + link = wrapper.to_gazebo().get_link(link_name=link_name) + link.enable_contact_detection(True) + + def _initialize_tf_and_markers(self, obj: ObjectData, wrapper: ModelWrapper): + self._setup_marker_array() + marker = self._create_marker(obj, wrapper, len(self.object_models)) + if marker: + self.marker_array.markers.append(marker) + # Start broadcasting once when len of markers == 1 + if len(self.marker_array.markers) == 1: + self._setup_tf_broadcaster() + + def _setup_tf_broadcaster(self): + if not hasattr(self, "tf_broadcaster_and_markers"): + self.tf_broadcaster_and_markers = self.node.create_timer( + 0.1, self.publish_marker + ) + + def _setup_marker_array(self): + if not hasattr(self, "marker_array"): + self.marker_array = MarkerArray() + self.marker_publisher = self.node.create_publisher( + MarkerArray, "/markers", 10 + ) + + def _create_marker( + self, obj: ObjectData, wrapper: ModelWrapper, id: int + ) -> Marker | None: + """Create a visualization marker based on the object type.""" + marker = Marker() + marker.header.frame_id = obj.relative_to + marker.header.stamp = self.node.get_clock().now().to_msg() + marker.ns = "assembly" + marker.id = id + + type_map = { + "mesh": Marker.MESH_RESOURCE, + "model": Marker.MESH_RESOURCE, + "sphere": Marker.SPHERE, + "box": Marker.CUBE, + "cylinder": Marker.CYLINDER, + } + + if obj.type not in type_map: + self.node.get_logger().fatal(f"Unsupported object type: {obj.type}") + return None + + marker.type = type_map[obj.type] + self._configure_marker_geometry_and_color(marker, obj) + + model_position, model_orientation = self.rotate_around_parent( + wrapper.base_position(), + wrapper.base_orientation(), + (0.0, 0.0, 0.0), + (1.0, 0.0, 0.0, 0.0), + ) + + position = RosPoint() + orientation = RosQuat() + position.x = model_position[0] + position.y = model_position[1] + position.z = model_position[2] + + orientation.w = model_orientation[0] + orientation.x = model_orientation[1] + orientation.y = model_orientation[2] + orientation.z = model_orientation[3] + + marker.pose.position = position + marker.pose.orientation = orientation + marker.action = Marker.ADD + + return marker + + def _configure_marker_geometry_and_color(self, marker: Marker, obj: ObjectData): + """Set marker geometry and color.""" + if obj.type in ["mesh", "model"]: + marker.mesh_resource = f"file://{get_model_meshes_info(obj.name)['visual']}" + marker.mesh_use_embedded_materials = True + marker.scale.x = marker.scale.y = marker.scale.z = 1.0 + elif obj.type == "sphere": + marker.scale.x = marker.scale.y = marker.scale.z = obj.radius + elif obj.type == "box": + marker.scale.x, marker.scale.y, marker.scale.z = obj.size + elif obj.type == "cylinder": + marker.scale.x = marker.scale.y = obj.radius * 2 + marker.scale.z = obj.length + + marker.color.r, marker.color.g, marker.color.b, marker.color.a = ( + 0.0, + 0.5, + 1.0, + 1.0, + ) + + def publish_marker(self): + if not self.marker_array: + return + + for idx, model in enumerate(self.object_models): + if self.marker_array.markers[idx]: + model_position, model_orientation = ( + model.base_position(), + model.base_orientation(), + ) + + position = RosPoint() + orientation = RosQuat() + position.x = model_position[0] + position.y = model_position[1] + position.z = model_position[2] + + orientation.w = model_orientation[0] + orientation.x = model_orientation[1] + orientation.y = model_orientation[2] + orientation.z = model_orientation[3] + self.marker_array.markers[idx].pose.position = position + self.marker_array.markers[idx].pose.orientation = orientation + + self.tf2_broadcaster_dyn.broadcast_tf( + parent_frame_id="world", + child_frame_id=model.base_frame(), + translation=model_position, + rotation=model_orientation, + xyzw=False, + ) + self.marker_publisher.publish(self.marker_array) + + def rotate_around_parent( + self, position, orientation, parent_position, parent_orientation + ): + """ + Apply a 180-degree rotation around the parent's Z-axis to the object's pose. + + Args: + position: Tuple (x, y, z) - the object's position relative to the parent. + orientation: Tuple (w, x, y, z) - the object's orientation relative to the parent. + parent_position: Tuple (x, y, z) - the parent's position. + parent_orientation: Tuple (w, x, y, z) - the parent's orientation. + + Returns: + A tuple containing the updated position and orientation: + (new_position, new_orientation) + """ + # Define a quaternion for 180-degree rotation around Z-axis (w, x, y, z) + rotation_180_z = (0.0, 0.0, 0.0, 1.0) + w1, x1, y1, z1 = orientation + # Кватернион для 180° поворота вокруг Z + w2, x2, y2, z2 = (0, 0, 0, 1) + + # Умножение кватернионов + w3 = w1 * w2 - x1 * x2 - y1 * y2 - z1 * z2 + x3 = w1 * x2 + x1 * w2 + y1 * z2 - z1 * y2 + y3 = w1 * y2 - x1 * z2 + y1 * w2 + z1 * x2 + z3 = w1 * z2 + x1 * y2 - y1 * x2 + z1 * w2 + new_orientation = (w3, x3, y3, z3) + + # Compute the new orientation: parent_orientation * rotation_180_z * orientation + # new_orientation = ( + # parent_orientation[0] * rotation_180_z[0] - parent_orientation[1] * rotation_180_z[1] - + # parent_orientation[2] * rotation_180_z[2] - parent_orientation[3] * rotation_180_z[3], + # parent_orientation[0] * rotation_180_z[1] + parent_orientation[1] * rotation_180_z[0] + + # parent_orientation[2] * rotation_180_z[3] - parent_orientation[3] * rotation_180_z[2], + # parent_orientation[0] * rotation_180_z[2] - parent_orientation[1] * rotation_180_z[3] + + # parent_orientation[2] * rotation_180_z[0] + parent_orientation[3] * rotation_180_z[1], + # parent_orientation[0] * rotation_180_z[3] + parent_orientation[1] * rotation_180_z[2] - + # parent_orientation[2] * rotation_180_z[1] + parent_orientation[3] * rotation_180_z[0], + # ) + + # Apply rotation to the position + rotated_position = ( + -position[0], # Rotate 180 degrees around Z-axis: x -> -x + -position[1], # y -> -y + position[2], # z remains unchanged + ) + + # Add parent position + new_position = ( + parent_position[0] + rotated_position[0], + parent_position[1] + rotated_position[1], + parent_position[2] + rotated_position[2], + ) + + return new_position, new_orientation + + def add_light(self): + """ + Configure and insert a default light source into the simulation. + + This method initializes and adds a light source to the Gazebo simulation based on the + specified light type. Currently, it supports a "sun" type light. If an unsupported + light type is specified, it raises an error. + + Raises: + RuntimeError: If the specified light type is unsupported, including: + - "random_sun": Currently not implemented. + - Any other unrecognized light type. + + Notes: + - The method constructs the light using the properties defined in the `self.light` object, + which should include direction, color, distance, visual properties, and radius, + as applicable for the specified light type. + - After adding the light to the simulation, the method pauses the Gazebo simulation + to ensure the scene is updated. + """ + + # Create light + match self.light.type: + case "sun": + self.light = Sun( + self.world, + direction=self.light.direction, + color=self.light.color, + distance=self.light.distance, + visual=self.light.visual, + radius=self.light.radius, + ) + case "random_sun": + raise RuntimeError("random_sun is not supported yet") + case _: + raise RuntimeError( + f"Type of light [{self.light.type}] currently not supported" + ) + + self.gazebo_paused_run() + + def add_terrain(self): + """ + Configure and insert default terrain into the simulation. + + This method initializes and adds a terrain element to the Gazebo simulation using + the properties specified in the `self.terrain` object. Currently, it creates a + ground plane, but there are plans to support additional terrain types in the future. + + Raises: + NotImplementedError: If there are attempts to add terrain types other than + the default ground. + + Notes: + - The method utilizes properties such as name, spawn position, spawn quaternion + (for orientation), and size defined in `self.terrain` to create the terrain. + - After the terrain is added, contact detection is enabled for all links associated + with the terrain object. + - The method pauses the Gazebo simulation after adding the terrain to ensure + changes are reflected in the environment. + """ + + if self.terrain.type == "flat": + self.terrain_wrapper = Ground( + self.world, + name=self.terrain.name, + position=self.terrain.spawn_position, + orientation=quat_to_wxyz(self.terrain.spawn_quat_xyzw), + size=self.terrain.size, + ambient=self.terrain.ambient, + diffuse=self.terrain.diffuse, + specular=self.terrain.specular, + ) + elif self.terrain.type == "random_flat": + self.terrain_wrapper = RandomGround( + self.world, + name=self.terrain.name, + position=self.terrain.spawn_position, + orientation=quat_to_wxyz(self.terrain.spawn_quat_xyzw), + size=self.terrain.size, + ) + else: + raise ValueError( + "Type of ground is not supported, supported type is: [ground, random_ground]" + ) + + # Enable contact detection + for link_name in self.terrain_wrapper.link_names(): + link = self.terrain_wrapper.to_gazebo().get_link(link_name=link_name) + link.enable_contact_detection(True) + + self.gazebo_paused_run() + + # def randomize_object_color(self, object: ObjectData): + # # debugpy.listen(5678) + # # debugpy.wait_for_client() + # task_object_names = self.__objects_unique_names[object.name] + # for object_name in task_object_names: + # if not self.world.to_gazebo().remove_model(object_name): + # self.node.get_logger().error(f"Failed to remove {object_name}") + # raise RuntimeError(f"Failed to remove {object_name}") + # + # self.gazebo_paused_run() + # del self.__objects_unique_names[object.name] + # self.add_object(object) + + def randomize_object_position(self, object: ObjectData): + """ + Randomize the position and/or orientation of a specified object in the simulation. + + This method retrieves the names of the object instances from the scene and updates + their positions and orientations based on the randomization settings defined in + the `object` parameter. The method applies random transformations to the object's + pose according to the specified flags in the `ObjectData` instance. + + Args: + object (ObjectData): An instance of `ObjectData` containing the properties + of the object to be randomized. + + Raises: + KeyError: If the object name is not found in the unique object names dictionary. + + Notes: + - If `random_pose` is `True`, both position and orientation are randomized. + - If `random_orientation` is `True`, only the orientation is randomized, while + the position remains unchanged. + - If `random_position` is `True`, only the position is randomized, while the + orientation remains unchanged. + """ + task_object_names = self.__objects_unique_names[object.name] + for object_name in task_object_names: + position, quat_random = self.get_random_object_pose(object) + obj = self.world.to_gazebo().get_model(object_name).to_gazebo() + if object.randomize.random_pose: + obj.reset_base_pose(position, quat_random) + elif object.randomize.random_orientation: + obj.reset_base_pose(object.position, quat_random) + elif object.randomize.random_position: + obj.reset_base_pose(position, object.orientation) + + self.__object_positions[object_name] = position + + self.gazebo_paused_run() + + def randomize_camera_pose(self, camera: CameraData): + """ + Randomize the pose of a specified camera in the simulation. + + This method updates the camera's position and orientation based on the selected + randomization mode. The new pose is computed relative to either the world frame or + a specified target model (e.g., the robot). The camera can be detached from the robot + during the pose update and reattached afterward if needed. + + Args: + camera (CameraData): An instance of `CameraData` containing properties of the + camera to be randomized. + + Raises: + TypeError: If the randomization mode specified in `camera.random_pose_mode` is + invalid. + Exception: If the camera cannot be detached from or attached to the robot. + + Notes: + - Supported randomization modes for camera pose: + - `"orbit"`: The camera is positioned in an orbital path around the object. + - `"select_random"`: A random camera pose is selected from predefined options. + - `"select_nearest"`: The camera is positioned based on the nearest predefined + camera pose. + """ + # Get random camera pose, centered at object position (or center of object spawn box) + if "orbit" == camera.random_pose_mode: + camera_position, camera_quat_xyzw = self.get_random_camera_pose_orbit( + camera + ) + elif "select_random" == camera.random_pose_mode: + ( + camera_position, + camera_quat_xyzw, + ) = self.get_random_camera_pose_sample_random(camera) + elif "select_nearest" == camera.random_pose_mode: + ( + camera_position, + camera_quat_xyzw, + ) = self.get_random_camera_pose_sample_nearest(camera) + else: + raise TypeError("Invalid mode for camera pose randomization.") + + if self.world.to_gazebo().name() == camera.relative_to: + transformed_camera_position = camera_position + transformed_camera_quat_wxyz = quat_to_wxyz(camera_quat_xyzw) + else: + # Transform the pose of camera to be with respect to robot - but represented in world reference frame for insertion into the world + ( + transformed_camera_position, + transformed_camera_quat_wxyz, + ) = transform_move_to_model_pose( + world=self.world, + position=camera_position, + quat=quat_to_wxyz(camera_quat_xyzw), + target_model=self.robot_wrapper, + target_link=camera.relative_to, + xyzw=False, + ) + + # Detach camera if needed + if self.__is_camera_attached: + if not self.robot_wrapper.to_gazebo().detach_link( + camera.relative_to, + self.camera_wrapper.name(), + self.camera_wrapper.link_name, + ): + raise Exception("Cannot detach camera link from robot") + + self.gazebo_paused_run() + + # Move pose of the camera + camera_gazebo = self.camera_wrapper.to_gazebo() + camera_gazebo.reset_base_pose( + transformed_camera_position, transformed_camera_quat_wxyz + ) + + self.gazebo_paused_run() + + # Attach to robot again if needed + if self.__is_camera_attached: + if not self.robot_wrapper.to_gazebo().attach_link( + camera.relative_to, + self.camera_wrapper.name(), + self.camera_wrapper.link_name, + ): + raise Exception("Cannot attach camera link to robot") + + self.gazebo_paused_run() + + # Broadcast tf + self.tf2_broadcaster.broadcast_tf( + parent_frame_id=camera.relative_to, + child_frame_id=self.camera_wrapper.frame_id, + translation=camera_position, + rotation=camera_quat_xyzw, + xyzw=True, + ) + + def get_random_camera_pose_orbit(self, camera: CameraData) -> Pose: + """ + Generate a random camera pose in an orbital path around a focal point. + + This method computes a random position for the camera based on an orbital distance + and height range. The camera's orientation is calculated to focus on a specified + focal point. The generated position ensures that it does not fall within a specified + arc behind the robot. + + Args: + camera (CameraData): An instance of `CameraData` containing properties of the + camera, including the orbital distance, height range, + focal point offset, and arc behind the robot to ignore. + + Returns: + Pose: A tuple containing the randomly generated position and orientation + (as a quaternion) of the camera. + + Notes: + - The method utilizes a random number generator to create a uniformly + distributed position within specified bounds. + - The computed camera orientation is represented in the quaternion format. + """ + rng = np.random.default_rng() + + while True: + position = rng.uniform( + low=(-1.0, -1.0, camera.random_pose_orbit_height_range[0]), + high=(1.0, 1.0, camera.random_pose_orbit_height_range[1]), + ) + + norm = np.linalg.norm(position) + position /= norm + + if ( + abs(np.arctan2(position[0], position[1]) + np.pi / 2) + > camera.random_pose_orbit_ignore_arc_behind_robot + ): + break + + rpy = np.array( + [ + 0.0, + np.arctan2( + position[2] - camera.random_pose_focal_point_z_offset, + np.linalg.norm(position[:2]), + ), + np.arctan2(position[1], position[0]) + np.pi, + ] + ) + quat_xyzw = Rotation.from_euler("xyz", rpy).as_quat() + + position *= camera.random_pose_orbit_distance + position[:2] += self.__objects_workspace_centre[:2] + + return tuple(position), tuple(quat_xyzw) + + def get_random_camera_pose_sample_random(self, camera: CameraData) -> Pose: + """ + Select a random position from the predefined camera position options. + + This method randomly selects one of the available camera position options + specified in the `camera` object and processes it to generate the camera's pose. + + Args: + camera (CameraData): An instance of `CameraData` containing the available + position options for random selection. + + Returns: + Pose: A tuple containing the selected camera position and its orientation + (as a quaternion). + """ + # Select a random entry from the options + camera.random_pose_select_position_options + + selection = camera.random_pose_select_position_options[ + np.random.randint(len(camera.random_pose_select_position_options)) + ] + + return self.get_random_camera_pose_sample_process(camera, selection) + + def get_random_camera_pose_sample_nearest(self, camera: CameraData) -> Pose: + """ + Select the nearest entry from the predefined camera position options. + + This method calculates the squared distances of the camera position options + from a central point and selects the nearest one to generate the camera's pose. + + Args: + camera (CameraData): An instance of `CameraData` containing the position options + to choose from. + + Returns: + Pose: A tuple containing the nearest camera position and its orientation + (as a quaternion). + """ + # Select the nearest entry + dist_sqr = np.sum( + ( + np.array(camera.random_pose_select_position_options) + - np.array(camera.random_pose_select_position_options) + ) + ** 2, + axis=1, + ) + nearest = camera.random_pose_select_position_options[np.argmin(dist_sqr)] + + return self.get_random_camera_pose_sample_process(camera, nearest) + + def get_random_camera_pose_sample_process( + self, camera: CameraData, position: Point + ) -> Pose: + """ + Process the selected camera position to determine its orientation. + + This method calculates the camera's orientation based on the selected position, + ensuring that the camera faces a focal point adjusted by a specified offset. + + Args: + camera (CameraData): An instance of `CameraData` that contains properties + used for orientation calculations. + position (Point): A 3D point representing the camera's position. + + Returns: + Pose: A tuple containing the camera's position and its orientation + (as a quaternion). + + Notes: + - The orientation is computed using roll, pitch, and yaw angles based on + the position relative to the workspace center. + """ + # Determine orientation such that camera faces the center + rpy = [ + 0.0, + np.arctan2( + position[2] - camera.random_pose_focal_point_z_offset, + np.linalg.norm( + ( + position[0] - self.__objects_workspace_centre[0], + position[1] - self.__objects_workspace_centre[1], + ), + 2, + ), + ), + np.arctan2( + position[1] - self.__objects_workspace_centre[1], + position[0] - self.__objects_workspace_centre[0], + ) + + np.pi, + ] + quat_xyzw = Rotation.from_euler("xyz", rpy).as_quat() + + return camera.spawn_position, tuple(quat_xyzw) + + def reset_robot_pose(self): + """ + Reset the robot's pose to a randomized position or its default spawn position. + + If the robot's randomizer is enabled for pose randomization, this method will + generate a new random position within the specified spawn volume and assign + a random orientation. Otherwise, it will reset the robot's pose to its default + spawn position and orientation. + + The new position is calculated by adding a random offset within the spawn + volume to the robot's initial spawn position. The orientation is generated + as a random rotation around the z-axis. + + Raises: + Exception: If there are issues resetting the robot pose in the Gazebo simulation. + + Notes: + - The position is a 3D vector represented as [x, y, z]. + - The orientation is represented as a quaternion in the form (x, y, z, w). + """ + if self.robot.randomizer.pose: + position = [ + self.robot.spawn_position[0] + + np.random.RandomState().uniform( + -self.robot.randomizer.spawn_volume[0] / 2, + self.robot.randomizer.spawn_volume[0] / 2, + ), + self.robot.spawn_position[1] + + np.random.RandomState().uniform( + -self.robot.randomizer.spawn_volume[1] / 2, + self.robot.randomizer.spawn_volume[1] / 2, + ), + self.robot.spawn_position[2] + + np.random.RandomState().uniform( + -self.robot.randomizer.spawn_volume[2] / 2, + self.robot.randomizer.spawn_volume[2] / 2, + ), + ] + quat_xyzw = Rotation.from_euler( + "xyz", (0, 0, np.random.RandomState().uniform(-np.pi, np.pi)) + ).as_quat() + quat_xyzw = tuple(quat_xyzw) + else: + position = self.robot.spawn_position + quat_xyzw = self.robot.spawn_quat_xyzw + + gazebo_robot = self.robot_wrapper.to_gazebo() + gazebo_robot.reset_base_pose(position, quat_to_wxyz(quat_xyzw)) + + self.gazebo_paused_run() + + def reset_robot_joint_positions(self): + """ + Reset the robot's joint positions and velocities to their initial values. + + This method retrieves the robot's initial arm joint positions and applies + them to the robot in the Gazebo simulation. If joint position randomization + is enabled, it adds Gaussian noise to the joint positions based on the + specified standard deviation. + + Additionally, the method resets the velocities of both the arm and gripper + joints to zero. After updating the joint states, it executes an unpaused step + in Gazebo to process the modifications and update the joint states. + + Raises: + RuntimeError: If there are issues resetting joint positions or velocities + in the Gazebo simulation, or if the Gazebo step fails. + + Notes: + - This method assumes the robot has a gripper only if `self.robot.with_gripper` is true. + - Joint positions for the gripper are reset only if gripper actuated joint names are available. + """ + gazebo_robot = self.robot_wrapper.to_gazebo() + + arm_joint_positions = self.robot_wrapper.initial_arm_joint_positions + + # Add normal noise if desired + if self.robot.randomizer.joint_positions: + for joint_position in arm_joint_positions: + joint_position += np.random.RandomState().normal( + loc=0.0, scale=self.robot.randomizer.joint_positions_std + ) + + # Arm joints - apply joint positions zero out velocities + if not gazebo_robot.reset_joint_positions( + arm_joint_positions, self.robot_wrapper.robot.actuated_joint_names + ): + raise RuntimeError("Failed to reset robot joint positions") + if not gazebo_robot.reset_joint_velocities( + [0.0] * len(self.robot_wrapper.robot.actuated_joint_names), + self.robot_wrapper.robot.actuated_joint_names, + ): + raise RuntimeError("Failed to reset robot joint velocities") + + # Gripper joints - apply joint positions zero out velocities + if ( + self.robot.with_gripper + and self.robot_wrapper.robot.gripper_actuated_joint_names + ): + if not gazebo_robot.reset_joint_positions( + self.robot_wrapper.initial_gripper_joint_positions, + self.robot_wrapper.robot.gripper_actuated_joint_names, + ): + raise RuntimeError("Failed to reset gripper joint positions") + if not gazebo_robot.reset_joint_velocities( + [0.0] * len(self.robot_wrapper.robot.gripper_actuated_joint_names), + self.robot_wrapper.robot.gripper_actuated_joint_names, + ): + raise RuntimeError("Failed to reset gripper joint velocities") + + # Execute an unpaused run to process model modification and get new JointStates + if not self.gazebo.step(): + raise RuntimeError("Failed to execute an unpaused Gazebo step") + + # if self.robot.with_gripper: + # if ( + # self.robot_wrapper.CLOSED_GRIPPER_JOINT_POSITIONS + # == self.robot.gripper_joint_positions + # ): + # self.gripper_controller.close() + # else: + # self.gripper.open() + + def reset_objects_pose(self, object: ObjectData): + """ + Reset the pose of specified objects in the simulation. + + This method updates the base position and orientation of all instances of + the specified object type in the Gazebo simulation to their defined + positions and orientations. + + Args: + object (ObjectData): The object data containing the name and the desired + position and orientation for the objects to be reset. + + Raises: + KeyError: If the specified object's name is not found in the unique names + registry. + + Notes: + - The method retrieves the list of unique names for the specified object + type and resets the pose of each instance to the provided position and + orientation from the `object` data. + """ + task_object_names = self.__objects_unique_names[object.name] + for object_name in task_object_names: + obj = self.world.to_gazebo().get_model(object_name).to_gazebo() + obj.reset_base_pose(object.position, object.orientation) + + self.gazebo_paused_run() + + def get_random_object_pose( + self, + obj: ObjectData, + name: str = "", + min_distance_to_other_objects: float = 0.2, + min_distance_decay_factor: float = 0.95, + ) -> Pose: + """ + Generate a random pose for an object, ensuring it is sufficiently + distanced from other objects. + + This method computes a random position within a specified spawn volume for + the given object. It checks that the new position does not violate minimum + distance constraints from existing objects in the simulation. + + Args: + obj (ObjectData): The object data containing the base position, + randomization parameters, and relative positioning info. + name (str, optional): The name of the object being positioned. Defaults to an empty string. + Mic_distance_to_other_objects (float, optional): The minimum required distance + from other objects. Defaults to 0.2. + min_distance_decay_factor (float, optional): Factor by which the minimum distance + will decay if the new position is + too close to existing objects. Defaults to 0.95. + + Returns: + Pose: A tuple containing the randomly generated position (x, y, z) and a + randomly generated orientation (quaternion). + + Notes: + - The method uses a uniform distribution to select random coordinates + within the object's defined spawn volume. + - The quaternion is generated to provide a random orientation for the object. + - The method iteratively checks for proximity to other objects and adjusts the + minimum distance if necessary. + """ + is_too_close = True + # The default value for randomization + object_position = obj.position + while is_too_close: + object_position = ( + obj.position[0] + + np.random.uniform( + -obj.randomize.random_spawn_volume[0] / 2, + obj.randomize.random_spawn_volume[0] / 2, + ), + obj.position[1] + + np.random.uniform( + -obj.randomize.random_spawn_volume[1] / 2, + obj.randomize.random_spawn_volume[1] / 2, + ), + obj.position[2] + + np.random.uniform( + -obj.randomize.random_spawn_volume[2] / 2, + obj.randomize.random_spawn_volume[2] / 2, + ), + ) + + if self.world.to_gazebo().name() != obj.relative_to: + # Transform the pose of camera to be with respect to robot - but represented in world reference frame for insertion into the world + object_position = transform_move_to_model_position( + world=self.world, + position=object_position, + target_model=self.robot_wrapper, + target_link=obj.relative_to, + ) + + # Check if position is far enough from other + is_too_close = False + for ( + existing_object_name, + existing_object_position, + ) in self.__object_positions.items(): + if existing_object_name == name: + # Do not compare to itself + continue + if ( + distance.euclidean(object_position, existing_object_position) + < min_distance_to_other_objects + ): + min_distance_to_other_objects *= min_distance_decay_factor + is_too_close = True + break + + quat = np.random.uniform(-1, 1, 4) + quat /= np.linalg.norm(quat) + + return object_position, tuple(quat) + + def is_camera_pose_expired(self, camera: CameraData) -> bool: + """ + Check if the camera pose has expired and needs to be randomized. + + This method evaluates whether the camera's current pose has reached its + limit for randomization based on the specified rollout count. If the + camera has exceeded the allowed number of rollouts, it will reset the + counter and indicate that the pose should be randomized. + + Args: + camera (CameraData): The camera data containing the current rollout + counter and the maximum number of rollouts + allowed before a new pose is required. + + Returns: + bool: True if the camera pose needs to be randomized (i.e., it has + expired), False otherwise. + """ + + if camera.random_pose_rollouts_num == 0: + return False + + camera.random_pose_rollout_counter += 1 + + if camera.random_pose_rollout_counter >= camera.random_pose_rollouts_num: + camera.random_pose_rollout_counter = 0 + return True + + return False + + def gazebo_paused_run(self): + """ + Execute a run in Gazebo while paused. + + This method attempts to run the Gazebo simulation in a paused state. + If the operation fails, it raises a RuntimeError to indicate the failure. + + Raises: + RuntimeError: If the Gazebo run operation fails. + """ + if not self.gazebo.run(paused=True): + raise RuntimeError("Failed to execute a paused Gazebo run") + + def check_object_outside_workspace( + self, + object_position: Point, + ) -> bool: + """ + Check if an object is outside the defined workspace. + + This method evaluates whether the given object position lies outside the + specified workspace boundaries, which are defined by a parallelepiped + determined by minimum and maximum bounds. + + Args: + object_position (Point): A tuple or list representing the 3D position + of the object in the format (x, y, z). + + Returns: + bool: True if the object is outside the workspace, False otherwise. + """ + + return ( + object_position[0] < self.__workspace_min_bound[0] + or object_position[1] < self.__workspace_min_bound[1] + or object_position[2] < self.__workspace_min_bound[2] + or object_position[0] > self.__workspace_max_bound[0] + or object_position[1] > self.__workspace_max_bound[1] + or object_position[2] > self.__workspace_max_bound[2] + ) + + def check_object_overlapping( + self, + object: ObjectData, + allowed_penetration_depth: float = 0.001, + terrain_allowed_penetration_depth: float = 0.002, + ) -> bool: + """ + Check for overlapping objects in the simulation and reset their positions if necessary. + + This method iterates through all objects and ensures that none of them are overlapping. + If an object is found to be overlapping with another object (or the robot), it resets + its position to a random valid pose. Collisions or overlaps with terrain are ignored. + + Args: + object (ObjectData): The object data to check for overlaps. + allowed_penetration_depth (float, optional): The maximum allowed penetration depth + between objects. Defaults to 0.001. + terrain_allowed_penetration_depth (float, optional): The maximum allowed penetration + depth when in contact with terrain. Defaults to 0.002. + + Returns: + bool: True if all objects are in valid positions, False if any had to be reset. + """ + + # Update object positions + for object_name in self.__objects_unique_names[object.name]: + model = self.world.get_model(object_name).to_gazebo() + self.__object_positions[object_name] = model.get_link( + link_name=model.link_names()[0] + ).position() + + for object_name in self.__objects_unique_names[object.name]: + obj = self.world.get_model(object_name).to_gazebo() + + # Make sure the object is inside workspace + if self.check_object_outside_workspace( + self.__object_positions[object_name] + ): + position, quat_random = self.get_random_object_pose( + object, + name=object_name, + ) + obj.reset_base_pose(position, quat_random) + obj.reset_base_world_velocity([0.0, 0.0, 0.0], [0.0, 0.0, 0.0]) + return False + + # Make sure the object is not intersecting other objects + try: + for contact in obj.contacts(): + depth = np.mean([point.depth for point in contact.points]) + if ( + self.terrain_wrapper.name() in contact.body_b + and depth < terrain_allowed_penetration_depth + ): + continue + if ( + self.robot_wrapper.name() in contact.body_b + or depth > allowed_penetration_depth + ): + position, quat_random = self.get_random_object_pose( + object, + name=object_name, + ) + obj.reset_base_pose(position, quat_random) + obj.reset_base_world_velocity([0.0, 0.0, 0.0], [0.0, 0.0, 0.0]) + return False + except Exception as e: + self.node.get_logger().error( + f"Runtime error encountered while checking objects intersections: {e}" + ) + + return True diff --git a/env_manager/env_manager/env_manager/utils/__init__.py b/env_manager/env_manager/env_manager/utils/__init__.py new file mode 100644 index 0000000..88b3cc1 --- /dev/null +++ b/env_manager/env_manager/env_manager/utils/__init__.py @@ -0,0 +1,4 @@ +from . import conversions, gazebo, logging, math, types +from .tf2_broadcaster import Tf2Broadcaster, Tf2BroadcasterStandalone +from .tf2_dynamic_broadcaster import Tf2DynamicBroadcaster +from .tf2_listener import Tf2Listener, Tf2ListenerStandalone diff --git a/env_manager/env_manager/env_manager/utils/conversions.py b/env_manager/env_manager/env_manager/utils/conversions.py new file mode 100644 index 0000000..064c33d --- /dev/null +++ b/env_manager/env_manager/env_manager/utils/conversions.py @@ -0,0 +1,182 @@ +from typing import Tuple, Union + +import numpy +# import open3d +# import pyoctree +import sensor_msgs +from scipy.spatial.transform import Rotation + +# from sensor_msgs.msg import PointCloud2 +# from open3d.geometry import PointCloud +from geometry_msgs.msg import Transform + + +# def pointcloud2_to_open3d( +# ros_point_cloud2: PointCloud2, +# include_color: bool = False, +# include_intensity: bool = False, +# # Note: Order does not matter for DL, that's why channel swapping is disabled by default +# fix_rgb_channel_order: bool = False, +# ) -> PointCloud: +# +# # Create output Open3D PointCloud +# open3d_pc = PointCloud() +# +# size = ros_point_cloud2.width * ros_point_cloud2.height +# xyz_dtype = ">f4" if ros_point_cloud2.is_bigendian else " 3: +# bgr = numpy.ndarray( +# shape=(size, 3), +# dtype=numpy.uint8, +# buffer=ros_point_cloud2.data, +# offset=ros_point_cloud2.fields[3].offset, +# strides=(ros_point_cloud2.point_step, 1), +# ) +# if fix_rgb_channel_order: +# # Swap channels to gain rgb (faster than `bgr[:, [2, 1, 0]]`) +# bgr[:, 0], bgr[:, 2] = bgr[:, 2], bgr[:, 0].copy() +# open3d_pc.colors = open3d.utility.Vector3dVector( +# (bgr[valid_points] / 255).astype(numpy.float64) +# ) +# else: +# open3d_pc.colors = open3d.utility.Vector3dVector( +# numpy.zeros((len(valid_points), 3), dtype=numpy.float64) +# ) +# # TODO: Update octree creator once L8 image format is supported in Ignition Gazebo +# # elif include_intensity: +# # # Faster approach, but only the first channel gets the intensity value (rest is 0) +# # intensities = numpy.zeros((len(valid_points), 3), dtype=numpy.float64) +# # intensities[:, [0]] = ( +# # numpy.ndarray( +# # shape=(size, 1), +# # dtype=numpy.uint8, +# # buffer=ros_point_cloud2.data, +# # offset=ros_point_cloud2.fields[3].offset, +# # strides=(ros_point_cloud2.point_step, 1), +# # )[valid_points] +# # / 255 +# # ).astype(numpy.float64) +# # open3d_pc.colors = open3d.utility.Vector3dVector(intensities) +# # # # Slower approach, but all channels get the intensity value +# # # intensities = numpy.ndarray( +# # # shape=(size, 1), +# # # dtype=numpy.uint8, +# # # buffer=ros_point_cloud2.data, +# # # offset=ros_point_cloud2.fields[3].offset, +# # # strides=(ros_point_cloud2.point_step, 1), +# # # ) +# # # open3d_pc.colors = open3d.utility.Vector3dVector( +# # # numpy.tile(intensities[valid_points] / 255, (1, 3)).astype(numpy.float64) +# # # ) +# +# # Return the converted Open3D PointCloud +# return open3d_pc + + +def transform_to_matrix(transform: Transform) -> numpy.ndarray: + + transform_matrix = numpy.zeros((4, 4)) + transform_matrix[3, 3] = 1.0 + + transform_matrix[0:3, 0:3] = open3d.geometry.get_rotation_matrix_from_quaternion( + [ + transform.rotation.w, + transform.rotation.x, + transform.rotation.y, + transform.rotation.z, + ] + ) + transform_matrix[0, 3] = transform.translation.x + transform_matrix[1, 3] = transform.translation.y + transform_matrix[2, 3] = transform.translation.z + + return transform_matrix + + +# def open3d_point_cloud_to_octree_points( +# open3d_point_cloud: PointCloud, +# include_color: bool = False, +# include_intensity: bool = False, +# ) -> pyoctree.Points: +# +# octree_points = pyoctree.Points() +# +# if include_color: +# features = numpy.reshape(numpy.asarray(open3d_point_cloud.colors), -1) +# elif include_intensity: +# features = numpy.asarray(open3d_point_cloud.colors)[:, 0] +# else: +# features = [] +# +# octree_points.set_points( +# # XYZ points +# numpy.reshape(numpy.asarray(open3d_point_cloud.points), -1), +# # Normals +# numpy.reshape(numpy.asarray(open3d_point_cloud.normals), -1), +# # Other features, e.g. color +# features, +# # Labels - not used +# [], +# ) +# +# return octree_points + + +def orientation_6d_to_quat( + v1: Tuple[float, float, float], v2: Tuple[float, float, float] +) -> Tuple[float, float, float, float]: + + # Normalize vectors + col1 = v1 / numpy.linalg.norm(v1) + col2 = v2 / numpy.linalg.norm(v2) + + # Find their orthogonal vector via cross product + col3 = numpy.cross(col1, col2) + + # Stack into rotation matrix as columns, convert to quaternion and return + quat_xyzw = Rotation.from_matrix(numpy.array([col1, col2, col3]).T).as_quat() + return quat_xyzw + + +def orientation_quat_to_6d( + quat_xyzw: Tuple[float, float, float, float] +) -> Tuple[Tuple[float, float, float], Tuple[float, float, float]]: + + # Convert quaternion into rotation matrix + rot_mat = Rotation.from_quat(quat_xyzw).as_matrix() + + # Return first two columns (already normalised) + return (tuple(rot_mat[:, 0]), tuple(rot_mat[:, 1])) + + +def quat_to_wxyz( + xyzw: tuple[float, float, float, float] +) -> tuple[float, float, float, float]: + + return (xyzw[3], xyzw[0], xyzw[1], xyzw[2]) + + # return xyzw[[3, 0, 1, 2]] + + +def quat_to_xyzw( + wxyz: Union[numpy.ndarray, Tuple[float, float, float, float]] +) -> numpy.ndarray: + + if isinstance(wxyz, tuple): + return (wxyz[1], wxyz[2], wxyz[3], wxyz[0]) + + return wxyz[[1, 2, 3, 0]] diff --git a/env_manager/env_manager/env_manager/utils/gazebo.py b/env_manager/env_manager/env_manager/utils/gazebo.py new file mode 100644 index 0000000..2786de8 --- /dev/null +++ b/env_manager/env_manager/env_manager/utils/gazebo.py @@ -0,0 +1,262 @@ +from typing import Tuple, Union + +from gym_gz.scenario.model_wrapper import ModelWrapper +from numpy import exp +from scenario.bindings.core import Link, World +from scipy.spatial.transform import Rotation + +from .conversions import quat_to_wxyz, quat_to_xyzw +from .math import quat_mul +from .types import Pose, Point, Quat + + +#NOTE: Errors in pyright will be fixed only with pybind11 in the scenario module +def get_model_pose( + world: World, + model: ModelWrapper | str, + link: Link | str | None = None, + xyzw: bool = False, +) -> Pose: + """ + Return pose of model's link. Orientation is represented as wxyz quaternion or xyzw based on the passed argument `xyzw`. + """ + + if isinstance(model, str): + # Get reference to the model from its name if string is passed + model = world.to_gazebo().get_model(model).to_gazebo() + + if link is None: + # Use the first link if not specified + link = model.get_link(link_name=model.link_names()[0]) + elif isinstance(link, str): + # Get reference to the link from its name if string + link = model.get_link(link_name=link) + + # Get position and orientation + position = link.position() + quat = link.orientation() + + # Convert to xyzw order if desired + if xyzw: + quat = quat_to_xyzw(quat) + + # Return pose of the model's link + return ( + position, + quat, + ) + + +def get_model_position( + world: World, + model: ModelWrapper | str, + link: Link | str | None = None, +) -> Point: + """ + Return position of model's link. + """ + + if isinstance(model, str): + # Get reference to the model from its name if string is passed + model = world.to_gazebo().get_model(model).to_gazebo() + + if link is None: + # Use the first link if not specified + link = model.get_link(link_name=model.link_names()[0]) + elif isinstance(link, str): + # Get reference to the link from its name if string + link = model.get_link(link_name=link) + + # Return position of the model's link + return link.position() + + +def get_model_orientation( + world: World, + model: ModelWrapper | str, + link: Link | str | None = None, + xyzw: bool = False, +) -> Quat: + """ + Return orientation of model's link that is represented as wxyz quaternion or xyzw based on the passed argument `xyzw`. + """ + + if isinstance(model, str): + # Get reference to the model from its name if string is passed + model = world.to_gazebo().get_model(model).to_gazebo() + + if link is None: + # Use the first link if not specified + link = model.get_link(link_name=model.link_names()[0]) + elif isinstance(link, str): + # Get reference to the link from its name if string + link = model.get_link(link_name=link) + + # Get orientation + quat = link.orientation() + + # Convert to xyzw order if desired + if xyzw: + quat = quat_to_xyzw(quat) + + # Return orientation of the model's link + return quat + + +def transform_move_to_model_pose( + world: World, + position: Point, + quat: Quat, + target_model: ModelWrapper | str, + target_link: Link | str | None = None, + xyzw: bool = False, +) -> Pose: + """ + Transform such that original `position` and `quat` are represented with respect to `target_model::target_link`. + The resulting pose is still represented in world coordinate system. + """ + + target_frame_position, target_frame_quat = get_model_pose( + world, + model=target_model, + link=target_link, + xyzw=True, + ) + + transformed_position = Rotation.from_quat(target_frame_quat).apply(position) + transformed_position = ( + transformed_position[0] + target_frame_position[0], + transformed_position[1] + target_frame_position[1], + transformed_position[2] + target_frame_position[2], + ) + + if not xyzw: + target_frame_quat = quat_to_wxyz(target_frame_quat) + transformed_quat = quat_mul(quat, target_frame_quat, xyzw=xyzw) + + return (transformed_position, transformed_quat) + + +def transform_move_to_model_position( + world: World, + position: Point, + target_model: ModelWrapper | str, + target_link: Link | str | None = None, +) -> Point: + + target_frame_position, target_frame_quat_xyzw = get_model_pose( + world, + model=target_model, + link=target_link, + xyzw=True, + ) + + transformed_position = Rotation.from_quat(target_frame_quat_xyzw).apply(position) + transformed_position = ( + target_frame_position[0] + transformed_position[0], + target_frame_position[1] + transformed_position[1], + target_frame_position[2] + transformed_position[2], + ) + + return transformed_position + + +def transform_move_to_model_orientation( + world: World, + quat: Quat, + target_model: ModelWrapper | str, + target_link: Link | str | None = None, + xyzw: bool = False, +) -> Quat: + + target_frame_quat = get_model_orientation( + world, + model=target_model, + link=target_link, + xyzw=xyzw, + ) + + transformed_quat = quat_mul(quat, target_frame_quat, xyzw=xyzw) + + return transformed_quat + + +def transform_change_reference_frame_pose( + world: World, + position: Point, + quat: Quat, + target_model: ModelWrapper | str, + target_link: Link | str | None, + xyzw: bool = False, +) -> Pose: + """ + Change reference frame of original `position` and `quat` from world coordinate system to `target_model::target_link` coordinate system. + """ + + target_frame_position, target_frame_quat = get_model_pose( + world, + model=target_model, + link=target_link, + xyzw=True, + ) + + transformed_position = ( + position[0] - target_frame_position[0], + position[1] - target_frame_position[1], + position[2] - target_frame_position[2], + ) + transformed_position = Rotation.from_quat(target_frame_quat).apply( + transformed_position, inverse=True + ) + + if not xyzw: + target_frame_quat = quat_to_wxyz(target_frame_quat) + transformed_quat = quat_mul(target_frame_quat, quat, xyzw=xyzw) + + return (tuple(transformed_position), transformed_quat) + + +def transform_change_reference_frame_position( + world: World, + position: Point, + target_model: ModelWrapper | str, + target_link: Link | str | None = None, +) -> Point: + + target_frame_position, target_frame_quat_xyzw = get_model_pose( + world, + model=target_model, + link=target_link, + xyzw=True, + ) + + transformed_position = ( + position[0] - target_frame_position[0], + position[1] - target_frame_position[1], + position[2] - target_frame_position[2], + ) + transformed_position = Rotation.from_quat(target_frame_quat_xyzw).apply( + transformed_position, inverse=True + ) + + return tuple(transformed_position) + + +def transform_change_reference_frame_orientation( + world: World, + quat: Quat, + target_model: ModelWrapper | str, + target_link: Link | str | None = None, + xyzw: bool = False, +) -> Quat: + + target_frame_quat = get_model_orientation( + world, + model=target_model, + link=target_link, + xyzw=xyzw, + ) + + transformed_quat = quat_mul(target_frame_quat, quat, xyzw=xyzw) + + return transformed_quat diff --git a/env_manager/env_manager/env_manager/utils/helper.py b/env_manager/env_manager/env_manager/utils/helper.py new file mode 100644 index 0000000..a5bfd08 --- /dev/null +++ b/env_manager/env_manager/env_manager/utils/helper.py @@ -0,0 +1,488 @@ +import numpy as np +from gym_gz.scenario.model_wrapper import ModelWrapper +from rclpy.node import Node +from scenario.bindings.core import World +from scipy.spatial.transform import Rotation + +from .conversions import orientation_6d_to_quat +from .gazebo import ( + get_model_orientation, + get_model_pose, + get_model_position, + transform_change_reference_frame_orientation, + transform_change_reference_frame_pose, + transform_change_reference_frame_position, +) +from .math import quat_mul +from .tf2_listener import Tf2Listener +from .types import Point, Pose, PoseRpy, Quat, Rpy + + +# Helper functions # +def get_relative_ee_position(self, translation: Point) -> Point: + # Scale relative action to metric units + translation = self.scale_relative_translation(translation) + # Get current position + current_position = self.get_ee_position() + # Compute target position + target_position = ( + current_position[0] + translation[0], + current_position[1] + translation[1], + current_position[2] + translation[2], + ) + + # Restrict target position to a limited workspace, if desired + if self._restrict_position_goal_to_workspace: + target_position = self.restrict_position_goal_to_workspace(target_position) + + return target_position + + +def get_relative_ee_orientation( + self, + rotation: float | Quat | PoseRpy, + representation: str = "quat", +) -> Quat: + current_quat_xyzw = self.get_ee_orientation() + + if representation == "z": + current_yaw = Rotation.from_quat(current_quat_xyzw).as_euler("xyz")[2] + current_quat_xyzw = Rotation.from_euler( + "xyz", [np.pi, 0, current_yaw] + ).as_quat() + + if isinstance(rotation, tuple): + if len(rotation) == 4 and representation == "quat": + relative_quat_xyzw = rotation + elif len(rotation) == 6 and representation == "6d": + vectors = (rotation[0:3], rotation[3:6]) + relative_quat_xyzw = orientation_6d_to_quat(vectors[0], vectors[1]) + else: + raise ValueError("Invalid rotation tuple length for representation.") + elif isinstance(rotation, float) and representation == "z": + rotation = self.scale_relative_rotation(rotation) + relative_quat_xyzw = Rotation.from_euler("xyz", [0, 0, rotation]).as_quat() + else: + raise TypeError("Invalid type for rotation or representation.") + + target_quat_xyzw = quat_mul(tuple(current_quat_xyzw), tuple(relative_quat_xyzw)) + + target_quat_xyzw = normalize_quaternion(tuple(relative_quat_xyzw)) + + return target_quat_xyzw + + +def normalize_quaternion( + target_quat_xyzw: tuple[float, float, float, float], +) -> tuple[float, float, float, float]: + quat_array = np.array(target_quat_xyzw) + normalized_quat = quat_array / np.linalg.norm(quat_array) + return tuple(normalized_quat) + + +def scale_relative_translation(self, translation: Point) -> Point: + return ( + self.__scaling_factor_translation * translation[0], + self.__scaling_factor_translation * translation[1], + self.__scaling_factor_translation * translation[2], + ) + + +def scale_relative_rotation( + self, rotation: float | Rpy | np.floating | np.ndarray +) -> float | Rpy: + scaling_factor = self.__scaling_factor_rotation + + if isinstance(rotation, (int, float, np.floating)): + return scaling_factor * rotation + + return tuple(scaling_factor * r for r in rotation) + + +def restrict_position_goal_to_workspace(self, position: Point) -> Point: + return ( + min( + self.workspace_max_bound[0], + max( + self.workspace_min_bound[0], + position[0], + ), + ), + min( + self.workspace_max_bound[1], + max( + self.workspace_min_bound[1], + position[1], + ), + ), + min( + self.workspace_max_bound[2], + max( + self.workspace_min_bound[2], + position[2], + ), + ), + ) + + +# def restrict_servo_translation_to_workspace( +# self, translation: tuple[float, float, float] +# ) -> tuple[float, float, float]: +# current_ee_position = self.get_ee_position() +# +# translation = tuple( +# 0.0 +# if ( +# current_ee_position[i] > self.workspace_max_bound[i] +# and translation[i] > 0.0 +# ) +# or ( +# current_ee_position[i] < self.workspace_min_bound[i] +# and translation[i] < 0.0 +# ) +# else translation[i] +# for i in range(3) +# ) +# +# return translation + + +def get_ee_pose( + node: Node, + world: World, + robot_ee_link_name: str, + robot_name: str, + robot_arm_base_link_name: str, + tf2_listener: Tf2Listener, +) -> Pose | None: + """ + Return the current pose of the end effector with respect to arm base link. + """ + + try: + robot_model = world.to_gazebo().get_model(robot_name).to_gazebo() + ee_position, ee_quat_xyzw = get_model_pose( + world=world, + model=robot_model, + link=robot_ee_link_name, + xyzw=True, + ) + return transform_change_reference_frame_pose( + world=world, + position=ee_position, + quat=ee_quat_xyzw, + target_model=robot_model, + target_link=robot_arm_base_link_name, + xyzw=True, + ) + except Exception as e: + node.get_logger().warn( + f"Cannot get end effector pose from Gazebo ({e}), using tf2..." + ) + transform = tf2_listener.lookup_transform_sync( + source_frame=robot_ee_link_name, + target_frame=robot_arm_base_link_name, + retry=False, + ) + if transform is not None: + return ( + ( + transform.translation.x, + transform.translation.y, + transform.translation.z, + ), + ( + transform.rotation.x, + transform.rotation.y, + transform.rotation.z, + transform.rotation.w, + ), + ) + else: + node.get_logger().error( + "Cannot get pose of the end effector (default values are returned)" + ) + return ( + (0.0, 0.0, 0.0), + (0.0, 0.0, 0.0, 1.0), + ) + + +def get_ee_position( + world: World, + robot_name: str, + robot_ee_link_name: str, + robot_arm_base_link_name: str, + node: Node, + tf2_listener: Tf2Listener, +) -> Point: + """ + Return the current position of the end effector with respect to arm base link. + """ + + try: + robot_model = world.to_gazebo().get_model(robot_name).to_gazebo() + ee_position = get_model_position( + world=world, + model=robot_model, + link=robot_ee_link_name, + ) + return transform_change_reference_frame_position( + world=world, + position=ee_position, + target_model=robot_model, + target_link=robot_arm_base_link_name, + ) + except Exception as e: + node.get_logger().debug( + f"Cannot get end effector position from Gazebo ({e}), using tf2..." + ) + transform = tf2_listener.lookup_transform_sync( + source_frame=robot_ee_link_name, + target_frame=robot_arm_base_link_name, + retry=False, + ) + if transform is not None: + return ( + transform.translation.x, + transform.translation.y, + transform.translation.z, + ) + else: + node.get_logger().error( + "Cannot get position of the end effector (default values are returned)" + ) + return (0.0, 0.0, 0.0) + + +def get_ee_orientation( + world: World, + robot_name: str, + robot_ee_link_name: str, + robot_arm_base_link_name: str, + node: Node, + tf2_listener: Tf2Listener, +) -> Quat: + """ + Return the current xyzw quaternion of the end effector with respect to arm base link. + """ + + try: + robot_model = world.to_gazebo().get_model(robot_name).to_gazebo() + ee_quat_xyzw = get_model_orientation( + world=world, + model=robot_model, + link=robot_ee_link_name, + xyzw=True, + ) + return transform_change_reference_frame_orientation( + world=world, + quat=ee_quat_xyzw, + target_model=robot_model, + target_link=robot_arm_base_link_name, + xyzw=True, + ) + except Exception as e: + node.get_logger().warn( + f"Cannot get end effector orientation from Gazebo ({e}), using tf2..." + ) + transform = tf2_listener.lookup_transform_sync( + source_frame=robot_ee_link_name, + target_frame=robot_arm_base_link_name, + retry=False, + ) + if transform is not None: + return ( + transform.rotation.x, + transform.rotation.y, + transform.rotation.z, + transform.rotation.w, + ) + else: + node.get_logger().error( + "Cannot get orientation of the end effector (default values are returned)" + ) + return (0.0, 0.0, 0.0, 1.0) + + +def get_object_position( + object_model: ModelWrapper | str, + node: Node, + world: World, + robot_name: str, + robot_arm_base_link_name: str, +) -> Point: + """ + Return the current position of an object with respect to arm base link. + Note: Only simulated objects are currently supported. + """ + + try: + object_position = get_model_position( + world=world, + model=object_model, + ) + return transform_change_reference_frame_position( + world=world, + position=object_position, + target_model=robot_name, + target_link=robot_arm_base_link_name, + ) + except Exception as e: + node.get_logger().error( + f"Cannot get position of {object_model} object (default values are returned): {e}" + ) + return (0.0, 0.0, 0.0) + + +def get_object_positions( + node: Node, + world: World, + object_names: list[str], + robot_name: str, + robot_arm_base_link_name: str, +) -> dict[str, tuple[float, float, float]]: + """ + Return the current position of all objects with respect to arm base link. + Note: Only simulated objects are currently supported. + """ + + object_positions = {} + + try: + robot_model = world.to_gazebo().get_model(robot_name).to_gazebo() + robot_arm_base_link = robot_model.get_link(link_name=robot_arm_base_link_name) + for object_name in object_names: + object_position = get_model_position( + world=world, + model=object_name, + ) + object_positions[object_name] = transform_change_reference_frame_position( + world=world, + position=object_position, + target_model=robot_model, + target_link=robot_arm_base_link, + ) + except Exception as e: + node.get_logger().error( + f"Cannot get positions of all objects (empty Dict is returned): {e}" + ) + + return object_positions + + +# def substitute_special_frame(self, frame_id: str) -> str: +# if "arm_base_link" == frame_id: +# return self.robot_arm_base_link_name +# elif "base_link" == frame_id: +# return self.robot_base_link_name +# elif "end_effector" == frame_id: +# return self.robot_ee_link_name +# elif "world" == frame_id: +# try: +# # In Gazebo, where multiple worlds are allowed +# return self.world.to_gazebo().name() +# except Exception as e: +# self.get_logger().warn(f"") +# # Otherwise (e.g. real world) +# return "rbs_gym_world" +# else: +# return frame_id + + +def move_to_initial_joint_configuration(self): + pass + + # self.moveit2.move_to_configuration(self.initial_arm_joint_positions) + + # if ( + # self.robot_model_class.CLOSED_GRIPPER_JOINT_POSITIONS + # == self.initial_gripper_joint_positions + # ): + # self.gripper.reset_close() + # else: + # self.gripper.reset_open() + + +def check_terrain_collision( + world: World, + robot_name: str, + terrain_name: str, + robot_base_link_name: str, + robot_arm_link_names: list[str], + robot_gripper_link_names: list[str], +) -> bool: + """ + Returns true if robot links are in collision with the ground. + """ + robot_name_len = len(robot_name) + terrain_model = world.get_model(terrain_name) + + for contact in terrain_model.contacts(): + body_b = contact.body_b + + if body_b.startswith(robot_name) and len(body_b) > robot_name_len: + link = body_b[robot_name_len + 2 :] + + if link != robot_base_link_name and ( + link in robot_arm_link_names or link in robot_gripper_link_names + ): + return True + + return False + + +def check_all_objects_outside_workspace( + workspace: Pose, + object_positions: dict[str, Point], +) -> bool: + """ + Returns True if all objects are outside the workspace. + """ + + return all( + [ + check_object_outside_workspace(workspace, object_position) + for object_position in object_positions.values() + ] + ) + + +def check_object_outside_workspace(workspace: Pose, object_position: Point) -> bool: + """ + Returns True if the object is outside the workspace. + """ + workspace_min_bound, workspace_max_bound = workspace + return any( + coord < min_bound or coord > max_bound + for coord, min_bound, max_bound in zip( + object_position, workspace_min_bound, workspace_max_bound + ) + ) + + +# def add_parameter_overrides(self, parameter_overrides: Dict[str, any]): +# self.add_task_parameter_overrides(parameter_overrides) +# self.add_randomizer_parameter_overrides(parameter_overrides) +# +# +# def add_task_parameter_overrides(self, parameter_overrides: Dict[str, any]): +# self.__task_parameter_overrides.update(parameter_overrides) +# +# +# def add_randomizer_parameter_overrides(self, parameter_overrides: Dict[str, any]): +# self._randomizer_parameter_overrides.update(parameter_overrides) +# +# +# def __consume_parameter_overrides(self): +# for key, value in self.__task_parameter_overrides.items(): +# if hasattr(self, key): +# setattr(self, key, value) +# elif hasattr(self, f"_{key}"): +# setattr(self, f"_{key}", value) +# elif hasattr(self, f"__{key}"): +# setattr(self, f"__{key}", value) +# else: +# self.get_logger().error(f"Override '{key}' is not supperted by the task.") +# +# self.__task_parameter_overrides.clear() diff --git a/env_manager/env_manager/env_manager/utils/logging.py b/env_manager/env_manager/env_manager/utils/logging.py new file mode 100644 index 0000000..e9b8c09 --- /dev/null +++ b/env_manager/env_manager/env_manager/utils/logging.py @@ -0,0 +1,25 @@ +from typing import Union + +from gymnasium import logger as gym_logger +from gym_gz.utils import logger as gym_ign_logger + + +def set_log_level(log_level: Union[int, str]): + """ + Set log level for (Gym) Ignition. + """ + + if not isinstance(log_level, int): + log_level = str(log_level).upper() + + if "WARNING" == log_level: + log_level = "WARN" + elif not log_level in ["DEBUG", "INFO", "WARN", "ERROR", "DISABLED"]: + log_level = "DISABLED" + + log_level = getattr(gym_logger, log_level) + + gym_ign_logger.set_level( + level=log_level, + scenario_level=log_level, + ) diff --git a/env_manager/env_manager/env_manager/utils/math.py b/env_manager/env_manager/env_manager/utils/math.py new file mode 100644 index 0000000..291cdf5 --- /dev/null +++ b/env_manager/env_manager/env_manager/utils/math.py @@ -0,0 +1,44 @@ +import numpy as np + + +def quat_mul( + quat_0: tuple[float, float, float, float], + quat_1: tuple[float, float, float, float], + xyzw: bool = True, +) -> tuple[float, float, float, float]: + """ + Multiply two quaternions + """ + if xyzw: + x0, y0, z0, w0 = quat_0 + x1, y1, z1, w1 = quat_1 + return ( + x1 * w0 + y1 * z0 - z1 * y0 + w1 * x0, + -x1 * z0 + y1 * w0 + z1 * x0 + w1 * y0, + x1 * y0 - y1 * x0 + z1 * w0 + w1 * z0, + -x1 * x0 - y1 * y0 - z1 * z0 + w1 * w0, + ) + else: + w0, x0, y0, z0 = quat_0 + w1, x1, y1, z1 = quat_1 + return ( + -x1 * x0 - y1 * y0 - z1 * z0 + w1 * w0, + x1 * w0 + y1 * z0 - z1 * y0 + w1 * x0, + -x1 * z0 + y1 * w0 + z1 * x0 + w1 * y0, + x1 * y0 - y1 * x0 + z1 * w0 + w1 * z0, + ) + + +def distance_to_nearest_point( + origin: tuple[float, float, float], points: list[tuple[float, float, float]] +) -> float: + + return np.linalg.norm(np.array(points) - np.array(origin), axis=1).min() + + +def get_nearest_point( + origin: tuple[float, float, float], points: list[tuple[float, float, float]] +) -> tuple[float, float, float]: + + target_distances = np.linalg.norm(np.array(points) - np.array(origin), axis=1) + return points[target_distances.argmin()] diff --git a/env_manager/env_manager/env_manager/utils/tf2_broadcaster.py b/env_manager/env_manager/env_manager/utils/tf2_broadcaster.py new file mode 100644 index 0000000..27fb52a --- /dev/null +++ b/env_manager/env_manager/env_manager/utils/tf2_broadcaster.py @@ -0,0 +1,74 @@ +import sys +from typing import Tuple + +import rclpy +from geometry_msgs.msg import TransformStamped +from rclpy.node import Node +from rclpy.parameter import Parameter +from tf2_ros import StaticTransformBroadcaster + + +class Tf2Broadcaster: + def __init__( + self, + node: Node, + ): + + self._node = node + self.__tf2_broadcaster = StaticTransformBroadcaster(node=self._node) + self._transform_stamped = TransformStamped() + + def broadcast_tf( + self, + parent_frame_id: str, + child_frame_id: str, + translation: Tuple[float, float, float], + rotation: Tuple[float, float, float, float], + xyzw: bool = True, + ): + """ + Broadcast transformation of the camera + """ + + self._transform_stamped.header.frame_id = parent_frame_id + self._transform_stamped.child_frame_id = child_frame_id + + self._transform_stamped.header.stamp = self._node.get_clock().now().to_msg() + + self._transform_stamped.transform.translation.x = float(translation[0]) + self._transform_stamped.transform.translation.y = float(translation[1]) + self._transform_stamped.transform.translation.z = float(translation[2]) + + if xyzw: + self._transform_stamped.transform.rotation.x = float(rotation[0]) + self._transform_stamped.transform.rotation.y = float(rotation[1]) + self._transform_stamped.transform.rotation.z = float(rotation[2]) + self._transform_stamped.transform.rotation.w = float(rotation[3]) + else: + self._transform_stamped.transform.rotation.w = float(rotation[0]) + self._transform_stamped.transform.rotation.x = float(rotation[1]) + self._transform_stamped.transform.rotation.y = float(rotation[2]) + self._transform_stamped.transform.rotation.z = float(rotation[3]) + + self.__tf2_broadcaster.sendTransform(self._transform_stamped) + + +class Tf2BroadcasterStandalone(Node, Tf2Broadcaster): + def __init__( + self, + node_name: str = "env_manager_tf_broadcaster", + use_sim_time: bool = True, + ): + + try: + rclpy.init() + except Exception as e: + if not rclpy.ok(): + sys.exit(f"ROS 2 context could not be initialised: {e}") + + Node.__init__(self, node_name) + self.set_parameters( + [Parameter("use_sim_time", type_=Parameter.Type.BOOL, value=use_sim_time)] + ) + + Tf2Broadcaster.__init__(self, node=self) diff --git a/env_manager/env_manager/env_manager/utils/tf2_dynamic_broadcaster.py b/env_manager/env_manager/env_manager/utils/tf2_dynamic_broadcaster.py new file mode 100644 index 0000000..4737754 --- /dev/null +++ b/env_manager/env_manager/env_manager/utils/tf2_dynamic_broadcaster.py @@ -0,0 +1,74 @@ +import sys +from typing import Tuple + +import rclpy +from geometry_msgs.msg import TransformStamped +from rclpy.node import Node +from rclpy.parameter import Parameter +from tf2_ros import TransformBroadcaster + + +class Tf2DynamicBroadcaster: + def __init__( + self, + node: Node, + ): + + self._node = node + self.__tf2_broadcaster = TransformBroadcaster(node=self._node) + self._transform_stamped = TransformStamped() + + def broadcast_tf( + self, + parent_frame_id: str, + child_frame_id: str, + translation: Tuple[float, float, float], + rotation: Tuple[float, float, float, float], + xyzw: bool = True, + ): + """ + Broadcast transformation of the camera + """ + + self._transform_stamped.header.frame_id = parent_frame_id + self._transform_stamped.child_frame_id = child_frame_id + + self._transform_stamped.header.stamp = self._node.get_clock().now().to_msg() + + self._transform_stamped.transform.translation.x = float(translation[0]) + self._transform_stamped.transform.translation.y = float(translation[1]) + self._transform_stamped.transform.translation.z = float(translation[2]) + + if xyzw: + self._transform_stamped.transform.rotation.x = float(rotation[0]) + self._transform_stamped.transform.rotation.y = float(rotation[1]) + self._transform_stamped.transform.rotation.z = float(rotation[2]) + self._transform_stamped.transform.rotation.w = float(rotation[3]) + else: + self._transform_stamped.transform.rotation.w = float(rotation[0]) + self._transform_stamped.transform.rotation.x = float(rotation[1]) + self._transform_stamped.transform.rotation.y = float(rotation[2]) + self._transform_stamped.transform.rotation.z = float(rotation[3]) + + self.__tf2_broadcaster.sendTransform(self._transform_stamped) + + +class Tf2BroadcasterStandalone(Node, Tf2DynamicBroadcaster): + def __init__( + self, + node_name: str = "env_manager_tf_broadcaster", + use_sim_time: bool = True, + ): + + try: + rclpy.init() + except Exception as e: + if not rclpy.ok(): + sys.exit(f"ROS 2 context could not be initialised: {e}") + + Node.__init__(self, node_name) + self.set_parameters( + [Parameter("use_sim_time", type_=Parameter.Type.BOOL, value=use_sim_time)] + ) + + Tf2DynamicBroadcaster.__init__(self, node=self) diff --git a/env_manager/env_manager/env_manager/utils/tf2_listener.py b/env_manager/env_manager/env_manager/utils/tf2_listener.py new file mode 100644 index 0000000..ef22bb0 --- /dev/null +++ b/env_manager/env_manager/env_manager/utils/tf2_listener.py @@ -0,0 +1,74 @@ +import sys +from typing import Optional + +import rclpy +from geometry_msgs.msg import Transform +from rclpy.node import Node +from rclpy.parameter import Parameter +from tf2_ros import Buffer, TransformListener + + +class Tf2Listener: + def __init__( + self, + node: Node, + ): + + self._node = node + + # Create tf2 buffer and listener for transform lookup + self.__tf2_buffer = Buffer() + TransformListener(buffer=self.__tf2_buffer, node=node) + + def lookup_transform_sync( + self, target_frame: str, source_frame: str, retry: bool = True + ) -> Optional[Transform]: + + try: + return self.__tf2_buffer.lookup_transform( + target_frame=target_frame, + source_frame=source_frame, + time=rclpy.time.Time(), + ).transform + except: + if retry: + while rclpy.ok(): + if self.__tf2_buffer.can_transform( + target_frame=target_frame, + source_frame=source_frame, + time=rclpy.time.Time(), + timeout=rclpy.time.Duration(seconds=1, nanoseconds=0), + ): + return self.__tf2_buffer.lookup_transform( + target_frame=target_frame, + source_frame=source_frame, + time=rclpy.time.Time(), + ).transform + + self._node.get_logger().warn( + f'Lookup of transform from "{source_frame}"' + f' to "{target_frame}" failed, retrying...' + ) + else: + return None + + +class Tf2ListenerStandalone(Node, Tf2Listener): + def __init__( + self, + node_name: str = "rbs_gym_tf_listener", + use_sim_time: bool = True, + ): + + try: + rclpy.init() + except Exception as e: + if not rclpy.ok(): + sys.exit(f"ROS 2 context could not be initialised: {e}") + + Node.__init__(self, node_name) + self.set_parameters( + [Parameter("use_sim_time", type_=Parameter.Type.BOOL, value=use_sim_time)] + ) + + Tf2Listener.__init__(self, node=self) diff --git a/env_manager/env_manager/env_manager/utils/types.py b/env_manager/env_manager/env_manager/utils/types.py new file mode 100644 index 0000000..a502bd6 --- /dev/null +++ b/env_manager/env_manager/env_manager/utils/types.py @@ -0,0 +1,5 @@ +Point = tuple[float, float, float] +Quat = tuple[float, float, float, float] +Rpy = tuple[float, float, float] +Pose = tuple[Point, Quat] +PoseRpy = tuple[Point, Rpy] diff --git a/env_manager/env_manager/package.nix b/env_manager/env_manager/package.nix new file mode 100644 index 0000000..d1c9250 --- /dev/null +++ b/env_manager/env_manager/package.nix @@ -0,0 +1,28 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license +{ + lib, + buildRosPackage, + ament-copyright, + ament-flake8, + ament-pep257, + gym-gz, + pythonPackages, + scenario +}: +buildRosPackage rec { + pname = "ros-jazzy-env-manager"; + version = "0.0.0"; + + src = ./.; + + buildType = "ament_python"; + checkInputs = [ament-copyright ament-flake8 ament-pep257 gym-gz pythonPackages.pytest scenario]; + propagatedBuildInputs = [ gym-gz ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [asl20]; + }; +} diff --git a/env_manager/env_manager/package.xml b/env_manager/env_manager/package.xml new file mode 100644 index 0000000..effa29f --- /dev/null +++ b/env_manager/env_manager/package.xml @@ -0,0 +1,21 @@ + + + + env_manager + 0.0.0 + TODO: Package description + narmak + Apache-2.0 + + + + + ament_copyright + ament_flake8 + ament_pep257 + python3-pytest + + + ament_python + + diff --git a/env_manager/env_manager/resource/env_manager b/env_manager/env_manager/resource/env_manager new file mode 100644 index 0000000..e69de29 diff --git a/env_manager/env_manager/setup.cfg b/env_manager/env_manager/setup.cfg new file mode 100644 index 0000000..36219d7 --- /dev/null +++ b/env_manager/env_manager/setup.cfg @@ -0,0 +1,4 @@ +[develop] +script_dir=$base/lib/env_manager +[install] +install_scripts=$base/lib/env_manager diff --git a/env_manager/env_manager/setup.py b/env_manager/env_manager/setup.py new file mode 100644 index 0000000..3e62b74 --- /dev/null +++ b/env_manager/env_manager/setup.py @@ -0,0 +1,25 @@ +from setuptools import find_packages, setup + +package_name = 'env_manager' + +setup( + name=package_name, + version='0.0.0', + packages=find_packages(exclude=['test']), + data_files=[ + ('share/ament_index/resource_index/packages', + ['resource/' + package_name]), + ('share/' + package_name, ['package.xml']), + ], + install_requires=['setuptools', 'trimesh'], + zip_safe=True, + maintainer='narmak', + maintainer_email='ur.narmak@gmail.com', + description='TODO: Package description', + license='Apache-2.0', + tests_require=['pytest'], + entry_points={ + 'console_scripts': [ + ], + }, +) diff --git a/env_manager/env_manager/test/test_copyright.py b/env_manager/env_manager/test/test_copyright.py new file mode 100644 index 0000000..97a3919 --- /dev/null +++ b/env_manager/env_manager/test/test_copyright.py @@ -0,0 +1,25 @@ +# Copyright 2015 Open Source Robotics Foundation, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from ament_copyright.main import main +import pytest + + +# Remove the `skip` decorator once the source file(s) have a copyright header +@pytest.mark.skip(reason='No copyright header has been placed in the generated source file.') +@pytest.mark.copyright +@pytest.mark.linter +def test_copyright(): + rc = main(argv=['.', 'test']) + assert rc == 0, 'Found errors' diff --git a/env_manager/env_manager/test/test_flake8.py b/env_manager/env_manager/test/test_flake8.py new file mode 100644 index 0000000..27ee107 --- /dev/null +++ b/env_manager/env_manager/test/test_flake8.py @@ -0,0 +1,25 @@ +# Copyright 2017 Open Source Robotics Foundation, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from ament_flake8.main import main_with_errors +import pytest + + +@pytest.mark.flake8 +@pytest.mark.linter +def test_flake8(): + rc, errors = main_with_errors(argv=[]) + assert rc == 0, \ + 'Found %d code style errors / warnings:\n' % len(errors) + \ + '\n'.join(errors) diff --git a/env_manager/env_manager/test/test_pep257.py b/env_manager/env_manager/test/test_pep257.py new file mode 100644 index 0000000..b234a38 --- /dev/null +++ b/env_manager/env_manager/test/test_pep257.py @@ -0,0 +1,23 @@ +# Copyright 2015 Open Source Robotics Foundation, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from ament_pep257.main import main +import pytest + + +@pytest.mark.linter +@pytest.mark.pep257 +def test_pep257(): + rc = main(argv=['.', 'test']) + assert rc == 0, 'Found code style errors / warnings' diff --git a/rbs_simulation/CMakeLists.txt b/env_manager/env_manager_interfaces/CMakeLists.txt similarity index 73% rename from rbs_simulation/CMakeLists.txt rename to env_manager/env_manager_interfaces/CMakeLists.txt index 6a9b3c9..a0a5c75 100644 --- a/rbs_simulation/CMakeLists.txt +++ b/env_manager/env_manager_interfaces/CMakeLists.txt @@ -1,5 +1,5 @@ cmake_minimum_required(VERSION 3.8) -project(rbs_simulation) +project(env_manager_interfaces) if(CMAKE_COMPILER_IS_GNUCXX OR CMAKE_CXX_COMPILER_ID MATCHES "Clang") add_compile_options(-Wall -Wextra -Wpedantic) @@ -7,17 +7,22 @@ endif() # find dependencies find_package(ament_cmake REQUIRED) +find_package(lifecycle_msgs REQUIRED) +find_package(rosidl_default_generators REQUIRED) # uncomment the following section in order to fill in # further dependencies manually. # find_package( REQUIRED) -install( - DIRECTORY launch worlds mujoco_model - DESTINATION share/${PROJECT_NAME} +rosidl_generate_interfaces(${PROJECT_NAME} + srv/StartEnv.srv + srv/ConfigureEnv.srv + srv/LoadEnv.srv + srv/UnloadEnv.srv + srv/ResetEnv.srv + msg/EnvState.msg + DEPENDENCIES lifecycle_msgs ) -add_subdirectory(models) - if(BUILD_TESTING) find_package(ament_lint_auto REQUIRED) # the following line skips the linter which checks for copyrights diff --git a/env_manager/env_manager_interfaces/LICENSE b/env_manager/env_manager_interfaces/LICENSE new file mode 100644 index 0000000..d645695 --- /dev/null +++ b/env_manager/env_manager_interfaces/LICENSE @@ -0,0 +1,202 @@ + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. 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In no event and under no legal theory, + whether in tort (including negligence), contract, or otherwise, + unless required by applicable law (such as deliberate and grossly + negligent acts) or agreed to in writing, shall any Contributor be + liable to You for damages, including any direct, indirect, special, + incidental, or consequential damages of any character arising as a + result of this License or out of the use or inability to use the + Work (including but not limited to damages for loss of goodwill, + work stoppage, computer failure or malfunction, or any and all + other commercial damages or losses), even if such Contributor + has been advised of the possibility of such damages. + + 9. Accepting Warranty or Additional Liability. While redistributing + the Work or Derivative Works thereof, You may choose to offer, + and charge a fee for, acceptance of support, warranty, indemnity, + or other liability obligations and/or rights consistent with this + License. However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + + APPENDIX: How to apply the Apache License to your work. + + To apply the Apache License to your work, attach the following + boilerplate notice, with the fields enclosed by brackets "[]" + replaced with your own identifying information. (Don't include + the brackets!) The text should be enclosed in the appropriate + comment syntax for the file format. We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/env_manager/env_manager_interfaces/msg/EnvState.msg b/env_manager/env_manager_interfaces/msg/EnvState.msg new file mode 100644 index 0000000..fa4c82e --- /dev/null +++ b/env_manager/env_manager_interfaces/msg/EnvState.msg @@ -0,0 +1,4 @@ +string name +string type +string plugin_name +lifecycle_msgs/State state diff --git a/env_manager/env_manager_interfaces/package.nix b/env_manager/env_manager_interfaces/package.nix new file mode 100644 index 0000000..3402f72 --- /dev/null +++ b/env_manager/env_manager_interfaces/package.nix @@ -0,0 +1,23 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 + +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license + +{ lib, buildRosPackage, ament-cmake, ament-lint-auto, ament-lint-common, builtin-interfaces, lifecycle-msgs, rosidl-default-generators, rosidl-default-runtime }: +buildRosPackage rec { + pname = "ros-jazzy-env-manager-interfaces"; + version = "0.0.0"; + + src = ./.; + + buildType = "ament_cmake"; + buildInputs = [ ament-cmake rosidl-default-generators ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ builtin-interfaces lifecycle-msgs rosidl-default-runtime ]; + nativeBuildInputs = [ ament-cmake rosidl-default-generators ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/env_manager/env_manager_interfaces/package.xml b/env_manager/env_manager_interfaces/package.xml new file mode 100644 index 0000000..4fb3920 --- /dev/null +++ b/env_manager/env_manager_interfaces/package.xml @@ -0,0 +1,27 @@ + + + + env_manager_interfaces + 0.0.0 + TODO: Package description + solid-sinusoid + Apache-2.0 + + ament_cmake + rosidl_default_generators + + builtin_interfaces + lifecycle_msgs + + builtin_interfaces + lifecycle_msgs + rosidl_default_runtime + + ament_lint_auto + ament_lint_common + + rosidl_interface_packages + + ament_cmake + + diff --git a/env_manager/env_manager_interfaces/srv/ConfigureEnv.srv b/env_manager/env_manager_interfaces/srv/ConfigureEnv.srv new file mode 100644 index 0000000..4292382 --- /dev/null +++ b/env_manager/env_manager_interfaces/srv/ConfigureEnv.srv @@ -0,0 +1,3 @@ +string name +--- +bool ok \ No newline at end of file diff --git a/env_manager/env_manager_interfaces/srv/LoadEnv.srv b/env_manager/env_manager_interfaces/srv/LoadEnv.srv new file mode 100644 index 0000000..d6d46cc --- /dev/null +++ b/env_manager/env_manager_interfaces/srv/LoadEnv.srv @@ -0,0 +1,4 @@ +string name +string type +--- +bool ok \ No newline at end of file diff --git a/env_manager/env_manager_interfaces/srv/ResetEnv.srv b/env_manager/env_manager_interfaces/srv/ResetEnv.srv new file mode 100644 index 0000000..5d0cbc4 --- /dev/null +++ b/env_manager/env_manager_interfaces/srv/ResetEnv.srv @@ -0,0 +1,3 @@ + +--- +bool ok diff --git a/env_manager/env_manager_interfaces/srv/StartEnv.srv b/env_manager/env_manager_interfaces/srv/StartEnv.srv new file mode 100644 index 0000000..d6d46cc --- /dev/null +++ b/env_manager/env_manager_interfaces/srv/StartEnv.srv @@ -0,0 +1,4 @@ +string name +string type +--- +bool ok \ No newline at end of file diff --git a/env_manager/env_manager_interfaces/srv/UnloadEnv.srv b/env_manager/env_manager_interfaces/srv/UnloadEnv.srv new file mode 100644 index 0000000..4292382 --- /dev/null +++ b/env_manager/env_manager_interfaces/srv/UnloadEnv.srv @@ -0,0 +1,3 @@ +string name +--- +bool ok \ No newline at end of file diff --git a/env_manager/rbs_gym/LICENSE b/env_manager/rbs_gym/LICENSE new file mode 100644 index 0000000..d645695 --- /dev/null +++ b/env_manager/rbs_gym/LICENSE @@ -0,0 +1,202 @@ + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. 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Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + copyright license to reproduce, prepare Derivative Works of, + publicly display, publicly perform, sublicense, and distribute the + Work and such Derivative Works in Source or Object form. + + 3. Grant of Patent License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + (except as stated in this section) patent license to make, have made, + use, offer to sell, sell, import, and otherwise transfer the Work, + where such license applies only to those patent claims licensable + by such Contributor that are necessarily infringed by their + Contribution(s) alone or by combination of their Contribution(s) + with the Work to which such Contribution(s) was submitted. If You + institute patent litigation against any entity (including a + cross-claim or counterclaim in a lawsuit) alleging that the Work + or a Contribution incorporated within the Work constitutes direct + or contributory patent infringement, then any patent licenses + granted to You under this License for that Work shall terminate + as of the date such litigation is filed. + + 4. Redistribution. You may reproduce and distribute copies of the + Work or Derivative Works thereof in any medium, with or without + modifications, and in Source or Object form, provided that You + meet the following conditions: + + (a) You must give any other recipients of the Work or + Derivative Works a copy of this License; and + + (b) You must cause any modified files to carry prominent notices + stating that You changed the files; and + + (c) You must retain, in the Source form of any Derivative Works + that You distribute, all copyright, patent, trademark, and + attribution notices from the Source form of the Work, + excluding those notices that do not pertain to any part of + the Derivative Works; and + + (d) If the Work includes a "NOTICE" text file as part of its + distribution, then any Derivative Works that You distribute must + include a readable copy of the attribution notices contained + within such NOTICE file, excluding those notices that do not + pertain to any part of the Derivative Works, in at least one + of the following places: within a NOTICE text file distributed + as part of the Derivative Works; within the Source form or + documentation, if provided along with the Derivative Works; or, + within a display generated by the Derivative Works, if and + wherever such third-party notices normally appear. The contents + of the NOTICE file are for informational purposes only and + do not modify the License. You may add Your own attribution + notices within Derivative Works that You distribute, alongside + or as an addendum to the NOTICE text from the Work, provided + that such additional attribution notices cannot be construed + as modifying the License. + + You may add Your own copyright statement to Your modifications and + may provide additional or different license terms and conditions + for use, reproduction, or distribution of Your modifications, or + for any such Derivative Works as a whole, provided Your use, + reproduction, and distribution of the Work otherwise complies with + the conditions stated in this License. + + 5. Submission of Contributions. Unless You explicitly state otherwise, + any Contribution intentionally submitted for inclusion in the Work + by You to the Licensor shall be under the terms and conditions of + this License, without any additional terms or conditions. + Notwithstanding the above, nothing herein shall supersede or modify + the terms of any separate license agreement you may have executed + with Licensor regarding such Contributions. + + 6. Trademarks. This License does not grant permission to use the trade + names, trademarks, service marks, or product names of the Licensor, + except as required for reasonable and customary use in describing the + origin of the Work and reproducing the content of the NOTICE file. + + 7. Disclaimer of Warranty. Unless required by applicable law or + agreed to in writing, Licensor provides the Work (and each + Contributor provides its Contributions) on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or + implied, including, without limitation, any warranties or conditions + of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A + PARTICULAR PURPOSE. You are solely responsible for determining the + appropriateness of using or redistributing the Work and assume any + risks associated with Your exercise of permissions under this License. + + 8. Limitation of Liability. In no event and under no legal theory, + whether in tort (including negligence), contract, or otherwise, + unless required by applicable law (such as deliberate and grossly + negligent acts) or agreed to in writing, shall any Contributor be + liable to You for damages, including any direct, indirect, special, + incidental, or consequential damages of any character arising as a + result of this License or out of the use or inability to use the + Work (including but not limited to damages for loss of goodwill, + work stoppage, computer failure or malfunction, or any and all + other commercial damages or losses), even if such Contributor + has been advised of the possibility of such damages. + + 9. Accepting Warranty or Additional Liability. While redistributing + the Work or Derivative Works thereof, You may choose to offer, + and charge a fee for, acceptance of support, warranty, indemnity, + or other liability obligations and/or rights consistent with this + License. However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + + APPENDIX: How to apply the Apache License to your work. + + To apply the Apache License to your work, attach the following + boilerplate notice, with the fields enclosed by brackets "[]" + replaced with your own identifying information. (Don't include + the brackets!) The text should be enclosed in the appropriate + comment syntax for the file format. We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/env_manager/rbs_gym/hyperparams/sac.yml b/env_manager/rbs_gym/hyperparams/sac.yml new file mode 100644 index 0000000..d372fc7 --- /dev/null +++ b/env_manager/rbs_gym/hyperparams/sac.yml @@ -0,0 +1,42 @@ +# Reach +Reach-Gazebo-v0: + policy: "MlpPolicy" + policy_kwargs: + n_critics: 2 + net_arch: [128, 64] + n_timesteps: 200000 + buffer_size: 25000 + learning_starts: 5000 + batch_size: 512 + learning_rate: lin_0.0002 + gamma: 0.95 + tau: 0.001 + ent_coef: "auto_0.1" + target_entropy: "auto" + train_freq: [1, "episode"] + gradient_steps: 100 + noise_type: "normal" + noise_std: 0.025 + use_sde: False + optimize_memory_usage: False + +Reach-ColorImage-Gazebo-v0: + policy: "CnnPolicy" + policy_kwargs: + n_critics: 2 + net_arch: [128, 128] + n_timesteps: 50000 + buffer_size: 25000 + learning_starts: 5000 + batch_size: 32 + learning_rate: lin_0.0002 + gamma: 0.95 + tau: 0.0005 + ent_coef: "auto_0.1" + target_entropy: "auto" + train_freq: [1, "episode"] + gradient_steps: 100 + noise_type: "normal" + noise_std: 0.025 + use_sde: False + optimize_memory_usage: False diff --git a/env_manager/rbs_gym/hyperparams/td3.yml b/env_manager/rbs_gym/hyperparams/td3.yml new file mode 100644 index 0000000..6f57e0a --- /dev/null +++ b/env_manager/rbs_gym/hyperparams/td3.yml @@ -0,0 +1,39 @@ +Reach-Gazebo-v0: + policy: "MlpPolicy" + policy_kwargs: + n_critics: 2 + net_arch: [128, 64] + n_timesteps: 200000 + buffer_size: 25000 + learning_starts: 5000 + batch_size: 512 + learning_rate: lin_0.0002 + gamma: 0.95 + tau: 0.001 + train_freq: [1, "episode"] + gradient_steps: 100 + target_policy_noise: 0.1 + target_noise_clip: 0.2 + noise_type: "normal" + noise_std: 0.025 + optimize_memory_usage: False + +Reach-ColorImage-Gazebo-v0: + policy: "CnnPolicy" + policy_kwargs: + n_critics: 2 + net_arch: [128, 128] + n_timesteps: 50000 + buffer_size: 25000 + learning_starts: 5000 + batch_size: 32 + learning_rate: lin_0.0002 + gamma: 0.95 + tau: 0.0005 + train_freq: [1, "episode"] + gradient_steps: 100 + target_policy_noise: 0.1 + target_noise_clip: 0.2 + noise_type: "normal" + noise_std: 0.025 + optimize_memory_usage: True diff --git a/env_manager/rbs_gym/hyperparams/tqc.yml b/env_manager/rbs_gym/hyperparams/tqc.yml new file mode 100644 index 0000000..7e483af --- /dev/null +++ b/env_manager/rbs_gym/hyperparams/tqc.yml @@ -0,0 +1,46 @@ +# Reach +Reach-Gazebo-v0: + policy: "MlpPolicy" + policy_kwargs: + n_quantiles: 25 + n_critics: 2 + net_arch: [128, 64] + n_timesteps: 200000 + buffer_size: 25000 + learning_starts: 5000 + batch_size: 512 + learning_rate: lin_0.0002 + gamma: 0.95 + tau: 0.001 + ent_coef: "auto_0.1" + target_entropy: "auto" + top_quantiles_to_drop_per_net: 2 + train_freq: [1, "episode"] + gradient_steps: 100 + noise_type: "normal" + noise_std: 0.025 + use_sde: False + optimize_memory_usage: False + +Reach-ColorImage-Gazebo-v0: + policy: "CnnPolicy" + policy_kwargs: + n_quantiles: 25 + n_critics: 2 + net_arch: [128, 128] + n_timesteps: 50000 + buffer_size: 25000 + learning_starts: 5000 + batch_size: 32 + learning_rate: lin_0.0002 + gamma: 0.95 + tau: 0.0005 + ent_coef: "auto_0.1" + target_entropy: "auto" + top_quantiles_to_drop_per_net: 2 + train_freq: [1, "episode"] + gradient_steps: 100 + noise_type: "normal" + noise_std: 0.025 + use_sde: False + optimize_memory_usage: True diff --git a/env_manager/rbs_gym/launch/evaluate.launch.py b/env_manager/rbs_gym/launch/evaluate.launch.py new file mode 100644 index 0000000..4e69f23 --- /dev/null +++ b/env_manager/rbs_gym/launch/evaluate.launch.py @@ -0,0 +1,426 @@ +from launch import LaunchContext, LaunchDescription +from launch.actions import ( + DeclareLaunchArgument, + IncludeLaunchDescription, + OpaqueFunction, + SetEnvironmentVariable, + TimerAction +) +from launch.launch_description_sources import PythonLaunchDescriptionSource +from launch.substitutions import LaunchConfiguration, PathJoinSubstitution +from launch_ros.substitutions import FindPackageShare +from launch_ros.actions import Node +import os +from os import cpu_count +from ament_index_python.packages import get_package_share_directory + +def launch_setup(context, *args, **kwargs): + # Initialize Arguments + robot_type = LaunchConfiguration("robot_type") + # General arguments + with_gripper_condition = LaunchConfiguration("with_gripper") + controllers_file = LaunchConfiguration("controllers_file") + cartesian_controllers = LaunchConfiguration("cartesian_controllers") + description_package = LaunchConfiguration("description_package") + description_file = LaunchConfiguration("description_file") + robot_name = LaunchConfiguration("robot_name") + start_joint_controller = LaunchConfiguration("start_joint_controller") + initial_joint_controller = LaunchConfiguration("initial_joint_controller") + launch_simulation = LaunchConfiguration("launch_sim") + launch_moveit = LaunchConfiguration("launch_moveit") + launch_task_planner = LaunchConfiguration("launch_task_planner") + launch_perception = LaunchConfiguration("launch_perception") + moveit_config_package = LaunchConfiguration("moveit_config_package") + moveit_config_file = LaunchConfiguration("moveit_config_file") + use_sim_time = LaunchConfiguration("use_sim_time") + sim_gazebo = LaunchConfiguration("sim_gazebo") + hardware = LaunchConfiguration("hardware") + env_manager = LaunchConfiguration("env_manager") + launch_controllers = LaunchConfiguration("launch_controllers") + gazebo_gui = LaunchConfiguration("gazebo_gui") + gripper_name = LaunchConfiguration("gripper_name") + + # training arguments + env = LaunchConfiguration("env") + algo = LaunchConfiguration("algo") + num_threads = LaunchConfiguration("num_threads") + seed = LaunchConfiguration("seed") + log_folder = LaunchConfiguration("log_folder") + verbose = LaunchConfiguration("verbose") + # use_sim_time = LaunchConfiguration("use_sim_time") + log_level = LaunchConfiguration("log_level") + env_kwargs = LaunchConfiguration("env_kwargs") + + n_episodes = LaunchConfiguration("n_episodes") + exp_id = LaunchConfiguration("exp_id") + load_best = LaunchConfiguration("load_best") + load_checkpoint = LaunchConfiguration("load_checkpoint") + stochastic = LaunchConfiguration("stochastic") + reward_log = LaunchConfiguration("reward_log") + norm_reward = LaunchConfiguration("norm_reward") + no_render = LaunchConfiguration("no_render") + + + sim_gazebo = LaunchConfiguration("sim_gazebo") + launch_simulation = LaunchConfiguration("launch_sim") + + initial_joint_controllers_file_path = os.path.join( + get_package_share_directory('rbs_arm'), 'config', 'controllers.yaml' + ) + + single_robot_setup = IncludeLaunchDescription( + PythonLaunchDescriptionSource([ + PathJoinSubstitution([ + FindPackageShare('rbs_bringup'), + "launch", + "rbs_robot.launch.py" + ]) + ]), + launch_arguments={ + "env_manager": env_manager, + "with_gripper": with_gripper_condition, + "gripper_name": gripper_name, + # "controllers_file": controllers_file, + "robot_type": robot_type, + "controllers_file": initial_joint_controllers_file_path, + "cartesian_controllers": cartesian_controllers, + "description_package": description_package, + "description_file": description_file, + "robot_name": robot_name, + "start_joint_controller": start_joint_controller, + "initial_joint_controller": initial_joint_controller, + "launch_simulation": launch_simulation, + "launch_moveit": launch_moveit, + "launch_task_planner": launch_task_planner, + "launch_perception": launch_perception, + "moveit_config_package": moveit_config_package, + "moveit_config_file": moveit_config_file, + "use_sim_time": use_sim_time, + "sim_gazebo": sim_gazebo, + "hardware": hardware, + "launch_controllers": launch_controllers, + # "gazebo_gui": gazebo_gui + }.items() + ) + + args = [ + "--env", + env, + "--env-kwargs", + env_kwargs, + "--algo", + algo, + "--seed", + seed, + "--num-threads", + num_threads, + "--n-episodes", + n_episodes, + "--log-folder", + log_folder, + "--exp-id", + exp_id, + "--load-best", + load_best, + "--load-checkpoint", + load_checkpoint, + "--stochastic", + stochastic, + "--reward-log", + reward_log, + "--norm-reward", + norm_reward, + "--no-render", + no_render, + "--verbose", + verbose, + "--ros-args", + "--log-level", + log_level, + ] + + rl_task = Node( + package="rbs_gym", + executable="evaluate", + output="log", + arguments=args, + parameters=[{"use_sim_time": use_sim_time}], + ) + + + + delay_robot_control_stack = TimerAction( + period=10.0, + actions=[single_robot_setup] + ) + + nodes_to_start = [ + # env, + rl_task, + delay_robot_control_stack + ] + return nodes_to_start + + +def generate_launch_description(): + declared_arguments = [] + declared_arguments.append( + DeclareLaunchArgument( + "robot_type", + description="Type of robot by name", + choices=["rbs_arm","ur3", "ur3e", "ur5", "ur5e", "ur10", "ur10e", "ur16e"], + default_value="rbs_arm", + ) + ) + # General arguments + declared_arguments.append( + DeclareLaunchArgument( + "controllers_file", + default_value="controllers_gazebosim.yaml", + description="YAML file with the controllers configuration.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "description_package", + default_value="rbs_arm", + description="Description package with robot URDF/XACRO files. Usually the argument \ + is not set, it enables use of a custom description.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "description_file", + default_value="rbs_arm_modular.xacro", + description="URDF/XACRO description file with the robot.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "robot_name", + default_value="arm0", + description="Name for robot, used to apply namespace for specific robot in multirobot setup", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "start_joint_controller", + default_value="false", + description="Enable headless mode for robot control", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "initial_joint_controller", + default_value="joint_trajectory_controller", + description="Robot controller to start.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "moveit_config_package", + default_value="rbs_arm", + description="MoveIt config package with robot SRDF/XACRO files. Usually the argument \ + is not set, it enables use of a custom moveit config.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "moveit_config_file", + default_value="rbs_arm.srdf.xacro", + description="MoveIt SRDF/XACRO description file with the robot.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "use_sim_time", + default_value="true", + description="Make MoveIt to use simulation time.\ + This is needed for the trajectory planing in simulation.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "gripper_name", + default_value="rbs_gripper", + choices=["rbs_gripper", ""], + description="choose gripper by name (leave empty if hasn't)", + ) + ) + declared_arguments.append( + DeclareLaunchArgument("with_gripper", + default_value="true", + description="With gripper or not?") + ) + declared_arguments.append( + DeclareLaunchArgument("sim_gazebo", + default_value="true", + description="Gazebo Simulation") + ) + declared_arguments.append( + DeclareLaunchArgument("env_manager", + default_value="false", + description="Launch env_manager?") + ) + declared_arguments.append( + DeclareLaunchArgument("launch_sim", + default_value="true", + description="Launch simulator (Gazebo)?\ + Most general arg") + ) + declared_arguments.append( + DeclareLaunchArgument("launch_moveit", + default_value="false", + description="Launch moveit?") + ) + declared_arguments.append( + DeclareLaunchArgument("launch_perception", + default_value="false", + description="Launch perception?") + ) + declared_arguments.append( + DeclareLaunchArgument("launch_task_planner", + default_value="false", + description="Launch task_planner?") + ) + declared_arguments.append( + DeclareLaunchArgument("cartesian_controllers", + default_value="true", + description="Load cartesian\ + controllers?") + ) + declared_arguments.append( + DeclareLaunchArgument("hardware", + choices=["gazebo", "mock"], + default_value="gazebo", + description="Choose your harware_interface") + ) + declared_arguments.append( + DeclareLaunchArgument("launch_controllers", + default_value="true", + description="Launch controllers?") + ) + declared_arguments.append( + DeclareLaunchArgument("gazebo_gui", + default_value="true", + description="Launch gazebo with gui?") + ) + # training arguments + declared_arguments.append( + DeclareLaunchArgument( + "env", + default_value="Reach-Gazebo-v0", + description="Environment ID", + )) + declared_arguments.append( + DeclareLaunchArgument( + "env_kwargs", + default_value="", + description="Optional keyword argument to pass to the env constructor.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "vec_env", + default_value="dummy", + description="Type of VecEnv to use (dummy or subproc).", + )) + # Algorithm and training + declared_arguments.append( + DeclareLaunchArgument( + "algo", + default_value="sac", + description="RL algorithm to use during the training.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "num_threads", + default_value="-1", + description="Number of threads for PyTorch (-1 to use default).", + )) + # Random seed + declared_arguments.append( + DeclareLaunchArgument( + "seed", + default_value="84", + description="Random generator seed.", + )) + # Logging + declared_arguments.append( + DeclareLaunchArgument( + "log_folder", + default_value="logs", + description="Path to the log directory.", + )) + # Verbosity + declared_arguments.append( + DeclareLaunchArgument( + "verbose", + default_value="1", + description="Verbose mode (0: no output, 1: INFO).", + )) + # HER specifics + declared_arguments.append( + DeclareLaunchArgument( + "log_level", + default_value="error", + description="The level of logging that is applied to all ROS 2 nodes launched by this script.", + )) + + + declared_arguments.append( + DeclareLaunchArgument( + "n_episodes", + default_value="200", + description="Number of evaluation episodes.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "exp_id", + default_value="0", + description="Experiment ID (default: 0: latest, -1: no exp folder).", + )) + declared_arguments.append( + DeclareLaunchArgument( + "load_best", + default_value="false", + description="Load best model instead of last model if available.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "load_checkpoint", + default_value="0", + description="Load checkpoint instead of last model if available, you must pass the number of timesteps corresponding to it.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "stochastic", + default_value="false", + description="Use stochastic actions instead of deterministic.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "reward_log", + default_value="reward_logs", + description="Where to log reward.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "norm_reward", + default_value="false", + description="Normalize reward if applicable (trained with VecNormalize)", + )) + declared_arguments.append( + DeclareLaunchArgument( + "no_render", + default_value="true", + description="Do not render the environment (useful for tests).", + )) + + + + env_variables = [ + SetEnvironmentVariable(name="OMP_DYNAMIC", value="TRUE"), + SetEnvironmentVariable(name="OMP_NUM_THREADS", value=str(cpu_count() // 2)) + ] + + return LaunchDescription(declared_arguments + [OpaqueFunction(function=launch_setup)] + env_variables) diff --git a/env_manager/rbs_gym/launch/optimize.launch.py b/env_manager/rbs_gym/launch/optimize.launch.py new file mode 100644 index 0000000..7e06a9c --- /dev/null +++ b/env_manager/rbs_gym/launch/optimize.launch.py @@ -0,0 +1,519 @@ +from launch import LaunchDescription +from launch.actions import ( + DeclareLaunchArgument, + IncludeLaunchDescription, + OpaqueFunction, + TimerAction +) +from launch.launch_description_sources import PythonLaunchDescriptionSource +from launch.substitutions import LaunchConfiguration, PathJoinSubstitution +from launch_ros.substitutions import FindPackageShare +from launch_ros.actions import Node +import os +from os import cpu_count +from ament_index_python.packages import get_package_share_directory + +def launch_setup(context, *args, **kwargs): + # Initialize Arguments + robot_type = LaunchConfiguration("robot_type") + # General arguments + with_gripper_condition = LaunchConfiguration("with_gripper") + controllers_file = LaunchConfiguration("controllers_file") + cartesian_controllers = LaunchConfiguration("cartesian_controllers") + description_package = LaunchConfiguration("description_package") + description_file = LaunchConfiguration("description_file") + robot_name = LaunchConfiguration("robot_name") + start_joint_controller = LaunchConfiguration("start_joint_controller") + initial_joint_controller = LaunchConfiguration("initial_joint_controller") + launch_simulation = LaunchConfiguration("launch_sim") + launch_moveit = LaunchConfiguration("launch_moveit") + launch_task_planner = LaunchConfiguration("launch_task_planner") + launch_perception = LaunchConfiguration("launch_perception") + moveit_config_package = LaunchConfiguration("moveit_config_package") + moveit_config_file = LaunchConfiguration("moveit_config_file") + use_sim_time = LaunchConfiguration("use_sim_time") + sim_gazebo = LaunchConfiguration("sim_gazebo") + hardware = LaunchConfiguration("hardware") + env_manager = LaunchConfiguration("env_manager") + launch_controllers = LaunchConfiguration("launch_controllers") + gripper_name = LaunchConfiguration("gripper_name") + + # training arguments + env = LaunchConfiguration("env") + env_kwargs = LaunchConfiguration("env_kwargs") + algo = LaunchConfiguration("algo") + hyperparams = LaunchConfiguration("hyperparams") + n_timesteps = LaunchConfiguration("n_timesteps") + num_threads = LaunchConfiguration("num_threads") + seed = LaunchConfiguration("seed") + preload_replay_buffer = LaunchConfiguration("preload_replay_buffer") + log_folder = LaunchConfiguration("log_folder") + tensorboard_log = LaunchConfiguration("tensorboard_log") + log_interval = LaunchConfiguration("log_interval") + uuid = LaunchConfiguration("uuid") + eval_episodes = LaunchConfiguration("eval_episodes") + verbose = LaunchConfiguration("verbose") + truncate_last_trajectory = LaunchConfiguration("truncate_last_trajectory") + use_sim_time = LaunchConfiguration("use_sim_time") + log_level = LaunchConfiguration("log_level") + sampler = LaunchConfiguration("sampler") + pruner = LaunchConfiguration("pruner") + n_trials = LaunchConfiguration("n_trials") + n_startup_trials = LaunchConfiguration("n_startup_trials") + n_evaluations = LaunchConfiguration("n_evaluations") + n_jobs = LaunchConfiguration("n_jobs") + storage = LaunchConfiguration("storage") + study_name = LaunchConfiguration("study_name") + + + sim_gazebo = LaunchConfiguration("sim_gazebo") + launch_simulation = LaunchConfiguration("launch_sim") + + initial_joint_controllers_file_path = os.path.join( + get_package_share_directory('rbs_arm'), 'config', 'controllers.yaml' + ) + + single_robot_setup = IncludeLaunchDescription( + PythonLaunchDescriptionSource([ + PathJoinSubstitution([ + FindPackageShare('rbs_bringup'), + "launch", + "rbs_robot.launch.py" + ]) + ]), + launch_arguments={ + "env_manager": env_manager, + "with_gripper": with_gripper_condition, + "gripper_name": gripper_name, + "controllers_file": controllers_file, + "robot_type": robot_type, + "controllers_file": initial_joint_controllers_file_path, + "cartesian_controllers": cartesian_controllers, + "description_package": description_package, + "description_file": description_file, + "robot_name": robot_name, + "start_joint_controller": start_joint_controller, + "initial_joint_controller": initial_joint_controller, + "launch_simulation": launch_simulation, + "launch_moveit": launch_moveit, + "launch_task_planner": launch_task_planner, + "launch_perception": launch_perception, + "moveit_config_package": moveit_config_package, + "moveit_config_file": moveit_config_file, + "use_sim_time": use_sim_time, + "sim_gazebo": sim_gazebo, + "hardware": hardware, + "launch_controllers": launch_controllers, + # "gazebo_gui": gazebo_gui + }.items() + ) + + args = [ + "--env", + env, + "--env-kwargs", + env_kwargs, + "--algo", + algo, + "--seed", + seed, + "--num-threads", + num_threads, + "--n-timesteps", + n_timesteps, + "--preload-replay-buffer", + preload_replay_buffer, + "--log-folder", + log_folder, + "--tensorboard-log", + tensorboard_log, + "--log-interval", + log_interval, + "--uuid", + uuid, + "--optimize-hyperparameters", + "True", + "--sampler", + sampler, + "--pruner", + pruner, + "--n-trials", + n_trials, + "--n-startup-trials", + n_startup_trials, + "--n-evaluations", + n_evaluations, + "--n-jobs", + n_jobs, + "--storage", + storage, + "--study-name", + study_name, + "--eval-episodes", + eval_episodes, + "--verbose", + verbose, + "--truncate-last-trajectory", + truncate_last_trajectory, + "--ros-args", + "--log-level", + log_level, + ] + + rl_task = Node( + package="rbs_gym", + executable="train", + output="log", + arguments = args, + parameters=[{"use_sim_time": True}] + ) + + + delay_robot_control_stack = TimerAction( + period=10.0, + actions=[single_robot_setup] + ) + + nodes_to_start = [ + rl_task, + delay_robot_control_stack + ] + return nodes_to_start + + +def generate_launch_description(): + declared_arguments = [] + declared_arguments.append( + DeclareLaunchArgument( + "robot_type", + description="Type of robot by name", + choices=["rbs_arm","ur3", "ur3e", "ur5", "ur5e", "ur10", "ur10e", "ur16e"], + default_value="rbs_arm", + ) + ) + # General arguments + declared_arguments.append( + DeclareLaunchArgument( + "controllers_file", + default_value="controllers_gazebosim.yaml", + description="YAML file with the controllers configuration.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "description_package", + default_value="rbs_arm", + description="Description package with robot URDF/XACRO files. Usually the argument \ + is not set, it enables use of a custom description.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "description_file", + default_value="rbs_arm_modular.xacro", + description="URDF/XACRO description file with the robot.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "robot_name", + default_value="arm0", + description="Name for robot, used to apply namespace for specific robot in multirobot setup", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "start_joint_controller", + default_value="false", + description="Enable headless mode for robot control", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "initial_joint_controller", + default_value="joint_trajectory_controller", + description="Robot controller to start.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "moveit_config_package", + default_value="rbs_arm", + description="MoveIt config package with robot SRDF/XACRO files. Usually the argument \ + is not set, it enables use of a custom moveit config.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "moveit_config_file", + default_value="rbs_arm.srdf.xacro", + description="MoveIt SRDF/XACRO description file with the robot.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "use_sim_time", + default_value="true", + description="Make MoveIt to use simulation time.\ + This is needed for the trajectory planing in simulation.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "gripper_name", + default_value="rbs_gripper", + choices=["rbs_gripper", ""], + description="choose gripper by name (leave empty if hasn't)", + ) + ) + declared_arguments.append( + DeclareLaunchArgument("with_gripper", + default_value="true", + description="With gripper or not?") + ) + declared_arguments.append( + DeclareLaunchArgument("sim_gazebo", + default_value="true", + description="Gazebo Simulation") + ) + declared_arguments.append( + DeclareLaunchArgument("env_manager", + default_value="false", + description="Launch env_manager?") + ) + declared_arguments.append( + DeclareLaunchArgument("launch_sim", + default_value="true", + description="Launch simulator (Gazebo)?\ + Most general arg") + ) + declared_arguments.append( + DeclareLaunchArgument("launch_moveit", + default_value="false", + description="Launch moveit?") + ) + declared_arguments.append( + DeclareLaunchArgument("launch_perception", + default_value="false", + description="Launch perception?") + ) + declared_arguments.append( + DeclareLaunchArgument("launch_task_planner", + default_value="false", + description="Launch task_planner?") + ) + declared_arguments.append( + DeclareLaunchArgument("cartesian_controllers", + default_value="true", + description="Load cartesian\ + controllers?") + ) + declared_arguments.append( + DeclareLaunchArgument("hardware", + choices=["gazebo", "mock"], + default_value="gazebo", + description="Choose your harware_interface") + ) + declared_arguments.append( + DeclareLaunchArgument("launch_controllers", + default_value="true", + description="Launch controllers?") + ) + declared_arguments.append( + DeclareLaunchArgument("gazebo_gui", + default_value="true", + description="Launch gazebo with gui?") + ) + # training arguments + declared_arguments.append( + DeclareLaunchArgument( + "env", + default_value="Reach-Gazebo-v0", + description="Environment ID", + )) + declared_arguments.append( + DeclareLaunchArgument( + "env_kwargs", + default_value="", + description="Optional keyword argument to pass to the env constructor.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "vec_env", + default_value="dummy", + description="Type of VecEnv to use (dummy or subproc).", + )) + # Algorithm and training + declared_arguments.append( + DeclareLaunchArgument( + "algo", + default_value="sac", + description="RL algorithm to use during the training.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "n_timesteps", + default_value="-1", + description="Overwrite the number of timesteps.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "hyperparams", + default_value="", + description="Optional RL hyperparameter overwrite (e.g. learning_rate:0.01 train_freq:10).", + )) + declared_arguments.append( + DeclareLaunchArgument( + "num_threads", + default_value="-1", + description="Number of threads for PyTorch (-1 to use default).", + )) + # Continue training an already trained agent + declared_arguments.append( + DeclareLaunchArgument( + "trained_agent", + default_value="", + description="Path to a pretrained agent to continue training.", + )) + # Random seed + declared_arguments.append( + DeclareLaunchArgument( + "seed", + default_value="84", + description="Random generator seed.", + )) + # Saving of model + declared_arguments.append( + DeclareLaunchArgument( + "save_freq", + default_value="10000", + description="Save the model every n steps (if negative, no checkpoint).", + )) + declared_arguments.append( + DeclareLaunchArgument( + "save_replay_buffer", + default_value="False", + description="Save the replay buffer too (when applicable).", + )) + # Pre-load a replay buffer and start training on it + declared_arguments.append( + DeclareLaunchArgument( + "preload_replay_buffer", + default_value="", + description="Path to a replay buffer that should be preloaded before starting the training process.", + )) + # Logging + declared_arguments.append( + DeclareLaunchArgument( + "log_folder", + default_value="logs", + description="Path to the log directory.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "tensorboard_log", + default_value="tensorboard_logs", + description="Tensorboard log dir.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "log_interval", + default_value="-1", + description="Override log interval (default: -1, no change).", + )) + declared_arguments.append( + DeclareLaunchArgument( + "uuid", + default_value="False", + description="Ensure that the run has a unique ID.", + )) + + declared_arguments.append( + DeclareLaunchArgument( + "sampler", + default_value="tpe", + description="Sampler to use when optimizing hyperparameters (random, tpe or skopt).", + )) + declared_arguments.append( + DeclareLaunchArgument( + "pruner", + default_value="median", + description="Pruner to use when optimizing hyperparameters (halving, median or none).", + )) + declared_arguments.append( + DeclareLaunchArgument( + "n_trials", + default_value="10", + description="Number of trials for optimizing hyperparameters.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "n_startup_trials", + default_value="5", + description="Number of trials before using optuna sampler.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "n_evaluations", + default_value="2", + description="Number of evaluations for hyperparameter optimization.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "n_jobs", + default_value="1", + description="Number of parallel jobs when optimizing hyperparameters.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "storage", + default_value="", + description="Database storage path if distributed optimization should be used.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "study_name", + default_value="", + description="Study name for distributed optimization.", + )) + + # Evaluation + declared_arguments.append( + DeclareLaunchArgument( + "eval_freq", + default_value="-1", + description="Evaluate the agent every n steps (if negative, no evaluation).", + )) + declared_arguments.append( + DeclareLaunchArgument( + "eval_episodes", + default_value="5", + description="Number of episodes to use for evaluation.", + )) + # Verbosity + declared_arguments.append( + DeclareLaunchArgument( + "verbose", + default_value="1", + description="Verbose mode (0: no output, 1: INFO).", + )) + # HER specifics + declared_arguments.append( + DeclareLaunchArgument( + "truncate_last_trajectory", + default_value="True", + description="When using HER with online sampling the last trajectory in the replay buffer will be truncated after) reloading the replay buffer." + )), + declared_arguments.append( + DeclareLaunchArgument( + "log_level", + default_value="error", + description="The level of logging that is applied to all ROS 2 nodes launched by this script.", + )) + +# env_variables = [ +# SetEnvironmentVariable(name="OMP_DYNAMIC", value="TRUE"), +# SetEnvironmentVariable(name="OMP_NUM_THREADS", value=str(cpu_count() // 2)) +# ] + + return LaunchDescription(declared_arguments + [OpaqueFunction(function=launch_setup)]) diff --git a/env_manager/rbs_gym/launch/test_env.launch.py b/env_manager/rbs_gym/launch/test_env.launch.py new file mode 100644 index 0000000..9cfbdde --- /dev/null +++ b/env_manager/rbs_gym/launch/test_env.launch.py @@ -0,0 +1,507 @@ +import os +from os import cpu_count + +import xacro +import yaml +from ament_index_python.packages import get_package_share_directory +from launch import LaunchDescription +from launch.actions import ( + DeclareLaunchArgument, + IncludeLaunchDescription, + OpaqueFunction, + SetEnvironmentVariable, + TimerAction, +) +from launch.launch_description_sources import PythonLaunchDescriptionSource +from launch.substitutions import LaunchConfiguration, PathJoinSubstitution +from launch_ros.actions import Node +from launch_ros.substitutions import FindPackageShare +from robot_builder.external.ros2_control import ControllerManager +from robot_builder.parser.urdf import URDF_parser + + +def launch_setup(context, *args, **kwargs): + # Initialize Arguments + robot_type = LaunchConfiguration("robot_type") + # General arguments + with_gripper_condition = LaunchConfiguration("with_gripper") + description_package = LaunchConfiguration("description_package") + description_file = LaunchConfiguration("description_file") + use_moveit = LaunchConfiguration("use_moveit") + moveit_config_package = LaunchConfiguration("moveit_config_package") + moveit_config_file = LaunchConfiguration("moveit_config_file") + use_sim_time = LaunchConfiguration("use_sim_time") + scene_config_file = LaunchConfiguration("scene_config_file").perform(context) + + ee_link_name = LaunchConfiguration("ee_link_name").perform(context) + base_link_name = LaunchConfiguration("base_link_name").perform(context) + + control_space = LaunchConfiguration("control_space").perform(context) + control_strategy = LaunchConfiguration("control_strategy").perform(context) + use_rbs_utils = LaunchConfiguration("use_rbs_utils") + + interactive = LaunchConfiguration("interactive").perform(context) + + # training arguments + env = LaunchConfiguration("env") + use_sim_time = LaunchConfiguration("use_sim_time") + log_level = LaunchConfiguration("log_level") + env_kwargs = LaunchConfiguration("env_kwargs") + + description_package_abs_path = get_package_share_directory( + description_package.perform(context) + ) + + xacro_file = os.path.join( + description_package_abs_path, + "urdf", + description_file.perform(context), + ) + + if not scene_config_file == "": + config_file = {"config_file": scene_config_file} + else: + config_file = {} + + description_package_abs_path = get_package_share_directory( + description_package.perform(context) + ) + + controllers_file = os.path.join( + description_package_abs_path, "config", "controllers.yaml" + ) + + xacro_file = os.path.join( + description_package_abs_path, + "urdf", + description_file.perform(context), + ) + + # xacro_config_file = f"{description_package_abs_path}/config/xacro_args.yaml" + xacro_config_file = os.path.join( + description_package_abs_path, "urdf", "xacro_args.yaml" + ) + + # TODO: hide this to another place + # Load xacro_args + def param_constructor(loader, node, local_vars): + value = loader.construct_scalar(node) + return LaunchConfiguration(value).perform( + local_vars.get("context", "Launch context if not defined") + ) + + def variable_constructor(loader, node, local_vars): + value = loader.construct_scalar(node) + return local_vars.get(value, f"Variable '{value}' not found") + + def load_xacro_args(yaml_file, local_vars): + # Get valut from ros2 argument + yaml.add_constructor( + "!param", lambda loader, node: param_constructor(loader, node, local_vars) + ) + + # Get value from local variable in this code + # The local variable should be initialized before the loader was called + yaml.add_constructor( + "!variable", + lambda loader, node: variable_constructor(loader, node, local_vars), + ) + + with open(yaml_file, "r") as file: + return yaml.load(file, Loader=yaml.FullLoader) + + mappings_data = load_xacro_args(xacro_config_file, locals()) + + robot_description_doc = xacro.process_file(xacro_file, mappings=mappings_data) + + robot_description_semantic_content = "" + + robot_description_content = robot_description_doc.toprettyxml(indent=" ") + robot_description = {"robot_description": robot_description_content} + + # Parse robot and configure controller's file for ControllerManager + robot = URDF_parser.load_string( + robot_description_content, ee_link_name=ee_link_name + ) + ControllerManager.save_to_yaml( + robot, description_package_abs_path, "controllers.yaml" + ) + + single_robot_setup = IncludeLaunchDescription( + PythonLaunchDescriptionSource( + [ + PathJoinSubstitution( + [FindPackageShare("rbs_bringup"), "launch", "rbs_robot.launch.py"] + ) + ] + ), + launch_arguments={ + "with_gripper": with_gripper_condition, + "controllers_file": controllers_file, + "robot_type": robot_type, + "description_package": description_package, + "description_file": description_file, + "robot_name": robot_type, + "use_moveit": "false", + "moveit_config_package": moveit_config_package, + "moveit_config_file": moveit_config_file, + "use_sim_time": "true", + "use_skills": "false", + "use_controllers": "true", + "robot_description": robot_description_content, + "robot_description_semantic": robot_description_semantic_content, + "base_link_name": base_link_name, + "ee_link_name": ee_link_name, + "control_space": control_space, + "control_strategy": control_strategy, + "use_rbs_utils": use_rbs_utils, + "interactive_control": "false", + }.items(), + ) + + args = [ + "--env", + env, + "--env-kwargs", + env_kwargs, + "--ros-args", + "--log-level", + log_level, + ] + + rl_task = Node( + package="rbs_gym", + executable="test_agent", + output="log", + arguments=args, + parameters=[{"use_sim_time": True}, robot_description], + ) + + clock_bridge = Node( + package="ros_gz_bridge", + executable="parameter_bridge", + arguments=["/clock@rosgraph_msgs/msg/Clock[ignition.msgs.Clock"], + output="screen", + ) + + delay_robot_control_stack = TimerAction(period=10.0, actions=[single_robot_setup]) + + nodes_to_start = [ + # env, + rl_task, + clock_bridge, + delay_robot_control_stack, + ] + return nodes_to_start + + +def generate_launch_description(): + declared_arguments = [] + declared_arguments.append( + DeclareLaunchArgument( + "robot_type", + description="Type of robot by name", + choices=[ + "rbs_arm", + "ar4", + "ur3", + "ur3e", + "ur5", + "ur5e", + "ur10", + "ur10e", + "ur16e", + ], + default_value="rbs_arm", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "description_package", + default_value="rbs_arm", + description="Description package with robot URDF/XACRO files. Usually the argument \ + is not set, it enables use of a custom description.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "description_file", + default_value="rbs_arm_modular.xacro", + description="URDF/XACRO description file with the robot.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "robot_name", + default_value="arm0", + description="Name for robot, used to apply namespace for specific robot in multirobot setup", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "moveit_config_package", + default_value="rbs_arm", + description="MoveIt config package with robot SRDF/XACRO files. Usually the argument \ + is not set, it enables use of a custom moveit config.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "moveit_config_file", + default_value="rbs_arm.srdf.xacro", + description="MoveIt SRDF/XACRO description file with the robot.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "use_sim_time", + default_value="true", + description="Make MoveIt to use simulation time.\ + This is needed for the trajectory planing in simulation.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "with_gripper", default_value="true", description="With gripper or not?" + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "use_moveit", default_value="false", description="Launch moveit?" + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "launch_perception", default_value="false", description="Launch perception?" + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "use_controllers", + default_value="true", + description="Launch controllers?", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "scene_config_file", + default_value="", + description="Path to a scene configuration file", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "ee_link_name", + default_value="", + description="End effector name of robot arm", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "base_link_name", + default_value="", + description="Base link name if robot arm", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "control_space", + default_value="task", + choices=["task", "joint"], + description="Specify the control space for the robot (e.g., task space).", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "control_strategy", + default_value="position", + choices=["position", "velocity", "effort"], + description="Specify the control strategy (e.g., position control).", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "interactive", + default_value="true", + description="Wheter to run the motion_control_handle controller", + ), + ) + + declared_arguments.append( + DeclareLaunchArgument( + "use_rbs_utils", + default_value="false", + description="Wheter to use rbs_utils", + ), + ) + # training arguments + declared_arguments.append( + DeclareLaunchArgument( + "env", + default_value="Reach-Gazebo-v0", + description="Environment ID", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "env_kwargs", + default_value="", + description="Optional keyword argument to pass to the env constructor.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "vec_env", + default_value="dummy", + description="Type of VecEnv to use (dummy or subproc).", + ) + ) + # Algorithm and training + declared_arguments.append( + DeclareLaunchArgument( + "algo", + default_value="sac", + description="RL algorithm to use during the training.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "n_timesteps", + default_value="-1", + description="Overwrite the number of timesteps.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "hyperparams", + default_value="", + description="Optional RL hyperparameter overwrite (e.g. learning_rate:0.01 train_freq:10).", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "num_threads", + default_value="-1", + description="Number of threads for PyTorch (-1 to use default).", + ) + ) + # Continue training an already trained agent + declared_arguments.append( + DeclareLaunchArgument( + "trained_agent", + default_value="", + description="Path to a pretrained agent to continue training.", + ) + ) + # Random seed + declared_arguments.append( + DeclareLaunchArgument( + "seed", + default_value="-1", + description="Random generator seed.", + ) + ) + # Saving of model + declared_arguments.append( + DeclareLaunchArgument( + "save_freq", + default_value="10000", + description="Save the model every n steps (if negative, no checkpoint).", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "save_replay_buffer", + default_value="False", + description="Save the replay buffer too (when applicable).", + ) + ) + # Pre-load a replay buffer and start training on it + declared_arguments.append( + DeclareLaunchArgument( + "preload_replay_buffer", + default_value="", + description="Path to a replay buffer that should be preloaded before starting the training process.", + ) + ) + # Logging + declared_arguments.append( + DeclareLaunchArgument( + "log_folder", + default_value="logs", + description="Path to the log directory.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "tensorboard_log", + default_value="tensorboard_logs", + description="Tensorboard log dir.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "log_interval", + default_value="-1", + description="Override log interval (default: -1, no change).", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "uuid", + default_value="False", + description="Ensure that the run has a unique ID.", + ) + ) + # Evaluation + declared_arguments.append( + DeclareLaunchArgument( + "eval_freq", + default_value="-1", + description="Evaluate the agent every n steps (if negative, no evaluation).", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "eval_episodes", + default_value="5", + description="Number of episodes to use for evaluation.", + ) + ) + # Verbosity + declared_arguments.append( + DeclareLaunchArgument( + "verbose", + default_value="1", + description="Verbose mode (0: no output, 1: INFO).", + ) + ) + # HER specifics + declared_arguments.append( + DeclareLaunchArgument( + "truncate_last_trajectory", + default_value="True", + description="When using HER with online sampling the last trajectory in the replay buffer will be truncated after) reloading the replay buffer.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "log_level", + default_value="error", + description="The level of logging that is applied to all ROS 2 nodes launched by this script.", + ) + ) + cpu_c = cpu_count() + if cpu_c is not None: + env_variables = [ + SetEnvironmentVariable(name="OMP_DYNAMIC", value="TRUE"), + SetEnvironmentVariable(name="OMP_NUM_THREADS", value=str(cpu_c // 2)), + ] + else: + env_variables = [ + SetEnvironmentVariable(name="OMP_DYNAMIC", value="TRUE"), + ] + + return LaunchDescription( + declared_arguments + [OpaqueFunction(function=launch_setup)] + env_variables + ) diff --git a/env_manager/rbs_gym/launch/train.launch.py b/env_manager/rbs_gym/launch/train.launch.py new file mode 100644 index 0000000..abea297 --- /dev/null +++ b/env_manager/rbs_gym/launch/train.launch.py @@ -0,0 +1,524 @@ +from launch import LaunchDescription +from launch.actions import ( + DeclareLaunchArgument, + IncludeLaunchDescription, + OpaqueFunction, + SetEnvironmentVariable, + TimerAction +) +from launch.launch_description_sources import PythonLaunchDescriptionSource +from launch.substitutions import LaunchConfiguration, PathJoinSubstitution +from launch_ros.substitutions import FindPackageShare +from launch_ros.actions import Node +import os +from os import cpu_count +from ament_index_python.packages import get_package_share_directory +import yaml +import xacro + +def launch_setup(context, *args, **kwargs): + # Initialize Arguments + robot_type = LaunchConfiguration("robot_type") + # General arguments + with_gripper_condition = LaunchConfiguration("with_gripper") + description_package = LaunchConfiguration("description_package") + description_file = LaunchConfiguration("description_file") + use_moveit = LaunchConfiguration("use_moveit") + moveit_config_package = LaunchConfiguration("moveit_config_package") + moveit_config_file = LaunchConfiguration("moveit_config_file") + use_sim_time = LaunchConfiguration("use_sim_time") + scene_config_file = LaunchConfiguration("scene_config_file").perform(context) + + ee_link_name = LaunchConfiguration("ee_link_name").perform(context) + base_link_name = LaunchConfiguration("base_link_name").perform(context) + + control_space = LaunchConfiguration("control_space").perform(context) + control_strategy = LaunchConfiguration("control_strategy").perform(context) + + interactive = LaunchConfiguration("interactive").perform(context) + + # training arguments + env = LaunchConfiguration("env") + algo = LaunchConfiguration("algo") + hyperparams = LaunchConfiguration("hyperparams") + n_timesteps = LaunchConfiguration("n_timesteps") + num_threads = LaunchConfiguration("num_threads") + seed = LaunchConfiguration("seed") + trained_agent = LaunchConfiguration("trained_agent") + save_freq = LaunchConfiguration("save_freq") + save_replay_buffer = LaunchConfiguration("save_replay_buffer") + preload_replay_buffer = LaunchConfiguration("preload_replay_buffer") + log_folder = LaunchConfiguration("log_folder") + tensorboard_log = LaunchConfiguration("tensorboard_log") + log_interval = LaunchConfiguration("log_interval") + uuid = LaunchConfiguration("uuid") + eval_freq = LaunchConfiguration("eval_freq") + eval_episodes = LaunchConfiguration("eval_episodes") + verbose = LaunchConfiguration("verbose") + truncate_last_trajectory = LaunchConfiguration("truncate_last_trajectory") + use_sim_time = LaunchConfiguration("use_sim_time") + log_level = LaunchConfiguration("log_level") + env_kwargs = LaunchConfiguration("env_kwargs") + + track = LaunchConfiguration("track") + + description_package_abs_path = get_package_share_directory( + description_package.perform(context) + ) + + + xacro_file = os.path.join( + description_package_abs_path, + "urdf", + description_file.perform(context), + ) + + if not scene_config_file == "": + config_file = {"config_file": scene_config_file} + else: + config_file = {} + + description_package_abs_path = get_package_share_directory( + description_package.perform(context) + ) + + controllers_file = os.path.join( + description_package_abs_path, "config", "controllers.yaml" + ) + + xacro_file = os.path.join( + description_package_abs_path, + "urdf", + description_file.perform(context), + ) + + # xacro_config_file = f"{description_package_abs_path}/config/xacro_args.yaml" + xacro_config_file = os.path.join( + description_package_abs_path, + "urdf", + "xacro_args.yaml" + ) + + + # TODO: hide this to another place + # Load xacro_args + def param_constructor(loader, node, local_vars): + value = loader.construct_scalar(node) + return LaunchConfiguration(value).perform( + local_vars.get("context", "Launch context if not defined") + ) + + def variable_constructor(loader, node, local_vars): + value = loader.construct_scalar(node) + return local_vars.get(value, f"Variable '{value}' not found") + + def load_xacro_args(yaml_file, local_vars): + # Get valut from ros2 argument + yaml.add_constructor( + "!param", lambda loader, node: param_constructor(loader, node, local_vars) + ) + + # Get value from local variable in this code + # The local variable should be initialized before the loader was called + yaml.add_constructor( + "!variable", + lambda loader, node: variable_constructor(loader, node, local_vars), + ) + + with open(yaml_file, "r") as file: + return yaml.load(file, Loader=yaml.FullLoader) + + mappings_data = load_xacro_args(xacro_config_file, locals()) + + robot_description_doc = xacro.process_file(xacro_file, mappings=mappings_data) + + robot_description_semantic_content = "" + + + robot_description_content = robot_description_doc.toprettyxml(indent=" ") + robot_description = {"robot_description": robot_description_content} + + single_robot_setup = IncludeLaunchDescription( + PythonLaunchDescriptionSource( + [ + PathJoinSubstitution( + [FindPackageShare("rbs_bringup"), "launch", "rbs_robot.launch.py"] + ) + ] + ), + launch_arguments={ + "with_gripper": with_gripper_condition, + "controllers_file": controllers_file, + "robot_type": robot_type, + "description_package": description_package, + "description_file": description_file, + "robot_name": robot_type, + "use_moveit": use_moveit, + "moveit_config_package": moveit_config_package, + "moveit_config_file": moveit_config_file, + "use_sim_time": use_sim_time, + "use_controllers": "true", + "robot_description": robot_description_content, + "robot_description_semantic": robot_description_semantic_content, + "base_link_name": base_link_name, + "ee_link_name": ee_link_name, + "control_space": control_space, + "control_strategy": control_strategy, + "interactive_control": interactive, + }.items(), + ) + + args = [ + "--env", + env, + "--env-kwargs", + env_kwargs, + "--algo", + algo, + "--hyperparams", + hyperparams, + "--n-timesteps", + n_timesteps, + "--num-threads", + num_threads, + "--seed", + seed, + "--trained-agent", + trained_agent, + "--save-freq", + save_freq, + "--save-replay-buffer", + save_replay_buffer, + "--preload-replay-buffer", + preload_replay_buffer, + "--log-folder", + log_folder, + "--tensorboard-log", + tensorboard_log, + "--log-interval", + log_interval, + "--uuid", + uuid, + "--eval-freq", + eval_freq, + "--eval-episodes", + eval_episodes, + "--verbose", + verbose, + "--track", + track, + "--truncate-last-trajectory", + truncate_last_trajectory, + "--ros-args", + "--log-level", + log_level, + ] + + clock_bridge = Node( + package='ros_gz_bridge', + executable='parameter_bridge', + arguments=['/clock@rosgraph_msgs/msg/Clock[ignition.msgs.Clock'], + output='screen') + + rl_task = Node( + package="rbs_gym", + executable="train", + output="log", + arguments=args, + parameters=[{"use_sim_time": True}] + ) + + + delay_robot_control_stack = TimerAction( + period=20.0, + actions=[single_robot_setup] + ) + + nodes_to_start = [ + # env, + rl_task, + clock_bridge, + delay_robot_control_stack + ] + return nodes_to_start + + +def generate_launch_description(): + declared_arguments = [] + declared_arguments.append( + DeclareLaunchArgument( + "robot_type", + description="Type of robot by name", + choices=[ + "rbs_arm", + "ar4", + "ur3", + "ur3e", + "ur5", + "ur5e", + "ur10", + "ur10e", + "ur16e", + ], + default_value="rbs_arm", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "description_package", + default_value="rbs_arm", + description="Description package with robot URDF/XACRO files. Usually the argument \ + is not set, it enables use of a custom description.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "description_file", + default_value="rbs_arm_modular.xacro", + description="URDF/XACRO description file with the robot.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "robot_name", + default_value="arm0", + description="Name for robot, used to apply namespace for specific robot in multirobot setup", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "moveit_config_package", + default_value="rbs_arm", + description="MoveIt config package with robot SRDF/XACRO files. Usually the argument \ + is not set, it enables use of a custom moveit config.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "moveit_config_file", + default_value="rbs_arm.srdf.xacro", + description="MoveIt SRDF/XACRO description file with the robot.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "use_sim_time", + default_value="true", + description="Make MoveIt to use simulation time.\ + This is needed for the trajectory planing in simulation.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "with_gripper", default_value="true", description="With gripper or not?" + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "use_moveit", default_value="false", description="Launch moveit?" + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "launch_perception", default_value="false", description="Launch perception?" + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "use_controllers", + default_value="true", + description="Launch controllers?", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "scene_config_file", + default_value="", + description="Path to a scene configuration file", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "ee_link_name", + default_value="", + description="End effector name of robot arm", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "base_link_name", + default_value="", + description="Base link name if robot arm", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "control_space", + default_value="task", + choices=["task", "joint"], + description="Specify the control space for the robot (e.g., task space).", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "control_strategy", + default_value="position", + choices=["position", "velocity", "effort"], + description="Specify the control strategy (e.g., position control).", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "interactive", + default_value="true", + description="Wheter to run the motion_control_handle controller", + ), + ) + # training arguments + declared_arguments.append( + DeclareLaunchArgument( + "env", + default_value="Reach-Gazebo-v0", + description="Environment ID", + )) + declared_arguments.append( + DeclareLaunchArgument( + "env_kwargs", + default_value="", + description="Optional keyword argument to pass to the env constructor.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "vec_env", + default_value="dummy", + description="Type of VecEnv to use (dummy or subproc).", + )) + # Algorithm and training + declared_arguments.append( + DeclareLaunchArgument( + "algo", + default_value="sac", + description="RL algorithm to use during the training.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "n_timesteps", + default_value="-1", + description="Overwrite the number of timesteps.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "hyperparams", + default_value="", + description="Optional RL hyperparameter overwrite (e.g. learning_rate:0.01 train_freq:10).", + )) + declared_arguments.append( + DeclareLaunchArgument( + "num_threads", + default_value="-1", + description="Number of threads for PyTorch (-1 to use default).", + )) + # Continue training an already trained agent + declared_arguments.append( + DeclareLaunchArgument( + "trained_agent", + default_value="", + description="Path to a pretrained agent to continue training.", + )) + # Random seed + declared_arguments.append( + DeclareLaunchArgument( + "seed", + default_value="-1", + description="Random generator seed.", + )) + # Saving of model + declared_arguments.append( + DeclareLaunchArgument( + "save_freq", + default_value="10000", + description="Save the model every n steps (if negative, no checkpoint).", + )) + declared_arguments.append( + DeclareLaunchArgument( + "save_replay_buffer", + default_value="False", + description="Save the replay buffer too (when applicable).", + )) + # Pre-load a replay buffer and start training on it + declared_arguments.append( + DeclareLaunchArgument( + "preload_replay_buffer", + default_value="", + description="Path to a replay buffer that should be preloaded before starting the training process.", + )) + # Logging + declared_arguments.append( + DeclareLaunchArgument( + "log_folder", + default_value="logs", + description="Path to the log directory.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "tensorboard_log", + default_value="tensorboard_logs", + description="Tensorboard log dir.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "log_interval", + default_value="-1", + description="Override log interval (default: -1, no change).", + )) + declared_arguments.append( + DeclareLaunchArgument( + "uuid", + default_value="False", + description="Ensure that the run has a unique ID.", + )) + # Evaluation + declared_arguments.append( + DeclareLaunchArgument( + "eval_freq", + default_value="-1", + description="Evaluate the agent every n steps (if negative, no evaluation).", + )) + declared_arguments.append( + DeclareLaunchArgument( + "eval_episodes", + default_value="5", + description="Number of episodes to use for evaluation.", + )) + # Verbosity + declared_arguments.append( + DeclareLaunchArgument( + "verbose", + default_value="1", + description="Verbose mode (0: no output, 1: INFO).", + )) + declared_arguments.append( + DeclareLaunchArgument( + "truncate_last_trajectory", + default_value="True", + description="When using HER with online sampling the last trajectory in the replay buffer will be truncated after) reloading the replay buffer." + )) + declared_arguments.append( + DeclareLaunchArgument( + "log_level", + default_value="error", + description="The level of logging that is applied to all ROS 2 nodes launched by this script.", + )) + declared_arguments.append( + DeclareLaunchArgument( + "track", + default_value="true", + description="The level of logging that is applied to all ROS 2 nodes launched by this script.", + )) + + env_variables = [ + SetEnvironmentVariable(name="OMP_DYNAMIC", value="TRUE"), + SetEnvironmentVariable(name="OMP_NUM_THREADS", value=str(cpu_count() // 2)) + ] + + return LaunchDescription(declared_arguments + [OpaqueFunction(function=launch_setup)] + env_variables) diff --git a/env_manager/rbs_gym/package.nix b/env_manager/rbs_gym/package.nix new file mode 100644 index 0000000..6411afe --- /dev/null +++ b/env_manager/rbs_gym/package.nix @@ -0,0 +1,20 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 + +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license + +{ lib, buildRosPackage, ament-copyright, ament-flake8, ament-pep257, pythonPackages }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-gym"; + version = "0.0.0"; + + src = ./.; + + buildType = "ament_python"; + checkInputs = [ ament-copyright ament-flake8 ament-pep257 pythonPackages.pytest ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/env_manager/rbs_gym/package.xml b/env_manager/rbs_gym/package.xml new file mode 100644 index 0000000..c11a38c --- /dev/null +++ b/env_manager/rbs_gym/package.xml @@ -0,0 +1,18 @@ + + + + rbs_gym + 0.0.0 + TODO: Package description + narmak + Apache-2.0 + + ament_copyright + ament_flake8 + ament_pep257 + python3-pytest + + + ament_python + + diff --git a/env_manager/rbs_gym/rbs_gym/__init__.py b/env_manager/rbs_gym/rbs_gym/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/env_manager/rbs_gym/rbs_gym/envs/__init__.py b/env_manager/rbs_gym/rbs_gym/envs/__init__.py new file mode 100644 index 0000000..f0db77a --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/__init__.py @@ -0,0 +1,184 @@ +# Note: The `open3d` and `stable_baselines3` modules must be imported prior to `gym_gz` +from env_manager.models.configs import ( + RobotData, + SceneData, + SphereObjectData, + TerrainData, +) +from env_manager.models.configs.objects import ObjectRandomizerData +from env_manager.models.configs.robot import RobotRandomizerData +from env_manager.models.configs.scene import PluginsData +# import open3d # isort:skip +import stable_baselines3 # isort:skip + +# Note: If installed, `tensorflow` module must be imported before `gym_gz`/`scenario` +# Otherwise, protobuf version incompatibility will cause an error +try: + from importlib.util import find_spec + + if find_spec("tensorflow") is not None: + import tensorflow +except: + pass + +from os import environ, path +from typing import Any, Dict, Tuple + +import numpy as np +from ament_index_python.packages import get_package_share_directory +from gymnasium.envs.registration import register +from rbs_assets_library import get_world_file + +from rbs_gym.utils.utils import str2bool + +from . import tasks + +###################### +# Runtime Entrypoint # +###################### + +RBS_ENVS_TASK_ENTRYPOINT: str = "gym_gz.runtimes.gazebo_runtime:GazeboRuntime" + + +################### +# Robot Specifics # +################### +# Default robot model to use in the tasks where robot can be static +RBS_ENVS_ROBOT_MODEL: str = "rbs_arm" + +###################### +# Datasets and paths # +###################### +# Path to directory containing base SDF worlds +RBS_ENVS_WORLDS_DIR: str = path.join(get_package_share_directory("rbs_gym"), "worlds") + + +########### +# Presets # +########### +# Gravity preset for Earth +# GRAVITY_EARTH: Tuple[float, float, float] = (0.0, 0.0, -9.80665) +# GRAVITY_EARTH_STD: Tuple[float, float, float] = (0.0, 0.0, 0.0232) + +############################ +# Additional Configuration # +############################ +# BROADCAST_GUI: bool = str2bool( +# environ.get("RBS_ENVS_BROADCAST_INTERACTIVE_GUI", default=True) +# ) + + +######### +# Reach # +######### +REACH_MAX_EPISODE_STEPS: int = 100 +REACH_KWARGS: Dict[str, Any] = { + "agent_rate": 4.0, + "robot_model": RBS_ENVS_ROBOT_MODEL, + "workspace_frame_id": "world", + "workspace_centre": (-0.45, 0.0, 0.35), + "workspace_volume": (0.7, 0.7, 0.7), + "ignore_new_actions_while_executing": False, + "use_servo": True, + "scaling_factor_translation": 8.0, + "scaling_factor_rotation": 3.0, + "restrict_position_goal_to_workspace": False, + "enable_gripper": False, + "sparse_reward": False, + "collision_reward": -10.0, + "act_quick_reward": -0.01, + "required_accuracy": 0.05, + "num_threads": 3, +} +REACH_KWARGS_SIM: Dict[str, Any] = { + "physics_rate": 100, + "real_time_factor": float(np.finfo(np.float32).max), + "world": get_world_file("ungravitational"), +} + + +REACH_RANDOMIZER: str = "rbs_gym.envs.randomizers:ManipulationGazeboEnvRandomizer" + +SCENE_CONFIGURATION: SceneData = SceneData( + physics_rollouts_num=0, + robot=RobotData( + name="rbs_arm", + joint_positions=[0.0, 0.5, 3.14159, 1.5, 0.0, 1.4, 0.0], + with_gripper=True, + gripper_joint_positions=0.00, + randomizer=RobotRandomizerData(joint_positions=True), + ), + objects=[ + SphereObjectData( + name="sphere", + type="sphere", + relative_to="base_link", + position=(0.0, 0.3, 0.5), + static=True, + collision=False, + color=(0.0, 1.0, 0.0, 0.8), + randomize=ObjectRandomizerData(random_pose=True, models_rollouts_num=2), + ) + ], + plugins=PluginsData( + scene_broadcaster=True, user_commands=True, fts_broadcaster=True + ), +) + + +# Task +register( + id="Reach-v0", + entry_point=RBS_ENVS_TASK_ENTRYPOINT, + max_episode_steps=REACH_MAX_EPISODE_STEPS, + kwargs={ + "task_cls": tasks.Reach, + **REACH_KWARGS, + }, +) +register( + id="Reach-ColorImage-v0", + entry_point=RBS_ENVS_TASK_ENTRYPOINT, + max_episode_steps=REACH_MAX_EPISODE_STEPS, + kwargs={ + "task_cls": tasks.ReachColorImage, + **REACH_KWARGS, + }, +) +register( + id="Reach-DepthImage-v0", + entry_point=RBS_ENVS_TASK_ENTRYPOINT, + max_episode_steps=REACH_MAX_EPISODE_STEPS, + kwargs={ + "task_cls": tasks.ReachDepthImage, + **REACH_KWARGS, + }, +) + +# Gazebo wrapper +register( + id="Reach-Gazebo-v0", + entry_point=REACH_RANDOMIZER, + max_episode_steps=REACH_MAX_EPISODE_STEPS, + kwargs={"env": "Reach-v0", **REACH_KWARGS_SIM, "scene_args": SCENE_CONFIGURATION}, +) +register( + id="Reach-ColorImage-Gazebo-v0", + entry_point=REACH_RANDOMIZER, + max_episode_steps=REACH_MAX_EPISODE_STEPS, + kwargs={ + "env": "Reach-ColorImage-v0", + **REACH_KWARGS_SIM, + "scene_args": SCENE_CONFIGURATION, + }, +) +register( + id="Reach-DepthImage-Gazebo-v0", + entry_point=REACH_RANDOMIZER, + max_episode_steps=REACH_MAX_EPISODE_STEPS, + kwargs={ + "env": "Reach-DepthImage-v0", + **REACH_KWARGS_SIM, + "scene_args": SCENE_CONFIGURATION, + }, +) diff --git a/env_manager/rbs_gym/rbs_gym/envs/control/__init__.py b/env_manager/rbs_gym/rbs_gym/envs/control/__init__.py new file mode 100644 index 0000000..b551c3d --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/control/__init__.py @@ -0,0 +1,3 @@ +from .cartesian_force_controller import CartesianForceController +from .grippper_controller import GripperController +from .joint_effort_controller import JointEffortController diff --git a/env_manager/rbs_gym/rbs_gym/envs/control/cartesian_force_controller.py b/env_manager/rbs_gym/rbs_gym/envs/control/cartesian_force_controller.py new file mode 100644 index 0000000..3c60500 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/control/cartesian_force_controller.py @@ -0,0 +1,41 @@ +from typing import Optional +from geometry_msgs.msg import WrenchStamped +from rclpy.node import Node +from rclpy.parameter import Parameter + +class CartesianForceController: + def __init__(self, node, namespace: Optional[str] = "") -> None: + self.node = node + self.publisher = node.create_publisher(WrenchStamped, + namespace + "/cartesian_force_controller/target_wrench", 10) + self.timer = node.create_timer(0.1, self.timer_callback) + self.publish = False + self._target_wrench = WrenchStamped() + + @property + def target_wrench(self) -> WrenchStamped: + return self._target_wrench + + @target_wrench.setter + def target_wrench(self, wrench: WrenchStamped): + self._target_wrench = wrench + + def timer_callback(self): + if self.publish: + self.publisher.publish(self._target_wrench) + + +class CartesianForceControllerStandalone(Node, CartesianForceController): + def __init__(self, node_name:str = "rbs_gym_controller", use_sim_time: bool = True): + + try: + rclpy.init() + except Exception as e: + if not rclpy.ok(): + sys.exit(f"ROS 2 context could not be initialised: {e}") + + Node.__init__(self, node_name) + self.set_parameters( + [Parameter("use_sim_time", type_=Parameter.Type.BOOL, value=use_sim_time)] + ) + CartesianForceController.__init__(self, node=self) diff --git a/env_manager/rbs_gym/rbs_gym/envs/control/cartesian_velocity_controller.py b/env_manager/rbs_gym/rbs_gym/envs/control/cartesian_velocity_controller.py new file mode 100644 index 0000000..b5a12c0 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/control/cartesian_velocity_controller.py @@ -0,0 +1,121 @@ +import rclpy +from rclpy.node import Node +import numpy as np +import quaternion +from geometry_msgs.msg import Twist +from geometry_msgs.msg import PoseStamped +import tf2_ros +import sys +import time +import threading +import os + + +class VelocityController: + """Convert Twist messages to PoseStamped + + Use this node to integrate twist messages into a moving target pose in + Cartesian space. An initial TF lookup assures that the target pose always + starts at the robot's end-effector. + """ + + def __init__(self, node: Node, topic_pose: str, topic_twist: str, base_frame: str, ee_frame: str): + self.node = node + + self._frame_id = base_frame + self._end_effector = ee_frame + + self.tf_buffer = tf2_ros.Buffer() + self.tf_listener = tf2_ros.TransformListener(self.tf_buffer, self) + self.rot = np.quaternion(0, 0, 0, 1) + self.pos = [0, 0, 0] + + self.pub = node.create_publisher(PoseStamped, topic_pose, 3) + self.sub = node.create_subscription(Twist, topic_twist, self.twist_cb, 1) + self.last = time.time() + + self.startup_done = False + period = 1.0 / node.declare_parameter("publishing_rate", 100).value + self.timer = node.create_timer(period, self.publish) + self.publish_it = False + + self.thread = threading.Thread(target=self.startup, daemon=True) + self.thread.start() + + def startup(self): + """Make sure to start at the robot's current pose""" + # Wait until we entered spinning in the main thread. + time.sleep(1) + try: + start = self.tf_buffer.lookup_transform( + target_frame=self._frame_id, + source_frame=self._end_effector, + time=rclpy.time.Time(), + ) + + except ( + tf2_ros.InvalidArgumentException, + tf2_ros.LookupException, + tf2_ros.ConnectivityException, + tf2_ros.ExtrapolationException, + ) as e: + print(f"Startup failed: {e}") + os._exit(1) + + self.pos[0] = start.transform.translation.x + self.pos[1] = start.transform.translation.y + self.pos[2] = start.transform.translation.z + self.rot.x = start.transform.rotation.x + self.rot.y = start.transform.rotation.y + self.rot.z = start.transform.rotation.z + self.rot.w = start.transform.rotation.w + self.startup_done = True + + def twist_cb(self, data): + """Numerically integrate twist message into a pose + + Use global self.frame_id as reference for the navigation commands. + """ + now = time.time() + dt = now - self.last + self.last = now + + # Position update + self.pos[0] += data.linear.x * dt + self.pos[1] += data.linear.y * dt + self.pos[2] += data.linear.z * dt + + # Orientation update + wx = data.angular.x + wy = data.angular.y + wz = data.angular.z + + _, q = quaternion.integrate_angular_velocity( + lambda _: (wx, wy, wz), 0, dt, self.rot + ) + + self.rot = q[-1] # the last one is after dt passed + + def publish(self): + if not self.startup_done: + return + if not self.publish_it: + return + try: + msg = PoseStamped() + msg.header.stamp = self.get_clock().now().to_msg() + msg.header.frame_id = self.frame_id + msg.pose.position.x = self.pos[0] + msg.pose.position.y = self.pos[1] + msg.pose.position.z = self.pos[2] + msg.pose.orientation.x = self.rot.x + msg.pose.orientation.y = self.rot.y + msg.pose.orientation.z = self.rot.z + msg.pose.orientation.w = self.rot.w + + self.pub.publish(msg) + except Exception: + # Swallow 'publish() to closed topic' error. + # This rarely happens on killing this node. + pass + diff --git a/env_manager/rbs_gym/rbs_gym/envs/control/grippper_controller.py b/env_manager/rbs_gym/rbs_gym/envs/control/grippper_controller.py new file mode 100644 index 0000000..79a9e2a --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/control/grippper_controller.py @@ -0,0 +1,50 @@ +from typing import Optional +from control_msgs.action import GripperCommand +from rclpy.action import ActionClient + + +class GripperController: + def __init__(self, node, + open_position: Optional[float] = 0.0, + close_position: Optional[float] = 0.0, + max_effort: Optional[float] = 0.0, + namespace: Optional[str] = ""): + self._action_client = ActionClient(node, GripperCommand, + namespace + "/gripper_controller/gripper_cmd") + self._open_position = open_position + self._close_position = close_position + self._max_effort = max_effort + self.is_executed = False + + def open(self): + self.send_goal(self._open_position) + + def close(self): + self.send_goal(self._close_position) + + def send_goal(self, goal: float): + goal_msg = GripperCommand.Goal() + goal_msg._command.position = goal + goal_msg._command.max_effort = self._max_effort + self._action_client.wait_for_server() + self._send_goal_future = self._action_client.send_goal_async(goal_msg) + self._send_goal_future.add_done_callback(self.goal_response_callback) + + def goal_response_callback(self, future): + goal_handle = future.result() + if not goal_handle.accepted: + self.get_logger().info('Goal rejected :(') + return + + self.get_logger().info('Goal accepted :)') + + self._get_result_future = goal_handle.get_result_async() + self._get_result_future.add_done_callback(self.get_result_callback) + + def get_result_callback(self, future): + result = future.result().result + self.get_logger().info(f"Gripper position: {result.position}") + + def wait_until_executed(self): + while not self.is_executed: + pass diff --git a/env_manager/rbs_gym/rbs_gym/envs/control/joint_effort_controller.py b/env_manager/rbs_gym/rbs_gym/envs/control/joint_effort_controller.py new file mode 100644 index 0000000..b58ff8a --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/control/joint_effort_controller.py @@ -0,0 +1,25 @@ +from typing import Optional +from std_msgs.msg import Float64MultiArray + +class JointEffortController: + def __init__(self, node, namespace: Optional[str] = "") -> None: + self.node = node + self.publisher = node.create_publisher(Float64MultiArray, + namespace + "/joint_effort_controller/commands", 10) + # self.timer = node.create_timer(0.1, self.timer_callback) + # self.publish = True + self._effort_array = Float64MultiArray() + + @property + def target_effort(self) -> Float64MultiArray: + return self._effort_array + + @target_effort.setter + def target_effort(self, data: Float64MultiArray): + self._effort_array = data + + # def timer_callback(self): + # if self.publish: + # self.publisher.publish(self._target_wrench) + + diff --git a/env_manager/rbs_gym/rbs_gym/envs/observation/__init__.py b/env_manager/rbs_gym/rbs_gym/envs/observation/__init__.py new file mode 100644 index 0000000..50b9243 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/observation/__init__.py @@ -0,0 +1,4 @@ +from .camera_subscriber import CameraSubscriber, CameraSubscriberStandalone +from .twist_subscriber import TwistSubscriber +from .joint_states import JointStates +# from .octree import OctreeCreator diff --git a/env_manager/rbs_gym/rbs_gym/envs/observation/camera_subscriber.py b/env_manager/rbs_gym/rbs_gym/envs/observation/camera_subscriber.py new file mode 100644 index 0000000..a60df57 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/observation/camera_subscriber.py @@ -0,0 +1,118 @@ +import sys +from threading import Lock, Thread +from typing import Optional, Union + +import rclpy +from rclpy.callback_groups import CallbackGroup +from rclpy.executors import SingleThreadedExecutor +from rclpy.node import Node +from rclpy.parameter import Parameter +from rclpy.qos import ( + QoSDurabilityPolicy, + QoSHistoryPolicy, + QoSProfile, + QoSReliabilityPolicy, +) +from sensor_msgs.msg import Image, PointCloud2 + + +class CameraSubscriber: + def __init__( + self, + node: Node, + topic: str, + is_point_cloud: bool, + callback_group: Optional[CallbackGroup] = None, + ): + + self._node = node + + # Prepare the subscriber + if is_point_cloud: + camera_msg_type = PointCloud2 + else: + camera_msg_type = Image + self.__observation = camera_msg_type() + self._node.create_subscription( + msg_type=camera_msg_type, + topic=topic, + callback=self.observation_callback, + qos_profile=QoSProfile( + reliability=QoSReliabilityPolicy.RELIABLE, + durability=QoSDurabilityPolicy.VOLATILE, + history=QoSHistoryPolicy.KEEP_LAST, + depth=1, + ), + callback_group=callback_group, + ) + self.__observation_mutex = Lock() + self.__new_observation_available = False + + def observation_callback(self, msg): + """ + Callback for getting observation. + """ + + self.__observation_mutex.acquire() + self.__observation = msg + self.__new_observation_available = True + self._node.get_logger().debug("New observation received.") + self.__observation_mutex.release() + + def get_observation(self) -> Union[PointCloud2, Image]: + """ + Get the last received observation. + """ + + self.__observation_mutex.acquire() + observation = self.__observation + self.__observation_mutex.release() + return observation + + def reset_new_observation_checker(self): + """ + Reset checker of new observations, i.e. `self.new_observation_available()` + """ + + self.__observation_mutex.acquire() + self.__new_observation_available = False + self.__observation_mutex.release() + + @property + def new_observation_available(self): + """ + Check if new observation is available since `self.reset_new_observation_checker()` was called + """ + + return self.__new_observation_available + + +class CameraSubscriberStandalone(Node, CameraSubscriber): + def __init__( + self, + topic: str, + is_point_cloud: bool, + node_name: str = "rbs_gym_camera_sub", + use_sim_time: bool = True, + ): + + try: + rclpy.init() + except Exception as e: + if not rclpy.ok(): + sys.exit(f"ROS 2 context could not be initialised: {e}") + + Node.__init__(self, node_name) + self.set_parameters( + [Parameter("use_sim_time", type_=Parameter.Type.BOOL, value=use_sim_time)] + ) + + CameraSubscriber.__init__( + self, node=self, topic=topic, is_point_cloud=is_point_cloud + ) + + # Spin the node in a separate thread + self._executor = SingleThreadedExecutor() + self._executor.add_node(self) + self._executor_thread = Thread(target=self._executor.spin, daemon=True, args=()) + self._executor_thread.start() diff --git a/env_manager/rbs_gym/rbs_gym/envs/observation/joint_states.py b/env_manager/rbs_gym/rbs_gym/envs/observation/joint_states.py new file mode 100644 index 0000000..bc1a097 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/observation/joint_states.py @@ -0,0 +1,107 @@ +from array import array +from threading import Lock +from typing import Optional + +from rclpy.callback_groups import CallbackGroup +from rclpy.node import Node +from rclpy.qos import ( + QoSDurabilityPolicy, + QoSHistoryPolicy, + QoSProfile, + QoSReliabilityPolicy, +) + +from sensor_msgs.msg import JointState + +class JointStates: + def __init__( + self, + node: Node, + topic: str, + callback_group: Optional[CallbackGroup] = None, + ): + + self._node = node + + self.__observation = JointState() + self._node.create_subscription( + msg_type=JointState, + topic=topic, + callback=self.observation_callback, + qos_profile=QoSProfile( + reliability=QoSReliabilityPolicy.RELIABLE, + durability=QoSDurabilityPolicy.VOLATILE, + history=QoSHistoryPolicy.KEEP_LAST, + depth=1, + ), + callback_group=callback_group, + ) + self.__observation_mutex = Lock() + self.__new_observation_available = False + + self.__observation.position + + def observation_callback(self, msg): + """ + Callback for getting observation. + """ + + self.__observation_mutex.acquire() + self.__observation = msg + self.__new_observation_available = True + self._node.get_logger().debug("New observation received.") + self.__observation_mutex.release() + + def get_observation(self) -> JointState: + """ + Get the last received observation. + """ + self.__observation_mutex.acquire() + observation = self.__observation + self.__observation_mutex.release() + return observation + + def get_positions(self) -> array: + """ + Get the last recorded observation position + """ + self.__observation_mutex.acquire() + observation = self.__observation.position + self.__observation_mutex.release() + return observation + + def get_velocities(self) -> array: + """ + Get the last recorded observation velocity + """ + self.__observation_mutex.acquire() + observation = self.__observation.velocity + self.__observation_mutex.release() + return observation + + def get_efforts(self) -> array: + """ + Get the last recorded observation effort + """ + self.__observation_mutex.acquire() + observation = self.__observation.effort + self.__observation_mutex.release() + return observation + + def reset_new_observation_checker(self): + """ + Reset checker of new observations, i.e. `self.new_observation_available()` + """ + + self.__observation_mutex.acquire() + self.__new_observation_available = False + self.__observation_mutex.release() + + @property + def new_observation_available(self): + """ + Check if new observation is available since `self.reset_new_observation_checker()` was called + """ + + return self.__new_observation_available + diff --git a/env_manager/rbs_gym/rbs_gym/envs/observation/octree.py b/env_manager/rbs_gym/rbs_gym/envs/observation/octree.py new file mode 100644 index 0000000..55caaaf --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/observation/octree.py @@ -0,0 +1,211 @@ +from typing import List, Tuple + +import numpy as np +import ocnn +import open3d +import torch +from rclpy.node import Node +from sensor_msgs.msg import PointCloud2 + +from env_manager.utils import Tf2Listener, conversions + + +class OctreeCreator: + def __init__( + self, + node: Node, + tf2_listener: Tf2Listener, + reference_frame_id: str, + min_bound: Tuple[float, float, float] = (-1.0, -1.0, -1.0), + max_bound: Tuple[float, float, float] = (1.0, 1.0, 1.0), + include_color: bool = False, + # Note: For efficiency, the first channel of RGB is used for intensity + include_intensity: bool = False, + depth: int = 4, + full_depth: int = 2, + adaptive: bool = False, + adp_depth: int = 4, + normals_radius: float = 0.05, + normals_max_nn: int = 10, + node_dis: bool = True, + node_feature: bool = False, + split_label: bool = False, + th_normal: float = 0.1, + th_distance: float = 2.0, + extrapolate: bool = False, + save_pts: bool = False, + key2xyz: bool = False, + debug_draw: bool = False, + debug_write_octree: bool = False, + ): + + self._node = node + + # Listener of tf2 transforms is shared with the owner + self.__tf2_listener = tf2_listener + + # Parameters + self._reference_frame_id = reference_frame_id + self._min_bound = min_bound + self._max_bound = max_bound + self._include_color = include_color + self._include_intensity = include_intensity + self._normals_radius = normals_radius + self._normals_max_nn = normals_max_nn + self._debug_draw = debug_draw + self._debug_write_octree = debug_write_octree + + # Create a converter between points and octree + self._points_to_octree = ocnn.Points2Octree( + depth=depth, + full_depth=full_depth, + node_dis=node_dis, + node_feature=node_feature, + split_label=split_label, + adaptive=adaptive, + adp_depth=adp_depth, + th_normal=th_normal, + th_distance=th_distance, + extrapolate=extrapolate, + save_pts=save_pts, + key2xyz=key2xyz, + bb_min=min_bound, + bb_max=max_bound, + ) + + def __call__(self, ros_point_cloud2: PointCloud2) -> torch.Tensor: + + # Convert to Open3D PointCloud + open3d_point_cloud = conversions.pointcloud2_to_open3d( + ros_point_cloud2=ros_point_cloud2, + include_color=self._include_color, + include_intensity=self._include_intensity, + ) + + # Preprocess point cloud (transform to robot frame, crop to workspace and estimate normals) + open3d_point_cloud = self.preprocess_point_cloud( + open3d_point_cloud=open3d_point_cloud, + camera_frame_id=ros_point_cloud2.header.frame_id, + reference_frame_id=self._reference_frame_id, + min_bound=self._min_bound, + max_bound=self._max_bound, + normals_radius=self._normals_radius, + normals_max_nn=self._normals_max_nn, + ) + + # Draw if needed + if self._debug_draw: + open3d.visualization.draw_geometries( + [ + open3d_point_cloud, + open3d.geometry.TriangleMesh.create_coordinate_frame( + size=0.2, origin=[0.0, 0.0, 0.0] + ), + ], + point_show_normal=True, + ) + + # Construct octree from such point cloud + octree = self.construct_octree( + open3d_point_cloud, + include_color=self._include_color, + include_intensity=self._include_intensity, + ) + + # Write if needed + if self._debug_write_octree: + ocnn.write_octree(octree, "octree.octree") + + return octree + + def preprocess_point_cloud( + self, + open3d_point_cloud: open3d.geometry.PointCloud, + camera_frame_id: str, + reference_frame_id: str, + min_bound: List[float], + max_bound: List[float], + normals_radius: float, + normals_max_nn: int, + ) -> open3d.geometry.PointCloud: + + # Check if point cloud has any points + if not open3d_point_cloud.has_points(): + self._node.get_logger().warn( + "Point cloud has no points. Pre-processing skipped." + ) + return open3d_point_cloud + + # Get transformation from camera to robot and use it to transform point + # cloud into robot's base coordinate frame + if camera_frame_id != reference_frame_id: + transform = self.__tf2_listener.lookup_transform_sync( + target_frame=reference_frame_id, source_frame=camera_frame_id + ) + transform_mat = conversions.transform_to_matrix(transform=transform) + open3d_point_cloud = open3d_point_cloud.transform(transform_mat) + + # Crop point cloud to include only the workspace + open3d_point_cloud = open3d_point_cloud.crop( + bounding_box=open3d.geometry.AxisAlignedBoundingBox( + min_bound=min_bound, max_bound=max_bound + ) + ) + + # Check if any points remain in the area after cropping + if not open3d_point_cloud.has_points(): + self._node.get_logger().warn( + "Point cloud has no points after cropping it to the workspace volume." + ) + return open3d_point_cloud + + # Estimate normal vector for each cloud point and orient these towards the camera + open3d_point_cloud.estimate_normals( + search_param=open3d.geometry.KDTreeSearchParamHybrid( + radius=normals_radius, max_nn=normals_max_nn + ), + fast_normal_computation=True, + ) + + open3d_point_cloud.orient_normals_towards_camera_location( + camera_location=transform_mat[0:3, 3] + ) + + return open3d_point_cloud + + def construct_octree( + self, + open3d_point_cloud: open3d.geometry.PointCloud, + include_color: bool, + include_intensity: bool, + ) -> torch.Tensor: + + # In case the point cloud has no points, add a single point + # This is a workaround because I was not able to create an empty octree without getting a segfault + # TODO: Figure out a better way of making an empty octree (it does not occur if setup correctly, so probably not worth it) + if not open3d_point_cloud.has_points(): + open3d_point_cloud.points.append( + ( + (self._min_bound[0] + self._max_bound[0]) / 2, + (self._min_bound[1] + self._max_bound[1]) / 2, + (self._min_bound[2] + self._max_bound[2]) / 2, + ) + ) + open3d_point_cloud.normals.append((0.0, 0.0, 0.0)) + if include_color or include_intensity: + open3d_point_cloud.colors.append((0.0, 0.0, 0.0)) + + # Convert open3d point cloud into octree points + octree_points = conversions.open3d_point_cloud_to_octree_points( + open3d_point_cloud=open3d_point_cloud, + include_color=include_color, + include_intensity=include_intensity, + ) + + # Convert octree points into 1D Tensor (via ndarray) + # Note: Copy of points here is necessary as ndarray would otherwise be immutable + octree_points_ndarray = np.frombuffer(np.copy(octree_points.buffer()), np.uint8) + octree_points_tensor = torch.from_numpy(octree_points_ndarray) + + # Finally, create an octree from the points + return self._points_to_octree(octree_points_tensor) diff --git a/env_manager/rbs_gym/rbs_gym/envs/observation/twist_subscriber.py b/env_manager/rbs_gym/rbs_gym/envs/observation/twist_subscriber.py new file mode 100644 index 0000000..6834a37 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/observation/twist_subscriber.py @@ -0,0 +1,81 @@ +import sys +from threading import Lock, Thread +from typing import Optional, Union + +import rclpy +from rclpy.callback_groups import CallbackGroup +from rclpy.executors import SingleThreadedExecutor +from rclpy.node import Node +from rclpy.parameter import Parameter +from rclpy.qos import ( + QoSDurabilityPolicy, + QoSHistoryPolicy, + QoSProfile, + QoSReliabilityPolicy, +) +from geometry_msgs.msg import TwistStamped + +class TwistSubscriber: + def __init__( + self, + node: Node, + topic: str, + callback_group: Optional[CallbackGroup] = None, + ): + + self._node = node + + self.__observation = TwistStamped() + self._node.create_subscription( + msg_type=TwistStamped, + topic=topic, + callback=self.observation_callback, + qos_profile=QoSProfile( + reliability=QoSReliabilityPolicy.RELIABLE, + durability=QoSDurabilityPolicy.VOLATILE, + history=QoSHistoryPolicy.KEEP_LAST, + depth=1, + ), + callback_group=callback_group, + ) + self.__observation_mutex = Lock() + self.__new_observation_available = False + + def observation_callback(self, msg): + """ + Callback for getting observation. + """ + + self.__observation_mutex.acquire() + self.__observation = msg + self.__new_observation_available = True + self._node.get_logger().debug("New observation received.") + self.__observation_mutex.release() + + def get_observation(self) -> TwistStamped: + """ + Get the last received observation. + """ + + self.__observation_mutex.acquire() + observation = self.__observation + self.__observation_mutex.release() + return observation + + def reset_new_observation_checker(self): + """ + Reset checker of new observations, i.e. `self.new_observation_available()` + """ + + self.__observation_mutex.acquire() + self.__new_observation_available = False + self.__observation_mutex.release() + + @property + def new_observation_available(self): + """ + Check if new observation is available since `self.reset_new_observation_checker()` was called + """ + + return self.__new_observation_available + diff --git a/env_manager/rbs_gym/rbs_gym/envs/randomizers/__init__.py b/env_manager/rbs_gym/rbs_gym/envs/randomizers/__init__.py new file mode 100644 index 0000000..9beec96 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/randomizers/__init__.py @@ -0,0 +1 @@ +from .manipulation import ManipulationGazeboEnvRandomizer diff --git a/env_manager/rbs_gym/rbs_gym/envs/randomizers/manipulation.py b/env_manager/rbs_gym/rbs_gym/envs/randomizers/manipulation.py new file mode 100644 index 0000000..5777a2c --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/randomizers/manipulation.py @@ -0,0 +1,345 @@ +import abc + +from env_manager.models.configs import ( + SceneData, +) +from env_manager.scene import Scene +from env_manager.utils.logging import set_log_level +from gym_gz import randomizers +from gym_gz.randomizers import gazebo_env_randomizer +from gym_gz.randomizers.gazebo_env_randomizer import MakeEnvCallable +from scenario import gazebo as scenario +from scenario.bindings.gazebo import GazeboSimulator + +from rbs_gym.envs import tasks + +SupportedTasks = tasks.Reach | tasks.ReachColorImage | tasks.ReachDepthImage + + +class ManipulationGazeboEnvRandomizer( + gazebo_env_randomizer.GazeboEnvRandomizer, + randomizers.abc.PhysicsRandomizer, + randomizers.abc.TaskRandomizer, + abc.ABC, +): + """ + Basic randomizer of environments for robotic manipulation inside Ignition Gazebo. This randomizer + also populates the simulated world with robot, terrain, lighting and other entities. + """ + + POST_RANDOMIZATION_MAX_STEPS = 50 + + metadata = {"render_modes": ["human"]} + + def __init__( + self, + env: MakeEnvCallable, + scene_args: SceneData = SceneData(), + **kwargs, + ): + self._scene_data = scene_args + # TODO (a lot of work): Implement proper physics randomization. + if scene_args.physics_rollouts_num != 0: + raise TypeError( + "Proper physics randomization at each reset is not yet implemented. Please set `physics_rollouts_num=0`." + ) + + # Update kwargs before passing them to the task constructor (some tasks might need them) + # TODO: update logic when will need choose between cameras + cameras: list[dict[str, str | int]] = [] + for camera in self._scene_data.camera: + camera_info: dict[str, str | int] = {} + camera_info["name"] = camera.name + camera_info["type"] = camera.type + camera_info["width"] = camera.width + camera_info["height"] = camera.height + cameras.append(camera_info) + + kwargs.update({"camera_info": cameras}) + + # Initialize base classes + randomizers.abc.TaskRandomizer.__init__(self) + randomizers.abc.PhysicsRandomizer.__init__( + self, randomize_after_rollouts_num=scene_args.physics_rollouts_num + ) + gazebo_env_randomizer.GazeboEnvRandomizer.__init__( + self, env=env, physics_randomizer=self, **kwargs + ) + + self.__env_initialised = False + + ########################## + # PhysicsRandomizer impl # + ########################## + + def init_physics_preset(self, task: SupportedTasks): + self.set_gravity(task=task) + + def randomize_physics(self, task: SupportedTasks, **kwargs): + self.set_gravity(task=task) + + def set_gravity(self, task: SupportedTasks): + if not task.world.to_gazebo().set_gravity( + ( + task.np_random.normal(loc=self._gravity[0], scale=self._gravity_std[0]), + task.np_random.normal(loc=self._gravity[1], scale=self._gravity_std[1]), + task.np_random.normal(loc=self._gravity[2], scale=self._gravity_std[2]), + ) + ): + raise RuntimeError("Failed to set the gravity") + + def get_engine(self): + return scenario.PhysicsEngine_dart + + ####################### + # TaskRandomizer impl # + ####################### + + def randomize_task(self, task: SupportedTasks, **kwargs): + """ + Randomization of the task, which is called on each reset of the environment. + Note that this randomizer reset is called before `reset_task()`. + """ + + # Get gazebo instance associated with the task + if "gazebo" not in kwargs: + raise ValueError("Randomizer does not have access to the gazebo interface") + if isinstance(kwargs["gazebo"], GazeboSimulator): + gazebo: GazeboSimulator = kwargs["gazebo"] + else: + raise RuntimeError("Provide GazeboSimulator instance") + + # Initialise the environment on the first iteration + if not self.__env_initialised: + self.init_env(task=task, gazebo=gazebo) + self.__env_initialised = True + + # Perform pre-randomization steps + self.pre_randomization(task=task) + + self._scene.reset_scene() + + # Perform post-randomization steps + # TODO: Something in post-randomization causes GUI client to freeze during reset (the simulation server still works fine) + self.post_randomization(task, gazebo) + + ################### + # Randomizer impl # + ################### + + # Initialisation # + def init_env(self, task: SupportedTasks, gazebo: scenario.GazeboSimulator): + """ + Initialise an instance of the environment before the very first iteration + """ + + self._scene = Scene( + task, + gazebo, + self._scene_data, + task.get_parameter("robot_description").get_parameter_value().string_value, + ) + + # Init Scene for task + task.scene = self._scene + # Set log level for (Gym) Ignition + set_log_level(log_level=task.get_logger().get_effective_level().name) + + self._scene.init_scene() + + # Pre-randomization # + def pre_randomization(self, task: SupportedTasks): + """ + Perform steps that are required before randomization is performed. + """ + + for obj in self._scene.objects: + # If desired, select random spawn position from the segments + # It is performed here because object spawn position might be of interest also for robot and camera randomization + + segments_len = len(obj.randomize.random_spawn_position_segments) + if segments_len > 1: + # Randomly select a segment between two points + start_index = task.np_random.randint(segments_len - 1) + segment = ( + obj.randomize.random_spawn_position_segments[start_index], + obj.randomize.random_spawn_position_segments[start_index + 1], + ) + + # Randomly select a point on the segment and use it as the new object spawn position + intersect = task.np_random.random() + direction = ( + segment[1][0] - segment[0][0], + segment[1][1] - segment[0][1], + segment[1][2] - segment[0][2], + ) + obj.position = ( + segment[0][0] + intersect * direction[0], + segment[0][1] + intersect * direction[1], + segment[0][2] + intersect * direction[2], + ) + + # TODO: add bounding box with multiple objects + + # # Update also the workspace centre (and bounding box) if desired + # if self._object_random_spawn_position_update_workspace_centre: + # task.workspace_centre = ( + # self._object_spawn_position[0], + # self._object_spawn_position[1], + # # Z workspace is currently kept the same on purpose + # task.workspace_centre[2], + # ) + # workspace_volume_half = ( + # task.workspace_volume[0] / 2, + # task.workspace_volume[1] / 2, + # task.workspace_volume[2] / 2, + # ) + # task.workspace_min_bound = ( + # task.workspace_centre[0] - workspace_volume_half[0], + # task.workspace_centre[1] - workspace_volume_half[1], + # task.workspace_centre[2] - workspace_volume_half[2], + # ) + # task.workspace_max_bound = ( + # task.workspace_centre[0] + workspace_volume_half[0], + # task.workspace_centre[1] + workspace_volume_half[1], + # task.workspace_centre[2] + workspace_volume_half[2], + # ) + + def post_randomization( + self, task: SupportedTasks, gazebo: scenario.GazeboSimulator + ): + """ + Perform steps required once randomization is complete and the simulation can be stepped unpaused. + """ + + def perform_gazebo_step(): + if not gazebo.step(): + raise RuntimeError("Failed to execute an unpaused Gazebo step") + + def wait_for_new_observations(): + attempts = 0 + while True: + attempts += 1 + if attempts % self.POST_RANDOMIZATION_MAX_STEPS == 0: + task.get_logger().debug( + f"Waiting for new joint state after reset. Iteration #{attempts}..." + ) + else: + task.get_logger().debug("Waiting for new joint state after reset.") + + perform_gazebo_step() + + # If camera_sub is defined, ensure all new observations are available + if hasattr(task, "camera_subs") and not all( + sub.new_observation_available for sub in task.camera_subs + ): + continue + + return # Observations are ready + + attempts = 0 + processed_objects = set() + + # Early exit if the maximum number of steps is already reached + if self.POST_RANDOMIZATION_MAX_STEPS == 0: + task.get_logger().error( + "Robot keeps falling through the terrain. There is something wrong..." + ) + return + + # Ensure no objects are overlapping + for obj in self._scene.objects: + if not obj.randomize.random_pose or obj.name in processed_objects: + continue + + # Try repositioning until no overlap or maximum attempts reached + for _ in range(self.POST_RANDOMIZATION_MAX_STEPS): + task.get_logger().debug( + f"Checking overlap for {obj.name}, attempt {attempts + 1}" + ) + if self._scene.check_object_overlapping(obj): + processed_objects.add(obj.name) + break # No overlap, move to next object + else: + task.get_logger().debug( + f"Objects overlapping, trying new positions for {obj.name}" + ) + + perform_gazebo_step() + + else: + task.get_logger().warn( + f"Could not place {obj.name} without overlap after {self.POST_RANDOMIZATION_MAX_STEPS} attempts" + ) + continue # Move to next object in case of failure + + # Execute steps until new observations are available + if hasattr(task, "camera_subs") or task._enable_gripper: + wait_for_new_observations() + + # Final check if observations are not available within the maximum steps + if self.POST_RANDOMIZATION_MAX_STEPS == attempts: + task.get_logger().error("Cannot obtain new observation.") + + # ============================= + # Additional features and debug + # ============================= + + # def visualise_workspace( + # self, + # task: SupportedTasks, + # gazebo: scenario.GazeboSimulator, + # color: Tuple[float, float, float, float] = (0, 1, 0, 0.8), + # ): + # # Insert a translucent box visible only in simulation with no physical interactions + # models.Box( + # world=task.world, + # name="_workspace_volume", + # position=self._object_spawn_position, + # orientation=(0, 0, 0, 1), + # size=task.workspace_volume, + # collision=False, + # visual=True, + # gui_only=True, + # static=True, + # color=color, + # ) + # # Execute a paused run to process model insertion + # if not gazebo.run(paused=True): + # raise RuntimeError("Failed to execute a paused Gazebo run") + # + # def visualise_spawn_volume( + # self, + # task: SupportedTasks, + # gazebo: scenario.GazeboSimulator, + # color: Tuple[float, float, float, float] = (0, 0, 1, 0.8), + # color_with_height: Tuple[float, float, float, float] = (1, 0, 1, 0.7), + # ): + # # Insert translucent boxes visible only in simulation with no physical interactions + # models.Box( + # world=task.world, + # name="_object_random_spawn_volume", + # position=self._object_spawn_position, + # orientation=(0, 0, 0, 1), + # size=self._object_random_spawn_volume, + # collision=False, + # visual=True, + # gui_only=True, + # static=True, + # color=color, + # ) + # models.Box( + # world=task.world, + # name="_object_random_spawn_volume_with_height", + # position=self._object_spawn_position, + # orientation=(0, 0, 0, 1), + # size=self._object_random_spawn_volume, + # collision=False, + # visual=True, + # gui_only=True, + # static=True, + # color=color_with_height, + # ) + # # Execute a paused run to process model insertion + # if not gazebo.run(paused=True): + # raise RuntimeError("Failed to execute a paused Gazebo run") diff --git a/env_manager/rbs_gym/rbs_gym/envs/tasks/__init__.py b/env_manager/rbs_gym/rbs_gym/envs/tasks/__init__.py new file mode 100644 index 0000000..15d114f --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/tasks/__init__.py @@ -0,0 +1,4 @@ +# from .curriculums import * +# from .grasp import * +# from .grasp_planetary import * +from .reach import * diff --git a/env_manager/rbs_gym/rbs_gym/envs/tasks/curriculums/__init__.py b/env_manager/rbs_gym/rbs_gym/envs/tasks/curriculums/__init__.py new file mode 100644 index 0000000..3e3828e --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/tasks/curriculums/__init__.py @@ -0,0 +1 @@ +from .grasp import GraspCurriculum diff --git a/env_manager/rbs_gym/rbs_gym/envs/tasks/curriculums/common.py b/env_manager/rbs_gym/rbs_gym/envs/tasks/curriculums/common.py new file mode 100644 index 0000000..5caf7bc --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/tasks/curriculums/common.py @@ -0,0 +1,700 @@ +from __future__ import annotations + +import enum +import itertools +import math +from collections import deque +from typing import Callable, Deque, Dict, Optional, Tuple, Type + +import numpy as np +from gym_gz.base.task import Task +from gym_gz.utils.typing import Reward +from tf2_ros.buffer_interface import TypeException + +INFO_MEAN_STEP_KEY: str = "__mean_step__" +INFO_MEAN_EPISODE_KEY: str = "__mean_episode__" + + +@enum.unique +class CurriculumStage(enum.Enum): + """ + Ordered enum that represents stages of a curriculum for RL task. + """ + + @classmethod + def first(self) -> CurriculumStage: + + return self(1) + + @classmethod + def last(self) -> CurriculumStage: + + return self(len(self)) + + def next(self) -> Optional[CurriculumStage]: + + next_value = self.value + 1 + + if next_value > self.last().value: + return None + else: + return self(next_value) + + def previous(self) -> Optional[CurriculumStage]: + + previous_value = self.value - 1 + + if previous_value < self.first().value: + return None + else: + return self(previous_value) + + +class StageRewardCurriculum: + """ + Curriculum that begins to compute rewards for a stage once all previous stages are complete. + """ + + PERSISTENT_ID: str = "PERSISTENT" + INFO_CURRICULUM_PREFIX: str = "curriculum/" + + def __init__( + self, + curriculum_stage: Type[CurriculumStage], + stage_reward_multiplier: float, + dense_reward: bool = False, + **kwargs, + ): + + if 0 == len(curriculum_stage): + raise TypeException(f"{curriculum_stage} has length of 0") + + self.__use_dense_reward = dense_reward + if self.__use_dense_reward: + raise ValueError( + "Dense reward is currently not implemented for any curriculum" + ) + + # Setup internals + self._stage_type = curriculum_stage + self._stage_reward_functions: Dict[curriculum_stage, Callable] = { + curriculum_stage(stage): getattr(self, f"get_reward_{stage.name}") + for stage in iter(curriculum_stage) + } + self.__stage_reward_multipliers: Dict[curriculum_stage, float] = { + curriculum_stage(stage): stage_reward_multiplier ** (stage.value - 1) + for stage in iter(curriculum_stage) + } + + self.stages_completed_this_episode: Dict[curriculum_stage, bool] = { + curriculum_stage(stage): False for stage in iter(curriculum_stage) + } + self.__stages_rewards_this_episode: Dict[curriculum_stage, float] = { + curriculum_stage(stage): 0.0 for stage in iter(curriculum_stage) + } + self.__stages_rewards_this_episode[self.PERSISTENT_ID] = 0.0 + + self.__episode_succeeded: bool = False + self.__episode_failed: bool = False + + def get_reward(self, only_last_stage: bool = False, **kwargs) -> Reward: + + reward = 0.0 + + # Determine the stage at which to start computing reward [performance - done stages give no reward] + if only_last_stage: + first_stage_to_process = self._stage_type.last() + else: + for stage in iter(self._stage_type): + if not self.stages_completed_this_episode[stage]: + first_stage_to_process = stage + break + + # Iterate over all stages that might need to be processed + for stage in range(first_stage_to_process.value, len(self._stage_type) + 1): + stage = self._stage_type(stage) + + # Compute reward for the current stage + stage_reward = self._stage_reward_functions[stage](**kwargs) + # Multiply by the reward multiplier + stage_reward *= self.__stage_reward_multipliers[stage] + # Add to the total step reward + reward += stage_reward + # Add reward to the list for info + self.__stages_rewards_this_episode[stage] += stage_reward + + # Break if stage is not yet completed [performance - next stages won't give any reward] + if not self.stages_completed_this_episode[stage]: + break + + # If the last stage is complete, the episode has succeeded + self.__episode_succeeded = self.stages_completed_this_episode[ + self._stage_type.last() + ] + if self.__episode_succeeded: + return reward + + # Add persistent reward that is added regardless of the episode (unless task already succeeded) + persistent_reward = self.get_persistent_reward(**kwargs) + # Add to the total step reward + reward += persistent_reward + # Add reward to the list for info + self.__stages_rewards_this_episode[self.PERSISTENT_ID] += persistent_reward + + return reward + + def is_done(self) -> bool: + + if self.__episode_succeeded: + # The episode ended with success + self.on_episode_success() + return True + elif self.__episode_failed: + # The episode ended due to failure + self.on_episode_failure() + return True + else: + # Otherwise, the episode is not yet done + return False + + def get_info(self) -> Dict: + + # Whether the episode succeeded + info = { + "is_success": self.__episode_succeeded, + } + + # What stage was reached during this episode so far + for stage in iter(self._stage_type): + reached_stage = stage + if not self.stages_completed_this_episode[stage]: + break + info.update( + { + f"{self.INFO_CURRICULUM_PREFIX}{INFO_MEAN_EPISODE_KEY}ep_reached_stage_mean": reached_stage.value, + } + ) + + # Rewards for the individual stages + info.update( + { + f"{self.INFO_CURRICULUM_PREFIX}{INFO_MEAN_EPISODE_KEY}ep_rew_mean_{stage.value}_{stage.name.lower()}": self.__stages_rewards_this_episode[ + stage + ] + for stage in iter(self._stage_type) + } + ) + info.update( + { + f"{self.INFO_CURRICULUM_PREFIX}{INFO_MEAN_EPISODE_KEY}ep_rew_mean_{self.PERSISTENT_ID.lower()}": self.__stages_rewards_this_episode[ + self.PERSISTENT_ID + ] + } + ) + + return info + + def reset_task(self): + + if not (self.__episode_succeeded or self.__episode_failed): + # The episode ended due to timeout + self.on_episode_timeout() + + # Reset internals + self.stages_completed_this_episode = dict.fromkeys( + self.stages_completed_this_episode, False + ) + self.__stages_rewards_this_episode = dict.fromkeys( + self.__stages_rewards_this_episode, 0.0 + ) + self.__stages_rewards_this_episode[self.PERSISTENT_ID] = 0.0 + self.__episode_succeeded = False + self.__episode_failed = False + + @property + def episode_succeeded(self) -> bool: + + return self.__episode_succeeded + + @episode_succeeded.setter + def episode_succeeded(self, value: bool): + + self.__episode_succeeded = value + + @property + def episode_failed(self) -> bool: + + return self.__episode_failed + + @episode_failed.setter + def episode_failed(self, value: bool): + + self.__episode_failed = value + + @property + def use_dense_reward(self) -> bool: + + return self.__use_dense_reward + + def get_persistent_reward(self, **kwargs) -> float: + """ + Virtual method. + """ + + reward = 0.0 + + return reward + + def on_episode_success(self): + """ + Virtual method. + """ + + pass + + def on_episode_failure(self): + """ + Virtual method. + """ + + pass + + def on_episode_timeout(self): + """ + Virtual method. + """ + + pass + + +class SuccessRateImpl: + """ + Moving average over the success rate of last N episodes. + """ + + INFO_CURRICULUM_PREFIX: str = "curriculum/" + + def __init__( + self, + initial_success_rate: float = 0.0, + rolling_average_n: int = 100, + **kwargs, + ): + + self.__success_rate = initial_success_rate + self.__rolling_average_n = rolling_average_n + + # Setup internals + self.__previous_success_rate_weight: int = 0 + self.__collected_samples: int = 0 + + def get_info(self) -> Dict: + + info = { + f"{self.INFO_CURRICULUM_PREFIX}_success_rate": self.__success_rate, + } + + return info + + def update_success_rate(self, is_success: bool): + + # Until `rolling_average_n` is reached, use number of collected samples during computations + if self.__collected_samples < self.__rolling_average_n: + self.__previous_success_rate_weight = self.__collected_samples + self.__collected_samples += 1 + + self.__success_rate = ( + self.__previous_success_rate_weight * self.__success_rate + + float(is_success) + ) / self.__collected_samples + + @property + def success_rate(self) -> float: + + return self.__success_rate + + +class WorkspaceScaleCurriculum: + """ + Curriculum that increases the workspace size as the success rate increases. + """ + + INFO_CURRICULUM_PREFIX: str = "curriculum/" + + def __init__( + self, + task: Task, + success_rate_impl: SuccessRateImpl, + min_workspace_scale: float, + max_workspace_volume: Tuple[float, float, float], + max_workspace_scale_success_rate_threshold: float, + **kwargs, + ): + + self.__task = task + self.__success_rate_impl = success_rate_impl + self.__min_workspace_scale = min_workspace_scale + self.__max_workspace_volume = max_workspace_volume + self.__max_workspace_scale_success_rate_threshold = ( + max_workspace_scale_success_rate_threshold + ) + + def get_info(self) -> Dict: + + info = { + f"{self.INFO_CURRICULUM_PREFIX}{INFO_MEAN_EPISODE_KEY}workspace_scale": self.__workspace_scale, + } + + return info + + def reset_task(self): + + # Update workspace size + self.__update_workspace_size() + + def __update_workspace_size(self): + + self.__workspace_scale = min( + 1.0, + max( + self.__min_workspace_scale, + self.__success_rate_impl.success_rate + / self.__max_workspace_scale_success_rate_threshold, + ), + ) + + workspace_volume_new = ( + self.__workspace_scale * self.__max_workspace_volume[0], + self.__workspace_scale * self.__max_workspace_volume[1], + # Z workspace is currently kept the same on purpose + self.__max_workspace_volume[2], + ) + workspace_volume_half_new = ( + workspace_volume_new[0] / 2, + workspace_volume_new[1] / 2, + workspace_volume_new[2] / 2, + ) + workspace_min_bound_new = ( + self.__task.workspace_centre[0] - workspace_volume_half_new[0], + self.__task.workspace_centre[1] - workspace_volume_half_new[1], + self.__task.workspace_centre[2] - workspace_volume_half_new[2], + ) + workspace_max_bound_new = ( + self.__task.workspace_centre[0] + workspace_volume_half_new[0], + self.__task.workspace_centre[1] + workspace_volume_half_new[1], + self.__task.workspace_centre[2] + workspace_volume_half_new[2], + ) + + self.__task.add_task_parameter_overrides( + { + "workspace_volume": workspace_volume_new, + "workspace_min_bound": workspace_min_bound_new, + "workspace_max_bound": workspace_max_bound_new, + } + ) + + +class ObjectSpawnVolumeScaleCurriculum: + """ + Curriculum that increases the object spawn volume as the success rate increases. + """ + + INFO_CURRICULUM_PREFIX: str = "curriculum/" + + def __init__( + self, + task: Task, + success_rate_impl: SuccessRateImpl, + min_object_spawn_volume_scale: float, + max_object_spawn_volume: Tuple[float, float, float], + max_object_spawn_volume_scale_success_rate_threshold: float, + **kwargs, + ): + + self.__task = task + self.__success_rate_impl = success_rate_impl + self.__min_object_spawn_volume_scale = min_object_spawn_volume_scale + self.__max_object_spawn_volume = max_object_spawn_volume + self.__max_object_spawn_volume_scale_success_rate_threshold = ( + max_object_spawn_volume_scale_success_rate_threshold + ) + + def get_info(self) -> Dict: + + info = { + f"{self.INFO_CURRICULUM_PREFIX}{INFO_MEAN_EPISODE_KEY}object_spawn_volume_scale": self.__object_spawn_volume_scale, + } + + return info + + def reset_task(self): + + # Update object_spawn_volume size + self.__update_object_spawn_volume_size() + + def __update_object_spawn_volume_size(self): + + self.__object_spawn_volume_scale = min( + 1.0, + max( + self.__min_object_spawn_volume_scale, + self.__success_rate_impl.success_rate + / self.__max_object_spawn_volume_scale_success_rate_threshold, + ), + ) + + object_spawn_volume_volume_new = ( + self.__object_spawn_volume_scale * self.__max_object_spawn_volume[0], + self.__object_spawn_volume_scale * self.__max_object_spawn_volume[1], + self.__object_spawn_volume_scale * self.__max_object_spawn_volume[2], + ) + + self.__task.add_randomizer_parameter_overrides( + { + "object_random_spawn_volume": object_spawn_volume_volume_new, + } + ) + + +class ObjectCountCurriculum: + """ + Curriculum that increases the number of objects as the success rate increases. + """ + + INFO_CURRICULUM_PREFIX: str = "curriculum/" + + def __init__( + self, + task: Task, + success_rate_impl: SuccessRateImpl, + object_count_min: int, + object_count_max: int, + max_object_count_success_rate_threshold: float, + **kwargs, + ): + + self.__task = task + self.__success_rate_impl = success_rate_impl + self.__object_count_min = object_count_min + self.__object_count_max = object_count_max + self.__max_object_count_success_rate_threshold = ( + max_object_count_success_rate_threshold + ) + + self.__object_count_min_max_diff = object_count_max - object_count_min + if self.__object_count_min_max_diff < 0: + raise Exception( + "'object_count_min' cannot be larger than 'object_count_max'" + ) + + def get_info(self) -> Dict: + + info = { + f"{self.INFO_CURRICULUM_PREFIX}object_count": self.__object_count, + } + + return info + + def reset_task(self): + + # Update object count + self.__update_object_count() + + def __update_object_count(self): + + self.__object_count = min( + self.__object_count_max, + math.floor( + self.__object_count_min + + ( + self.__success_rate_impl.success_rate + / self.__max_object_count_success_rate_threshold + ) + * self.__object_count_min_max_diff + ), + ) + + self.__task.add_randomizer_parameter_overrides( + { + "object_count": self.__object_count, + } + ) + + +class ArmStuckChecker: + """ + Checker for arm getting stuck. + """ + + INFO_CURRICULUM_PREFIX: str = "curriculum/" + + def __init__( + self, + task: Task, + arm_stuck_n_steps: int, + arm_stuck_min_joint_difference_norm: float, + **kwargs, + ): + + self.__task = task + self.__arm_stuck_min_joint_difference_norm = arm_stuck_min_joint_difference_norm + + # List of previous join positions (used to compute difference norm with an older previous reading) + self.__previous_joint_positions: Deque[np.ndarray] = deque( + [], maxlen=arm_stuck_n_steps + ) + # Counter of how many time the robot got stuck + self.__robot_stuck_total_counter: int = 0 + + # Initialize list of indices for the arm. + # It is assumed that these indices do not change during the operation + self.__arm_joint_indices = None + + def get_info(self) -> Dict: + + info = { + f"{self.INFO_CURRICULUM_PREFIX}robot_stuck_count": self.__robot_stuck_total_counter, + } + + return info + + def reset_task(self): + + self.__previous_joint_positions.clear() + + joint_positions = self.__get_arm_joint_positions() + if joint_positions is not None: + self.__previous_joint_positions.append(joint_positions) + + def is_robot_stuck(self) -> bool: + + # Get current position and append to the list of previous ones + current_joint_positions = self.__get_arm_joint_positions() + if current_joint_positions is not None: + self.__previous_joint_positions.append(current_joint_positions) + + # Stop checking if there is not yet enough entries in the list + if ( + len(self.__previous_joint_positions) + < self.__previous_joint_positions.maxlen + ): + return False + + # Make sure the length of joint position matches + if len(current_joint_positions) != len(self.__previous_joint_positions[0]): + return False + + # Compute joint difference norm only with the `t - arm_stuck_n_steps` entry first (performance reason) + joint_difference_norm = np.linalg.norm( + current_joint_positions - self.__previous_joint_positions[0] + ) + + # If the difference is large enough, the arm does not appear to be stuck, so skip computing all other entries + if joint_difference_norm > self.__arm_stuck_min_joint_difference_norm: + return False + + # If it is too small, consider all other entries as well + joint_difference_norms = np.linalg.norm( + current_joint_positions + - list(itertools.islice(self.__previous_joint_positions, 1, None)), + axis=1, + ) + + # Return true (stuck) if all joint difference entries are too small + is_stuck = all( + joint_difference_norms < self.__arm_stuck_min_joint_difference_norm + ) + self.__robot_stuck_total_counter += int(is_stuck) + return is_stuck + + def __get_arm_joint_positions(self) -> Optional[np.ndarray[float]]: + + joint_state = self.__task.moveit2.joint_state + + if joint_state is None: + return None + + if self.__arm_joint_indices is None: + self.__arm_joint_indices = [ + i + for i, joint_name in enumerate(joint_state.name) + if joint_name in self.__task.robot_arm_joint_names + ] + + return np.take(joint_state.position, self.__arm_joint_indices) + + +class AttributeCurriculum: + """ + Curriculum that increases the value of an attribute (e.g. requirement) as the success rate increases. + Currently support only attributes that are increasing. + """ + + INFO_CURRICULUM_PREFIX: str = "curriculum/" + + def __init__( + self, + success_rate_impl: SuccessRateImpl, + attribute_owner: Type, + attribute_name: str, + initial_value: float, + target_value: float, + target_value_threshold: float, + **kwargs, + ): + + self.__success_rate_impl = success_rate_impl + self.__attribute_owner = attribute_owner + self.__attribute_name = attribute_name + self.__initial_value = initial_value + self.__target_value_threshold = target_value_threshold + + # Initialise current value of the attribute + self.__current_value = initial_value + + # Store difference for faster computations + self.__value_diff = target_value - initial_value + + def get_info(self) -> Dict: + + info = { + f"{self.INFO_CURRICULUM_PREFIX}{self.__attribute_name}": self.__current_value, + } + + return info + + def reset_task(self): + + # Update object count + self.__update_attribute() + + def __update_attribute(self): + + scale = min( + 1.0, + max( + self.__initial_value, + self.__success_rate_impl.success_rate / self.__target_value_threshold, + ), + ) + + self.__current_value = self.__initial_value + (scale * self.__value_diff) + + if hasattr(self.__attribute_owner, self.__attribute_name): + setattr(self.__attribute_owner, self.__attribute_name, self.__current_value) + elif hasattr(self.__attribute_owner, f"_{self.__attribute_name}"): + setattr( + self.__attribute_owner, + f"_{self.__attribute_name}", + self.__current_value, + ) + elif hasattr(self.__attribute_owner, f"__{self.__attribute_name}"): + setattr( + self.__attribute_owner, + f"__{self.__attribute_name}", + self.__current_value, + ) + else: + raise Exception( + f"Attribute owner '{self.__attribute_owner}' does not have any attribute named {self.__attribute_name}." + ) diff --git a/env_manager/rbs_gym/rbs_gym/envs/tasks/curriculums/grasp.py b/env_manager/rbs_gym/rbs_gym/envs/tasks/curriculums/grasp.py new file mode 100644 index 0000000..bd6a751 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/tasks/curriculums/grasp.py @@ -0,0 +1,341 @@ +from typing import Dict, List, Tuple + +from gym_gz.base.task import Task + +from rbs_gym.envs.tasks.curriculums.common import * +from rbs_gym.envs.utils.math import distance_to_nearest_point + + +class GraspStage(CurriculumStage): + """ + Ordered enum that represents stages of a curriculum for Grasp (and GraspPlanetary) task. + """ + + REACH = 1 + TOUCH = 2 + GRASP = 3 + LIFT = 4 + + +class GraspCurriculum( + StageRewardCurriculum, + SuccessRateImpl, + WorkspaceScaleCurriculum, + ObjectSpawnVolumeScaleCurriculum, + ObjectCountCurriculum, + ArmStuckChecker, +): + """ + Curriculum learning implementation for grasp task that provides termination (success/fail) and reward for each stage of the task. + """ + + def __init__( + self, + task: Task, + stages_base_reward: float, + reach_required_distance: float, + lift_required_height: float, + persistent_reward_each_step: float, + persistent_reward_terrain_collision: float, + persistent_reward_all_objects_outside_workspace: float, + persistent_reward_arm_stuck: float, + enable_stage_reward_curriculum: bool, + enable_workspace_scale_curriculum: bool, + enable_object_spawn_volume_scale_curriculum: bool, + enable_object_count_curriculum: bool, + reach_required_distance_min: Optional[float] = None, + reach_required_distance_max: Optional[float] = None, + reach_required_distance_max_threshold: Optional[float] = None, + lift_required_height_min: Optional[float] = None, + lift_required_height_max: Optional[float] = None, + lift_required_height_max_threshold: Optional[float] = None, + **kwargs, + ): + + StageRewardCurriculum.__init__(self, curriculum_stage=GraspStage, **kwargs) + SuccessRateImpl.__init__(self, **kwargs) + WorkspaceScaleCurriculum.__init__( + self, task=task, success_rate_impl=self, **kwargs + ) + ObjectSpawnVolumeScaleCurriculum.__init__( + self, task=task, success_rate_impl=self, **kwargs + ) + ObjectCountCurriculum.__init__( + self, task=task, success_rate_impl=self, **kwargs + ) + ArmStuckChecker.__init__(self, task=task, **kwargs) + + # Grasp task/environment that will be used to extract information from the scene + self.__task = task + + # Parameters + self.__stages_base_reward = stages_base_reward + self.reach_required_distance = reach_required_distance + self.lift_required_height = lift_required_height + self.__persistent_reward_each_step = persistent_reward_each_step + self.__persistent_reward_terrain_collision = persistent_reward_terrain_collision + self.__persistent_reward_all_objects_outside_workspace = ( + persistent_reward_all_objects_outside_workspace + ) + self.__persistent_reward_arm_stuck = persistent_reward_arm_stuck + self.__enable_stage_reward_curriculum = enable_stage_reward_curriculum + self.__enable_workspace_scale_curriculum = enable_workspace_scale_curriculum + self.__enable_object_spawn_volume_scale_curriculum = ( + enable_object_spawn_volume_scale_curriculum + ) + self.__enable_object_count_curriculum = enable_object_count_curriculum + + # Make sure that the persistent rewards for each step are negative + if self.__persistent_reward_each_step > 0.0: + self.__persistent_reward_each_step *= -1.0 + if self.__persistent_reward_terrain_collision > 0.0: + self.__persistent_reward_terrain_collision *= -1.0 + if self.__persistent_reward_all_objects_outside_workspace > 0.0: + self.__persistent_reward_all_objects_outside_workspace *= -1.0 + if self.__persistent_reward_arm_stuck > 0.0: + self.__persistent_reward_arm_stuck *= -1.0 + + # Setup curriculum for Reach distance requirement (if enabled) + reach_required_distance_min = ( + reach_required_distance_min + if reach_required_distance_min is not None + else reach_required_distance + ) + reach_required_distance_max = ( + reach_required_distance_max + if reach_required_distance_max is not None + else reach_required_distance + ) + reach_required_distance_max_threshold = ( + reach_required_distance_max_threshold + if reach_required_distance_max_threshold is not None + else 0.5 + ) + self.__reach_required_distance_curriculum_enabled = ( + not reach_required_distance_min == reach_required_distance_max + ) + if self.__reach_required_distance_curriculum_enabled: + self.__reach_required_distance_curriculum = AttributeCurriculum( + success_rate_impl=self, + attribute_owner=self, + attribute_name="reach_required_distance", + initial_value=reach_required_distance_min, + target_value=reach_required_distance_max, + target_value_threshold=reach_required_distance_max_threshold, + ) + + # Setup curriculum for Lift height requirement (if enabled) + lift_required_height_min = ( + lift_required_height_min + if lift_required_height_min is not None + else lift_required_height + ) + lift_required_height_max = ( + lift_required_height_max + if lift_required_height_max is not None + else lift_required_height + ) + lift_required_height_max_threshold = ( + lift_required_height_max_threshold + if lift_required_height_max_threshold is not None + else 0.5 + ) + # Offset Lift height requirement by the robot base offset + lift_required_height += task.robot_model_class.BASE_LINK_Z_OFFSET + lift_required_height_min += task.robot_model_class.BASE_LINK_Z_OFFSET + lift_required_height_max += task.robot_model_class.BASE_LINK_Z_OFFSET + lift_required_height_max_threshold += task.robot_model_class.BASE_LINK_Z_OFFSET + + self.__lift_required_height_curriculum_enabled = ( + not lift_required_height_min == lift_required_height_max + ) + if self.__lift_required_height_curriculum_enabled: + self.__lift_required_height_curriculum = AttributeCurriculum( + success_rate_impl=self, + attribute_owner=self, + attribute_name="lift_required_height", + initial_value=lift_required_height_min, + target_value=lift_required_height_max, + target_value_threshold=lift_required_height_max_threshold, + ) + + def get_reward(self) -> Reward: + + if self.__enable_stage_reward_curriculum: + # Try to get reward from each stage + return StageRewardCurriculum.get_reward( + self, + ee_position=self.__task.get_ee_position(), + object_positions=self.__task.get_object_positions(), + touched_objects=self.__task.get_touched_objects(), + grasped_objects=self.__task.get_grasped_objects(), + ) + else: + # If curriculum for stages is disabled, compute reward only for the last stage + return StageRewardCurriculum.get_reward( + self, + only_last_stage=True, + object_positions=self.__task.get_object_positions(), + grasped_objects=self.__task.get_grasped_objects(), + ) + + def is_done(self) -> bool: + + return StageRewardCurriculum.is_done(self) + + def get_info(self) -> Dict: + + info = StageRewardCurriculum.get_info(self) + info.update(SuccessRateImpl.get_info(self)) + if self.__enable_workspace_scale_curriculum: + info.update(WorkspaceScaleCurriculum.get_info(self)) + if self.__enable_object_spawn_volume_scale_curriculum: + info.update(ObjectSpawnVolumeScaleCurriculum.get_info(self)) + if self.__enable_object_count_curriculum: + info.update(ObjectCountCurriculum.get_info(self)) + if self.__persistent_reward_arm_stuck: + info.update(ArmStuckChecker.get_info(self)) + if self.__reach_required_distance_curriculum_enabled: + info.update(self.__reach_required_distance_curriculum.get_info()) + if self.__lift_required_height_curriculum_enabled: + info.update(self.__lift_required_height_curriculum.get_info()) + + return info + + def reset_task(self): + + StageRewardCurriculum.reset_task(self) + if self.__enable_workspace_scale_curriculum: + WorkspaceScaleCurriculum.reset_task(self) + if self.__enable_object_spawn_volume_scale_curriculum: + ObjectSpawnVolumeScaleCurriculum.reset_task(self) + if self.__enable_object_count_curriculum: + ObjectCountCurriculum.reset_task(self) + if self.__persistent_reward_arm_stuck: + ArmStuckChecker.reset_task(self) + if self.__reach_required_distance_curriculum_enabled: + self.__reach_required_distance_curriculum.reset_task() + if self.__lift_required_height_curriculum_enabled: + self.__lift_required_height_curriculum.reset_task() + + def on_episode_success(self): + + self.update_success_rate(is_success=True) + + def on_episode_failure(self): + + self.update_success_rate(is_success=False) + + def on_episode_timeout(self): + + self.update_success_rate(is_success=False) + + def get_reward_REACH( + self, + ee_position: Tuple[float, float, float], + object_positions: Dict[str, Tuple[float, float, float]], + **kwargs, + ) -> float: + + if not object_positions: + return 0.0 + + nearest_object_distance = distance_to_nearest_point( + origin=ee_position, points=list(object_positions.values()) + ) + + self.__task.get_logger().debug( + f"[Curriculum] Distance to nearest object: {nearest_object_distance}" + ) + if nearest_object_distance < self.reach_required_distance: + self.__task.get_logger().info( + f"[Curriculum] An object is now closer than the required distance of {self.reach_required_distance}" + ) + self.stages_completed_this_episode[GraspStage.REACH] = True + return self.__stages_base_reward + else: + return 0.0 + + def get_reward_TOUCH(self, touched_objects: List[str], **kwargs) -> float: + + if touched_objects: + self.__task.get_logger().info( + f"[Curriculum] Touched objects: {touched_objects}" + ) + self.stages_completed_this_episode[GraspStage.TOUCH] = True + return self.__stages_base_reward + else: + return 0.0 + + def get_reward_GRASP(self, grasped_objects: List[str], **kwargs) -> float: + + if grasped_objects: + self.__task.get_logger().info( + f"[Curriculum] Grasped objects: {grasped_objects}" + ) + self.stages_completed_this_episode[GraspStage.GRASP] = True + return self.__stages_base_reward + else: + return 0.0 + + def get_reward_LIFT( + self, + object_positions: Dict[str, Tuple[float, float, float]], + grasped_objects: List[str], + **kwargs, + ) -> float: + + if not (grasped_objects or object_positions): + return 0.0 + + for grasped_object in grasped_objects: + grasped_object_height = object_positions[grasped_object][2] + + self.__task.get_logger().debug( + f"[Curriculum] Height of grasped object '{grasped_objects}': {grasped_object_height}" + ) + if grasped_object_height > self.lift_required_height: + self.__task.get_logger().info( + f"[Curriculum] Lifted object: {grasped_object}" + ) + self.stages_completed_this_episode[GraspStage.LIFT] = True + return self.__stages_base_reward + + return 0.0 + + def get_persistent_reward( + self, object_positions: Dict[str, Tuple[float, float, float]], **kwargs + ) -> float: + + # Subtract a small reward each step to provide incentive to act quickly + reward = self.__persistent_reward_each_step + + # Negative reward for colliding with terrain + if self.__persistent_reward_terrain_collision: + if self.__task.check_terrain_collision(): + self.__task.get_logger().info( + "[Curriculum] Robot collided with the terrain" + ) + reward += self.__persistent_reward_terrain_collision + + # Negative reward for having all objects outside of the workspace + if self.__persistent_reward_all_objects_outside_workspace: + if self.__task.check_all_objects_outside_workspace( + object_positions=object_positions + ): + self.__task.get_logger().warn( + "[Curriculum] All objects are outside of the workspace" + ) + reward += self.__persistent_reward_all_objects_outside_workspace + self.episode_failed = True + + # Negative reward for arm getting stuck + if self.__persistent_reward_arm_stuck: + if ArmStuckChecker.is_robot_stuck(self): + self.__task.get_logger().error( + f"[Curriculum] Robot appears to be stuck, resetting..." + ) + reward += self.__persistent_reward_arm_stuck + self.episode_failed = True + + return reward diff --git a/env_manager/rbs_gym/rbs_gym/envs/tasks/manipulation.py b/env_manager/rbs_gym/rbs_gym/envs/tasks/manipulation.py new file mode 100644 index 0000000..b1bb7a0 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/tasks/manipulation.py @@ -0,0 +1,707 @@ +import abc +import multiprocessing +import sys +from itertools import count +from threading import Thread +from typing import Any, Dict, Optional, Tuple, Union + +import numpy as np +import rclpy +from env_manager.models.configs import RobotData +from env_manager.models.robots import RobotWrapper, get_robot_model_class +from env_manager.scene import Scene +from env_manager.utils import Tf2Broadcaster, Tf2Listener +from env_manager.utils.conversions import orientation_6d_to_quat +from env_manager.utils.gazebo import ( + Point, + Pose, + Quat, + get_model_orientation, + get_model_pose, + get_model_position, + transform_change_reference_frame_orientation, + transform_change_reference_frame_pose, + transform_change_reference_frame_position, +) +from env_manager.utils.math import quat_mul +from gym_gz.base.task import Task +from gym_gz.scenario.model_wrapper import ModelWrapper +from gym_gz.utils.typing import ( + Action, + ActionSpace, + Observation, + ObservationSpace, + Reward, +) +from rclpy.callback_groups import ReentrantCallbackGroup +from rclpy.executors import MultiThreadedExecutor, SingleThreadedExecutor +from rclpy.node import Node +from robot_builder.elements.robot import Robot +from scipy.spatial.transform import Rotation + +from rbs_gym.envs.control import ( + CartesianForceController, + GripperController, + JointEffortController, +) + + +class Manipulation(Task, Node, abc.ABC): + _ids = count(0) + + def __init__( + self, + agent_rate: float, + robot_model: str, + workspace_frame_id: str, + workspace_centre: Tuple[float, float, float], + workspace_volume: Tuple[float, float, float], + ignore_new_actions_while_executing: bool, + use_servo: bool, + scaling_factor_translation: float, + scaling_factor_rotation: float, + restrict_position_goal_to_workspace: bool, + enable_gripper: bool, + num_threads: int, + **kwargs, + ): + # Get next ID for this task instance + self.id = next(self._ids) + + # Initialize the Task base class + Task.__init__(self, agent_rate=agent_rate) + + # Initialize ROS 2 context (if not done before) + try: + rclpy.init() + except Exception as e: + if not rclpy.ok(): + sys.exit(f"ROS 2 context could not be initialised: {e}") + + # Initialize ROS 2 Node base class + Node.__init__(self, f"rbs_gym_{self.id}") + + self._allow_undeclared_parameters = True + self.declare_parameter("robot_description", "") + # Create callback group that allows execution of callbacks in parallel without restrictions + self._callback_group = ReentrantCallbackGroup() + + # Create executor + if num_threads == 1: + executor = SingleThreadedExecutor() + elif num_threads > 1: + executor = MultiThreadedExecutor( + num_threads=num_threads, + ) + else: + executor = MultiThreadedExecutor(num_threads=multiprocessing.cpu_count()) + + # Add this node to the executor + executor.add_node(self) + + # Spin this node in background thread(s) + self._executor_thread = Thread(target=executor.spin, daemon=True, args=()) + self._executor_thread.start() + + # Get class of the robot model based on passed argument + # self.robot_model_class = get_robot_model_class(robot_model) + + # Store passed arguments for later use + # self.workspace_centre = ( + # workspace_centre[0], + # workspace_centre[1], + # workspace_centre[2] + self.robot_model_class.BASE_LINK_Z_OFFSET, + # ) + # self.workspace_volume = workspace_volume + # self._restrict_position_goal_to_workspace = restrict_position_goal_to_workspace + # self._use_servo = use_servo + # self.__scaling_factor_translation = scaling_factor_translation + # self.__scaling_factor_rotation = scaling_factor_rotation + self._enable_gripper = enable_gripper + self._scene: Scene | None = None + # + # # Get workspace bounds, useful is many computations + # workspace_volume_half = ( + # workspace_volume[0] / 2, + # workspace_volume[1] / 2, + # workspace_volume[2] / 2, + # ) + # self.workspace_min_bound = ( + # self.workspace_centre[0] - workspace_volume_half[0], + # self.workspace_centre[1] - workspace_volume_half[1], + # self.workspace_centre[2] - workspace_volume_half[2], + # ) + # self.workspace_max_bound = ( + # self.workspace_centre[0] + workspace_volume_half[0], + # self.workspace_centre[1] + workspace_volume_half[1], + # self.workspace_centre[2] + workspace_volume_half[2], + # ) + + # Determine robot name and prefix based on current ID of the task + # self.robot_prefix: str = self.robot_model_class.DEFAULT_PREFIX + # if 0 == self.id: + # self.robot_name = self.robot_model_class.ROBOT_MODEL_NAME + # else: + # self.robot_name = f"{self.robot_model_class.ROBOT_MODEL_NAME}{self.id}" + # if self.robot_prefix.endswith("_"): + # self.robot_prefix = f"{self.robot_prefix[:-1]}{self.id}_" + # elif self.robot_prefix == "": + # self.robot_prefix = f"robot{self.id}_" + + # Names of specific robot links, useful all around the code + # self.robot_base_link_name = self.robot_model_class.get_robot_base_link_name( + # self.robot_prefix + # ) + # self.robot_arm_base_link_name = self.robot_model_class.get_arm_base_link_name( + # self.robot_prefix + # ) + # self.robot_ee_link_name = self.robot_model_class.get_ee_link_name( + # self.robot_prefix + # ) + # self.robot_arm_link_names = self.robot_model_class.get_arm_link_names( + # self.robot_prefix + # ) + # self.robot_gripper_link_names = self.robot_model_class.get_gripper_link_names( + # self.robot_prefix + # ) + # self.robot_arm_joint_names = self.robot_model_class.get_arm_joint_names( + # self.robot_prefix + # ) + # self.robot_gripper_joint_names = self.robot_model_class.get_gripper_joint_names( + # self.robot_prefix + # ) + + # Get exact name substitution of the frame for workspace + self.workspace_frame_id = self.substitute_special_frame(workspace_frame_id) + + # Specify initial positions (default configuration is used here) + # self.initial_arm_joint_positions = ( + # self.robot_model_class.DEFAULT_ARM_JOINT_POSITIONS + # ) + # self.initial_gripper_joint_positions = ( + # self.robot_model_class.DEFAULT_GRIPPER_JOINT_POSITIONS + # ) + + # Names of important models (in addition to robot model) + + # Setup listener and broadcaster of transforms via tf2 + self.tf2_listener = Tf2Listener(node=self) + self.tf2_broadcaster = Tf2Broadcaster(node=self) + + self.cartesian_control = True # TODO: make it as an external parameter + + # Setup controllers + self.controller = CartesianForceController(self) + if not self.cartesian_control: + self.joint_controller = JointEffortController(self) + if self._enable_gripper: + self.gripper = GripperController(self, 0.064) + + # Initialize task and randomizer overrides (e.g. from curriculum) + # Both of these are consumed at the beginning of reset + self.__task_parameter_overrides: dict[str, Any] = {} + self._randomizer_parameter_overrides: dict[str, Any] = {} + + def create_spaces(self) -> Tuple[ActionSpace, ObservationSpace]: + action_space = self.create_action_space() + observation_space = self.create_observation_space() + + return action_space, observation_space + + def create_action_space(self) -> ActionSpace: + raise NotImplementedError() + + def create_observation_space(self) -> ObservationSpace: + raise NotImplementedError() + + def set_action(self, action: Action): + raise NotImplementedError() + + def get_observation(self) -> Observation: + raise NotImplementedError() + + def get_reward(self) -> Reward: + raise NotImplementedError() + + def is_done(self) -> bool: + raise NotImplementedError() + + def reset_task(self): + # self.__consume_parameter_overrides() + pass + + # # Helper functions # + # def get_relative_ee_position( + # self, translation: Tuple[float, float, float] + # ) -> Tuple[float, float, float]: + # # Scale relative action to metric units + # translation = self.scale_relative_translation(translation) + # # Get current position + # current_position = self.get_ee_position() + # # Compute target position + # target_position = ( + # current_position[0] + translation[0], + # current_position[1] + translation[1], + # current_position[2] + translation[2], + # ) + # + # # Restrict target position to a limited workspace, if desired + # if self._restrict_position_goal_to_workspace: + # target_position = self.restrict_position_goal_to_workspace(target_position) + # + # return target_position + # + # def get_relative_ee_orientation( + # self, + # rotation: Union[ + # float, + # Tuple[float, float, float, float], + # Tuple[float, float, float, float, float, float], + # ], + # representation: str = "quat", + # ) -> Tuple[float, float, float, float]: + # # Get current orientation + # current_quat_xyzw = self.get_ee_orientation() + # + # # For 'z' representation, result should always point down + # # Therefore, create a new quatertnion that contains only yaw component + # if "z" == representation: + # current_yaw = Rotation.from_quat(current_quat_xyzw).as_euler("xyz")[2] + # current_quat_xyzw = Rotation.from_euler( + # "xyz", [np.pi, 0, current_yaw] + # ).as_quat() + # + # # Convert relative orientation representation to quaternion + # relative_quat_xyzw = None + # if "quat" == representation: + # relative_quat_xyzw = rotation + # elif "6d" == representation: + # vectors = tuple( + # rotation[x : x + 3] for x, _ in enumerate(rotation) if x % 3 == 0 + # ) + # relative_quat_xyzw = orientation_6d_to_quat(vectors[0], vectors[1]) + # elif "z" == representation: + # rotation = self.scale_relative_rotation(rotation) + # relative_quat_xyzw = Rotation.from_euler("xyz", [0, 0, rotation]).as_quat() + # + # # Compute target position (combine quaternions) + # target_quat_xyzw = quat_mul(current_quat_xyzw, relative_quat_xyzw) + # + # # Normalise quaternion (should not be needed, but just to be safe) + # target_quat_xyzw /= np.linalg.norm(target_quat_xyzw) + # + # return target_quat_xyzw + + # def scale_relative_translation( + # self, translation: Tuple[float, float, float] + # ) -> Tuple[float, float, float]: + # return ( + # self.__scaling_factor_translation * translation[0], + # self.__scaling_factor_translation * translation[1], + # self.__scaling_factor_translation * translation[2], + # ) + + # def scale_relative_rotation( + # self, + # rotation: Union[float, Tuple[float, float, float], np.floating, np.ndarray], + # ) -> float: + # if not hasattr(rotation, "__len__"): + # return self.__scaling_factor_rotation * rotation + # else: + # return ( + # self.__scaling_factor_rotation * rotation[0], + # self.__scaling_factor_rotation * rotation[1], + # self.__scaling_factor_rotation * rotation[2], + # ) + # + # def restrict_position_goal_to_workspace( + # self, position: Tuple[float, float, float] + # ) -> Tuple[float, float, float]: + # return ( + # min( + # self.workspace_max_bound[0], + # max( + # self.workspace_min_bound[0], + # position[0], + # ), + # ), + # min( + # self.workspace_max_bound[1], + # max( + # self.workspace_min_bound[1], + # position[1], + # ), + # ), + # min( + # self.workspace_max_bound[2], + # max( + # self.workspace_min_bound[2], + # position[2], + # ), + # ), + # ) + + # def restrict_servo_translation_to_workspace( + # self, translation: tuple[float, float, float] + # ) -> tuple[float, float, float]: + # current_ee_position = self.get_ee_position() + # + # translation = tuple( + # 0.0 + # if ( + # current_ee_position[i] > self.workspace_max_bound[i] + # and translation[i] > 0.0 + # ) + # or ( + # current_ee_position[i] < self.workspace_min_bound[i] + # and translation[i] < 0.0 + # ) + # else translation[i] + # for i in range(3) + # ) + # + # return translation + + def get_ee_pose( + self, + ) -> Pose: + """ + Return the current pose of the end effector with respect to arm base link. + """ + + try: + robot_model = self.world.to_gazebo().get_model(self.robot.name).to_gazebo() + ee_position, ee_quat_xyzw = get_model_pose( + world=self.world, + model=robot_model, + link=self.robot.ee_link, + xyzw=True, + ) + return transform_change_reference_frame_pose( + world=self.world, + position=ee_position, + quat=ee_quat_xyzw, + target_model=robot_model, + target_link=self.robot.base_link, + xyzw=True, + ) + except Exception as e: + self.get_logger().warn( + f"Cannot get end effector pose from Gazebo ({e}), using tf2..." + ) + transform = self.tf2_listener.lookup_transform_sync( + source_frame=self.robot.ee_link, + target_frame=self.robot.base_link, + retry=False, + ) + if transform is not None: + return ( + ( + transform.translation.x, + transform.translation.y, + transform.translation.z, + ), + ( + transform.rotation.x, + transform.rotation.y, + transform.rotation.z, + transform.rotation.w, + ), + ) + else: + self.get_logger().error( + "Cannot get pose of the end effector (default values are returned)" + ) + return ( + (0.0, 0.0, 0.0), + (0.0, 0.0, 0.0, 1.0), + ) + + def get_ee_position(self) -> Point: + """ + Return the current position of the end effector with respect to arm base link. + """ + + try: + robot_model = self.robot_wrapper + ee_position = get_model_position( + world=self.world, + model=robot_model, + link=self.robot.ee_link, + ) + return transform_change_reference_frame_position( + world=self.world, + position=ee_position, + target_model=robot_model, + target_link=self.robot.base_link, + ) + except Exception as e: + self.get_logger().debug( + f"Cannot get end effector position from Gazebo ({e}), using tf2..." + ) + transform = self.tf2_listener.lookup_transform_sync( + source_frame=self.robot.ee_link, + target_frame=self.robot.base_link, + retry=False, + ) + if transform is not None: + return ( + transform.translation.x, + transform.translation.y, + transform.translation.z, + ) + else: + self.get_logger().error( + "Cannot get position of the end effector (default values are returned)" + ) + return (0.0, 0.0, 0.0) + + def get_ee_orientation(self) -> Quat: + """ + Return the current xyzw quaternion of the end effector with respect to arm base link. + """ + + try: + robot_model = self.robot_wrapper + ee_quat_xyzw = get_model_orientation( + world=self.world, + model=robot_model, + link=self.robot.ee_link, + xyzw=True, + ) + return transform_change_reference_frame_orientation( + world=self.world, + quat=ee_quat_xyzw, + target_model=robot_model, + target_link=self.robot.base_link, + xyzw=True, + ) + except Exception as e: + self.get_logger().warn( + f"Cannot get end effector orientation from Gazebo ({e}), using tf2..." + ) + transform = self.tf2_listener.lookup_transform_sync( + source_frame=self.robot.ee_link, + target_frame=self.robot.base_link, + retry=False, + ) + if transform is not None: + return ( + transform.rotation.x, + transform.rotation.y, + transform.rotation.z, + transform.rotation.w, + ) + else: + self.get_logger().error( + "Cannot get orientation of the end effector (default values are returned)" + ) + return (0.0, 0.0, 0.0, 1.0) + + def get_object_position( + self, object_model: ModelWrapper | str + ) -> Point: + """ + Return the current position of an object with respect to arm base link. + Note: Only simulated objects are currently supported. + """ + + try: + object_position = get_model_position( + world=self.world, + model=object_model, + ) + return transform_change_reference_frame_position( + world=self.world, + position=object_position, + target_model=self.robot_wrapper.name(), + target_link=self.robot.base_link, + ) + except Exception as e: + self.get_logger().error( + f"Cannot get position of {object_model} object (default values are returned): {e}" + ) + return (0.0, 0.0, 0.0) + + def get_object_positions(self) -> dict[str, Point]: + """ + Return the current position of all objects with respect to arm base link. + Note: Only simulated objects are currently supported. + """ + + object_positions = {} + + try: + robot_model = self.robot_wrapper + robot_arm_base_link = robot_model.get_link(link_name=self.robot.base_link) + for object_name in self.scene.__objects_unique_names: + object_position = get_model_position( + world=self.world, + model=object_name, + ) + object_positions[object_name] = ( + transform_change_reference_frame_position( + world=self.world, + position=object_position, + target_model=robot_model, + target_link=robot_arm_base_link, + ) + ) + except Exception as e: + self.get_logger().error( + f"Cannot get positions of all objects (empty Dict is returned): {e}" + ) + + return object_positions + + def substitute_special_frame(self, frame_id: str) -> str: + if "arm_base_link" == frame_id: + return self.robot.base_link + elif "base_link" == frame_id: + return self.robot.base_link + elif "end_effector" == frame_id: + return self.robot.ee_link + elif "world" == frame_id: + try: + # In Gazebo, where multiple worlds are allowed + return self.world.to_gazebo().name() + except Exception as e: + self.get_logger().warn(f"{e}") + # Otherwise (e.g. real world) + return "rbs_gym_world" + else: + return frame_id + + def wait_until_action_executed(self): + if self._enable_gripper: + #FIXME: code is not tested + self.gripper.wait_until_executed() + + def move_to_initial_joint_configuration(self): + #TODO: Write this code for cartesian_control + pass + + # self.moveit2.move_to_configuration(self.initial_arm_joint_positions) + + # if ( + # self.robot_model_class.CLOSED_GRIPPER_JOINT_POSITIONS + # == self.initial_gripper_joint_positions + # ): + # self.gripper.reset_close() + # else: + # self.gripper.reset_open() + + def check_terrain_collision(self) -> bool: + """ + Returns true if robot links are in collision with the ground. + """ + robot_name_len = len(self.robot.name) + model_names = self.world.model_names() + terrain_model = self.world.get_model(self.scene.terrain.name) + + for contact in terrain_model.contacts(): + body_b = contact.body_b + + if body_b.startswith(self.robot.name) and len(body_b) > robot_name_len: + link = body_b[robot_name_len + 2 :] + + if link != self.robot.base_link and ( + link in self.robot.actuated_joint_names + or link in self.robot.gripper_actuated_joint_names + ): + return True + + return False + + # def check_all_objects_outside_workspace( + # self, + # object_positions: Dict[str, Tuple[float, float, float]], + # ) -> bool: + # """ + # Returns true if all objects are outside the workspace + # """ + # + # return all( + # [ + # self.check_object_outside_workspace(object_position) + # for object_position in object_positions.values() + # ] + # ) + # + # def check_object_outside_workspace( + # self, + # object_position: Tuple[float, float, float], + # ) -> bool: + # """ + # Returns true if the object is outside the workspace + # """ + # + # return ( + # object_position[0] < self.workspace_min_bound[0] + # or object_position[1] < self.workspace_min_bound[1] + # or object_position[2] < self.workspace_min_bound[2] + # or object_position[0] > self.workspace_max_bound[0] + # or object_position[1] > self.workspace_max_bound[1] + # or object_position[2] > self.workspace_max_bound[2] + # ) + + # def add_parameter_overrides(self, parameter_overrides: Dict[str, Any]): + # self.add_task_parameter_overrides(parameter_overrides) + # self.add_randomizer_parameter_overrides(parameter_overrides) + # # + # def add_task_parameter_overrides(self, parameter_overrides: Dict[str, Any]): + # self.__task_parameter_overrides.update(parameter_overrides) + # # + # def add_randomizer_parameter_overrides(self, parameter_overrides: Dict[str, Any]): + # self._randomizer_parameter_overrides.update(parameter_overrides) + # + # def __consume_parameter_overrides(self): + # for key, value in self.__task_parameter_overrides.items(): + # if hasattr(self, key): + # setattr(self, key, value) + # elif hasattr(self, f"_{key}"): + # setattr(self, f"_{key}", value) + # elif hasattr(self, f"__{key}"): + # setattr(self, f"__{key}", value) + # else: + # self.get_logger().error( + # f"Override '{key}' is not supperted by the task." + # ) + # + # self.__task_parameter_overrides.clear() + + @property + def robot(self) -> Robot: + """The robot property.""" + if self._scene: + return self._scene.robot_wrapper.robot + else: + raise ValueError("R") + + @property + def robot_data(self) -> RobotData: + """The robot_data property.""" + if self._scene: + return self._scene.robot + else: + raise ValueError("RD") + + @property + def robot_wrapper(self) -> RobotWrapper: + """The robot_wrapper property.""" + if self._scene: + return self._scene.robot_wrapper + else: + raise ValueError("RW") + + @property + def scene(self) -> Scene: + """The scene property.""" + if self._scene: + return self._scene + else: + raise ValueError("S") + + @scene.setter + def scene(self, value: Scene): + self._scene = value diff --git a/env_manager/rbs_gym/rbs_gym/envs/tasks/reach/__init__.py b/env_manager/rbs_gym/rbs_gym/envs/tasks/reach/__init__.py new file mode 100644 index 0000000..1fc68c3 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/tasks/reach/__init__.py @@ -0,0 +1,4 @@ +from .reach import Reach +from .reach_color_image import ReachColorImage +from .reach_depth_image import ReachDepthImage +# from .reach_octree import ReachOctree diff --git a/env_manager/rbs_gym/rbs_gym/envs/tasks/reach/pick_and_place_imitate.py b/env_manager/rbs_gym/rbs_gym/envs/tasks/reach/pick_and_place_imitate.py new file mode 100644 index 0000000..dd2d408 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/tasks/reach/pick_and_place_imitate.py @@ -0,0 +1,120 @@ +import abc + +import gymnasium as gym +import numpy as np +from gym_gz.utils.typing import Observation, ObservationSpace + +from rbs_gym.envs.models.sensors import Camera +from rbs_gym.envs.observation import CameraSubscriber +from rbs_gym.envs.tasks.reach import Reach + + +class ReachColorImage(Reach, abc.ABC): + def __init__( + self, + camera_info: list[dict] = [], + monochromatic: bool = False, + **kwargs, + ): + # Initialize the Task base class + Reach.__init__( + self, + **kwargs, + ) + + # Store parameters for later use + self._camera_width = sum(w.get("width", 0) for w in camera_info) + self._camera_height = camera_info[0]["height"] + self._monochromatic = monochromatic + self._saved = False + + self.camera_subs: list[CameraSubscriber] = [] + for camera in camera_info: + # Perception (RGB camera) + self.camera_subs.append( + CameraSubscriber( + node=self, + topic=Camera.get_color_topic(camera["name"], camera["type"]), + is_point_cloud=False, + callback_group=self._callback_group, + ) + ) + + def create_observation_space(self) -> ObservationSpace: + """ + Creates the observation space for the Imitation Learning algorithm. + + This method returns a dictionary-based observation space that includes: + + - **image**: A 2D image captured from the robot's camera. The image's shape is determined by the camera's + width and height, and the number of channels (either monochromatic or RGB). + - Dimensions: `(camera_height, camera_width, channels)` where `channels` is 1 for monochromatic images + and 3 for RGB images. + - Pixel values are in the range `[0, 255]` with data type `np.uint8`. + + - **joint_states**: The joint positions of the robot arm, represented as continuous values within the + range `[-1.0, 1.0]`, where `nDoF` refers to the number of degrees of freedom of the robot arm. + + Returns: + gym.spaces.Dict: A dictionary defining the observation space for the learning algorithm, + containing both image and joint_states information. + """ + return gym.spaces.Dict( + { + "image": gym.spaces.Box( + low=0, + high=255, + shape=( + self._camera_height, + self._camera_width, + 1 if self._monochromatic else 3, + ), + dtype=np.uint8, + ), + "joint_states": gym.spaces.Box(low=-1.0, high=1.0), + } + ) + + def get_observation(self) -> Observation: + # Get the latest images + image = [] + + for sub in self.camera_subs: + image.append(sub.get_observation()) + + image_width = sum(i.width for i in image) + image_height = image[0].height + # if image_width == self._camera_width and image_height == self._camera_height: + + # image_data = np.concatenate([i.data for i in image], axis=1) + + assert ( + image_width == self._camera_width and image_height == self._camera_height + ), f"Error: Resolution of the input image does not match the configured observation space. ({image_width}x{image_height} instead of {self._camera_width}x{self._camera_height})" + + # Reshape and create the observation + # color_image = np.array([i.data for i in image], dtype=np.uint8).reshape( + # self._camera_height, self._camera_width, 3 + # ) + color_image = np.concatenate( + [ + np.array(i.data, dtype=np.uint8).reshape(i.height, i.width, 3) + for i in image + ], + axis=1, + ) + + # # Debug save images + # from PIL import Image + # img_color = Image.fromarray(color_image) + # img_color.save("img_color.png") + + if self._monochromatic: + observation = Observation(color_image[:, :, 0]) + else: + observation = Observation(color_image) + + self.get_logger().debug(f"\nobservation: {observation}") + + # Return the observation + return observation diff --git a/env_manager/rbs_gym/rbs_gym/envs/tasks/reach/reach.py b/env_manager/rbs_gym/rbs_gym/envs/tasks/reach/reach.py new file mode 100644 index 0000000..4d26ad5 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/tasks/reach/reach.py @@ -0,0 +1,199 @@ +import abc +from typing import Tuple + +from geometry_msgs.msg import WrenchStamped +import gymnasium as gym +import numpy as np +from gym_gz.utils.typing import ( + Action, + ActionSpace, + Observation, + ObservationSpace, + Reward, +) + +from rbs_gym.envs.tasks.manipulation import Manipulation +from env_manager.utils.math import distance_to_nearest_point +from std_msgs.msg import Float64MultiArray +from rbs_gym.envs.observation import TwistSubscriber, JointStates +from env_manager.utils.helper import get_object_position + + +class Reach(Manipulation, abc.ABC): + def __init__( + self, + sparse_reward: bool, + collision_reward: float, + act_quick_reward: float, + required_accuracy: float, + **kwargs, + ): + # Initialize the Task base class + Manipulation.__init__( + self, + **kwargs, + ) + + # Additional parameters + self._sparse_reward: bool = sparse_reward + self._act_quick_reward = ( + act_quick_reward if act_quick_reward >= 0.0 else -act_quick_reward + ) + self._collision_reward = ( + collision_reward if collision_reward >= 0.0 else -collision_reward + ) + self._required_accuracy: float = required_accuracy + + # Flag indicating if the task is done (performance - get_reward + is_done) + self._is_done: bool = False + self._is_truncated: bool = False + self._is_terminated: bool = False + + # Distance to target in the previous step (or after reset) + self._previous_distance: float = 0.0 + # self._collision_reward: float = collision_reward + + # self.initial_gripper_joint_positions = self.robot_data.gripper_joint_positions + self.twist = TwistSubscriber( + self, + topic="/cartesian_force_controller/current_twist", + callback_group=self._callback_group, + ) + + self.joint_states = JointStates( + self, topic="/joint_states", callback_group=self._callback_group + ) + + self._action = WrenchStamped() + self._action_array: Action = np.array([]) + self.followed_object_name = "sphere" + + def create_action_space(self) -> ActionSpace: + # 0:3 - (x, y, z) force + # 3:6 - (x, y, z) torque + return gym.spaces.Box(low=-1.0, high=1.0, shape=(3,), dtype=np.float32) + + def create_observation_space(self) -> ObservationSpace: + # 0:3 - (x, y, z) end effector position + # 3:6 - (x, y, z) target position + # 6:9 - (x, y, z) current twist + # Note: These could theoretically be restricted to the workspace and object spawn area instead of inf + return gym.spaces.Box(low=-np.inf, high=np.inf, shape=(12,), dtype=np.float32) + + def set_action(self, action: Action): + # self.get_logger().debug(f"action: {action}") + # act = Float64MultiArray() + # act.data = action + # self.joint_controller.publisher.publish(act) + if isinstance(action, np.number): + raise RuntimeError("For the task Reach the action space should be array") + + # Store action for reward function + self._action_array = action + + # self._action.header.frame_id = self.robot_ee_link_name + self._action.header.stamp = self.get_clock().now().to_msg() + self._action.header.frame_id = self.robot.ee_link + self._action.wrench.force.x = float(action[0]) * 30.0 + self._action.wrench.force.y = float(action[1]) * 30.0 + self._action.wrench.force.z = float(action[2]) * 30.0 + # self._action.wrench.torque.x = float(action[3]) * 10.0 + # self._action.wrench.torque.y = float(action[4]) * 10.0 + # self._action.wrench.torque.z = float(action[5]) * 10.0 + self.controller.publisher.publish(self._action) + + def get_observation(self) -> Observation: + # Get current end-effector and target positions + self.object_names = [] + ee_position = self.get_ee_position() + target_position = self.get_object_position(self.followed_object_name) + # target_position = self.get_object_position(object_model=self.object_names[0]) + # joint_states = tuple(self.joint_states.get_positions()) + + # self.get_logger().warn(f"joint_states: {joint_states[:7]}") + + twist = self.twist.get_observation() + twt: tuple[float, float, float, float, float, float] = ( + twist.twist.linear.x, + twist.twist.linear.y, + twist.twist.linear.z, + twist.twist.angular.x, + twist.twist.angular.y, + twist.twist.angular.z, + ) + + observation: Observation = np.concatenate([ee_position, target_position, twt], dtype=np.float32) + # Create the observation + # observation = Observation( + # np.concatenate([ee_position, target_position, twt], dtype=np.float32) + # ) + + self.get_logger().debug(f"\nobservation: {observation}") + + # Return the observation + return observation + + def get_reward(self) -> Reward: + reward = 0.0 + + # Compute the current distance to the target + current_distance = self.get_distance_to_target() + + # Mark the episode done if target is reached + if current_distance < self._required_accuracy: + self._is_terminated = True + reward += 1.0 if self._sparse_reward else 0.0 # 100.0 + self.get_logger().debug(f"reward_target: {reward}") + + # Give reward based on how much closer robot got relative to the target for dense reward + if not self._sparse_reward: + distance_delta = self._previous_distance - current_distance + reward += distance_delta * 10.0 + self._previous_distance = current_distance + self.get_logger().debug(f"reward_distance: {reward}") + + if self.check_terrain_collision(): + reward -= self._collision_reward + self._is_truncated = True + self.get_logger().debug(f"reward_collision: {reward}") + + # Reward control + # reward -= np.abs(self._action_array).sum() * 0.01 + # self.get_logger().debug(f"reward_c: {reward}") + + # Subtract a small reward each step to provide incentive to act quickly (if enabled) + reward += self._act_quick_reward + + self.get_logger().debug(f"reward: {reward}") + + return Reward(reward) + + def is_terminated(self) -> bool: + self.get_logger().debug(f"terminated: {self._is_terminated}") + return self._is_terminated + + def is_truncated(self) -> bool: + self.get_logger().debug(f"truncated: {self._is_truncated}") + return self._is_truncated + + def reset_task(self): + Manipulation.reset_task(self) + + self._is_done = False + self._is_truncated = False + self._is_terminated = False + + # Compute and store the distance after reset if using dense reward + if not self._sparse_reward: + self._previous_distance = self.get_distance_to_target() + + self.get_logger().debug("\ntask reset") + + def get_distance_to_target(self) -> float: + ee_position = self.get_ee_position() + object_position = self.get_object_position(object_model=self.followed_object_name) + self.tf2_broadcaster.broadcast_tf( + "world", "object", object_position, (0.0, 0.0, 0.0, 1.0), xyzw=True + ) + + return distance_to_nearest_point(origin=ee_position, points=[object_position]) diff --git a/env_manager/rbs_gym/rbs_gym/envs/tasks/reach/reach_color_image.py b/env_manager/rbs_gym/rbs_gym/envs/tasks/reach/reach_color_image.py new file mode 100644 index 0000000..32ea90a --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/tasks/reach/reach_color_image.py @@ -0,0 +1,89 @@ +import abc + +import gymnasium as gym +import numpy as np +from gym_gz.utils.typing import Observation, ObservationSpace + +from env_manager.models.sensors import Camera +from rbs_gym.envs.observation import CameraSubscriber +from rbs_gym.envs.tasks.reach import Reach + + +class ReachColorImage(Reach, abc.ABC): + def __init__( + self, + camera_info: list[dict] = [], + monochromatic: bool = False, + **kwargs, + ): + + # Initialize the Task base class + Reach.__init__( + self, + **kwargs, + ) + + # Store parameters for later use + self._camera_width = sum(w.get('width', 0) for w in camera_info) + self._camera_height = camera_info[0]["height"] + self._monochromatic = monochromatic + self._saved = False + + self.camera_subs: list[CameraSubscriber] = [] + for camera in camera_info: + # Perception (RGB camera) + self.camera_subs.append(CameraSubscriber( + node=self, + topic=Camera.get_color_topic(camera["name"], camera["type"]), + is_point_cloud=False, + callback_group=self._callback_group, + )) + + def create_observation_space(self) -> ObservationSpace: + + # 0:3*height*width - rgb image + # 0:1*height*width - monochromatic (intensity) image + return gym.spaces.Box( + low=0, + high=255, + shape=( + self._camera_height, + self._camera_width, + 1 if self._monochromatic else 3, + ), + dtype=np.uint8, + ) + + def get_observation(self) -> Observation: + # Get the latest images + image = [] + + for sub in self.camera_subs: + image.append(sub.get_observation()) + + image_width = sum(i.width for i in image) + image_height = image[0].height + + assert ( + image_width == self._camera_width and image_height == self._camera_height + ), f"Error: Resolution of the input image does not match the configured observation space. ({image_width}x{image_height} instead of {self._camera_width}x{self._camera_height})" + + color_image = np.concatenate( + [np.array(i.data, dtype=np.uint8).reshape(i.height, i.width, 3) for i in image], + axis=1 + ) + + # # Debug save images + # from PIL import Image + # img_color = Image.fromarray(color_image) + # img_color.save("img_color.png") + + if self._monochromatic: + observation = Observation(color_image[:, :, 0]) + else: + observation = Observation(color_image) + + self.get_logger().debug(f"\nobservation: {observation}") + + # Return the observation + return observation diff --git a/env_manager/rbs_gym/rbs_gym/envs/tasks/reach/reach_depth_image.py b/env_manager/rbs_gym/rbs_gym/envs/tasks/reach/reach_depth_image.py new file mode 100644 index 0000000..00d64b9 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/envs/tasks/reach/reach_depth_image.py @@ -0,0 +1,67 @@ +import abc + +import gymnasium as gym +import numpy as np +from gym_gz.utils.typing import Observation, ObservationSpace + +from env_manager.models.sensors import Camera +from rbs_gym.envs.observation import CameraSubscriber +from rbs_gym.envs.tasks.reach import Reach + + +class ReachDepthImage(Reach, abc.ABC): + def __init__( + self, + camera_width: int, + camera_height: int, + camera_type: str = "depth_camera", + **kwargs, + ): + + # Initialize the Task base class + Reach.__init__( + self, + **kwargs, + ) + + # Store parameters for later use + self._camera_width = camera_width + self._camera_height = camera_height + + # Perception (depth camera) + self.camera_sub = CameraSubscriber( + node=self, + topic=Camera.get_depth_topic(camera_type), + is_point_cloud=False, + callback_group=self._callback_group, + ) + + def create_observation_space(self) -> ObservationSpace: + + # 0:height*width - depth image + return gym.spaces.Box( + low=0, + high=np.inf, + shape=(self._camera_height, self._camera_width, 1), + dtype=np.float32, + ) + + def get_observation(self) -> Observation: + + # Get the latest image + image = self.camera_sub.get_observation() + + # Construct from buffer and reshape + depth_image = np.frombuffer(image.data, dtype=np.float32).reshape( + self._camera_height, self._camera_width, 1 + ) + # Replace all instances of infinity with 0 + depth_image[depth_image == np.inf] = 0.0 + + # Create the observation + observation = Observation(depth_image) + + self.get_logger().debug(f"\nobservation: {observation}") + + # Return the observation + return observation diff --git a/env_manager/rbs_gym/rbs_gym/scripts/evaluate.py b/env_manager/rbs_gym/rbs_gym/scripts/evaluate.py new file mode 100755 index 0000000..813ab4d --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/scripts/evaluate.py @@ -0,0 +1,295 @@ +#!/usr/bin/env -S python3 -O + +import argparse +import os +from typing import Dict + +import numpy as np +import torch as th +import yaml +from rbs_gym import envs as gz_envs +from rbs_gym.utils import create_test_env, get_latest_run_id, get_saved_hyperparams +from rbs_gym.utils.utils import ALGOS, StoreDict, str2bool +from stable_baselines3.common.utils import set_random_seed +from stable_baselines3.common.vec_env import DummyVecEnv, VecEnv, VecEnvWrapper + + +def find_model_path(log_path: str, args) -> str: + model_extensions = ["zip"] + for ext in model_extensions: + model_path = os.path.join(log_path, f"{args.env}.{ext}") + if os.path.isfile(model_path): + return model_path + + if args.load_best: + best_model_path = os.path.join(log_path, "best_model.zip") + if os.path.isfile(best_model_path): + return best_model_path + + if args.load_checkpoint is not None: + checkpoint_model_path = os.path.join( + log_path, f"rl_model_{args.load_checkpoint}_steps.zip" + ) + if os.path.isfile(checkpoint_model_path): + return checkpoint_model_path + + raise ValueError(f"No model found for {args.algo} on {args.env}, path: {log_path}") + + +def main(): + parser = argparse.ArgumentParser() + + # Environment and its parameters + parser.add_argument( + "--env", type=str, default="Reach-Gazebo-v0", help="Environment ID" + ) + parser.add_argument( + "--env-kwargs", + type=str, + nargs="+", + action=StoreDict, + help="Optional keyword argument to pass to the env constructor", + ) + parser.add_argument("--n-envs", type=int, default=1, help="Number of environments") + + # Algorithm + parser.add_argument( + "--algo", + type=str, + choices=list(ALGOS.keys()), + required=False, + default="sac", + help="RL algorithm to use during the training", + ) + parser.add_argument( + "--num-threads", + type=int, + default=-1, + help="Number of threads for PyTorch (-1 to use default)", + ) + + # Test duration + parser.add_argument( + "-n", + "--n-episodes", + type=int, + default=200, + help="Number of evaluation episodes", + ) + + # Random seed + parser.add_argument("--seed", type=int, default=0, help="Random generator seed") + + # Model to test + parser.add_argument( + "-f", "--log-folder", type=str, default="logs", help="Path to the log directory" + ) + parser.add_argument( + "--exp-id", + type=int, + default=0, + help="Experiment ID (default: 0: latest, -1: no exp folder)", + ) + parser.add_argument( + "--load-best", + type=str2bool, + default=False, + help="Load best model instead of last model if available", + ) + parser.add_argument( + "--load-checkpoint", + type=int, + help="Load checkpoint instead of last model if available, you must pass the number of timesteps corresponding to it", + ) + + # Deterministic/stochastic actions + parser.add_argument( + "--stochastic", + type=str2bool, + default=False, + help="Use stochastic actions instead of deterministic", + ) + + # Logging + parser.add_argument( + "--reward-log", type=str, default="reward_logs", help="Where to log reward" + ) + parser.add_argument( + "--norm-reward", + type=str2bool, + default=False, + help="Normalize reward if applicable (trained with VecNormalize)", + ) + + # Disable render + parser.add_argument( + "--no-render", + type=str2bool, + default=False, + help="Do not render the environment (useful for tests)", + ) + + # Verbosity + parser.add_argument( + "--verbose", type=int, default=1, help="Verbose mode (0: no output, 1: INFO)" + ) + + args, unknown = parser.parse_known_args() + + if args.exp_id == 0: + args.exp_id = get_latest_run_id( + os.path.join(args.log_folder, args.algo), args.env + ) + print(f"Loading latest experiment, id={args.exp_id}") + + # Sanity checks + if args.exp_id > 0: + log_path = os.path.join(args.log_folder, args.algo, f"{args.env}_{args.exp_id}") + else: + log_path = os.path.join(args.log_folder, args.algo) + + assert os.path.isdir(log_path), f"The {log_path} folder was not found" + + model_path = find_model_path(log_path, args) + off_policy_algos = ["qrdqn", "dqn", "ddpg", "sac", "her", "td3", "tqc"] + + if args.algo in off_policy_algos: + args.n_envs = 1 + + set_random_seed(args.seed) + + if args.num_threads > 0: + if args.verbose > 1: + print(f"Setting torch.num_threads to {args.num_threads}") + th.set_num_threads(args.num_threads) + + stats_path = os.path.join(log_path, args.env) + hyperparams, stats_path = get_saved_hyperparams( + stats_path, norm_reward=args.norm_reward, test_mode=True + ) + + # load env_kwargs if existing + env_kwargs = {} + args_path = os.path.join(log_path, args.env, "args.yml") + if os.path.isfile(args_path): + with open(args_path, "r") as f: + loaded_args = yaml.load(f, Loader=yaml.UnsafeLoader) + if loaded_args["env_kwargs"] is not None: + env_kwargs = loaded_args["env_kwargs"] + # overwrite with command line arguments + if args.env_kwargs is not None: + env_kwargs.update(args.env_kwargs) + + log_dir = args.reward_log if args.reward_log != "" else None + + env = create_test_env( + args.env, + n_envs=args.n_envs, + stats_path=stats_path, + seed=args.seed, + log_dir=log_dir, + should_render=not args.no_render, + hyperparams=hyperparams, + env_kwargs=env_kwargs, + ) + + kwargs = dict(seed=args.seed) + if args.algo in off_policy_algos: + # Dummy buffer size as we don't need memory to evaluate the trained agent + kwargs.update(dict(buffer_size=1)) + + custom_objects = { + "observation_space": env.observation_space, + "action_space": env.action_space, + } + + model = ALGOS[args.algo].load( + model_path, env=env, custom_objects=custom_objects, **kwargs + ) + + obs = env.reset() + + # Deterministic by default + stochastic = args.stochastic + deterministic = not stochastic + + print( + f"Evaluating for {args.n_episodes} episodes with a", + "deterministic" if deterministic else "stochastic", + "policy.", + ) + + state = None + episode_reward = 0.0 + episode_rewards, episode_lengths, success_episode_lengths = [], [], [] + ep_len = 0 + episode = 0 + # For HER, monitor success rate + successes = [] + while episode < args.n_episodes: + action, state = model.predict(obs, state=state, deterministic=deterministic) + obs, reward, done, infos = env.step(action) + if not args.no_render: + env.render("human") + + episode_reward += reward[0] + ep_len += 1 + + if done and args.verbose > 0: + episode += 1 + print(f"--- Episode {episode}/{args.n_episodes}") + # NOTE: for env using VecNormalize, the mean reward + # is a normalized reward when `--norm_reward` flag is passed + print(f"Episode Reward: {episode_reward:.2f}") + episode_rewards.append(episode_reward) + print("Episode Length", ep_len) + episode_lengths.append(ep_len) + if infos[0].get("is_success") is not None: + print("Success?:", infos[0].get("is_success", False)) + successes.append(infos[0].get("is_success", False)) + if infos[0].get("is_success"): + success_episode_lengths.append(ep_len) + print(f"Current success rate: {100 * np.mean(successes):.2f}%") + episode_reward = 0.0 + ep_len = 0 + state = None + + if args.verbose > 0 and len(successes) > 0: + print(f"Success rate: {100 * np.mean(successes):.2f}%") + + if args.verbose > 0 and len(episode_rewards) > 0: + print( + f"Mean reward: {np.mean(episode_rewards):.2f} " + f"+/- {np.std(episode_rewards):.2f}" + ) + + if args.verbose > 0 and len(episode_lengths) > 0: + print( + f"Mean episode length: {np.mean(episode_lengths):.2f} " + f"+/- {np.std(episode_lengths):.2f}" + ) + + if args.verbose > 0 and len(success_episode_lengths) > 0: + print( + f"Mean episode length of successful episodes: {np.mean(success_episode_lengths):.2f} " + f"+/- {np.std(success_episode_lengths):.2f}" + ) + + # Workaround for https://github.com/openai/gym/issues/893 + if not args.no_render: + if args.n_envs == 1 and "Bullet" not in args.env and isinstance(env, VecEnv): + # DummyVecEnv + # Unwrap env + while isinstance(env, VecEnvWrapper): + env = env.venv + if isinstance(env, DummyVecEnv): + env.envs[0].env.close() + else: + env.close() + else: + # SubprocVecEnv + env.close() + + +if __name__ == "__main__": + main() diff --git a/env_manager/rbs_gym/rbs_gym/scripts/optimize.py b/env_manager/rbs_gym/rbs_gym/scripts/optimize.py new file mode 100644 index 0000000..d840a67 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/scripts/optimize.py @@ -0,0 +1,234 @@ +#!/usr/bin/env -S python3 -O + +import argparse +import difflib +import os +import uuid +from typing import Dict + +import gymnasium as gym +import numpy as np +import torch as th +from rbs_gym import envs as gz_envs +from rbs_gym.utils.exp_manager import ExperimentManager +from rbs_gym.utils.utils import ALGOS, StoreDict, empty_str2none, str2bool +from stable_baselines3.common.utils import set_random_seed + + +def main(): + parser = argparse.ArgumentParser() + + # Environment and its parameters + parser.add_argument( + "--env", type=str, default="Reach-Gazebo-v0", help="Environment ID" + ) + parser.add_argument( + "--env-kwargs", + type=str, + nargs="+", + action=StoreDict, + help="Optional keyword argument to pass to the env constructor", + ) + parser.add_argument( + "--vec-env", + type=str, + choices=["dummy", "subproc"], + default="dummy", + help="Type of VecEnv to use", + ) + + # Algorithm and training + parser.add_argument( + "--algo", + type=str, + choices=list(ALGOS.keys()), + required=False, + default="sac", + help="RL algorithm to use during the training", + ) + parser.add_argument( + "-params", + "--hyperparams", + type=str, + nargs="+", + action=StoreDict, + help="Optional RL hyperparameter overwrite (e.g. learning_rate:0.01 train_freq:10)", + ) + parser.add_argument( + "-n", + "--n-timesteps", + type=int, + default=-1, + help="Overwrite the number of timesteps", + ) + parser.add_argument( + "--num-threads", + type=int, + default=-1, + help="Number of threads for PyTorch (-1 to use default)", + ) + + # Continue training an already trained agent + parser.add_argument( + "-i", + "--trained-agent", + type=str, + default="", + help="Path to a pretrained agent to continue training", + ) + + # Random seed + parser.add_argument("--seed", type=int, default=-1, help="Random generator seed") + + # Saving of model + parser.add_argument( + "--save-freq", + type=int, + default=10000, + help="Save the model every n steps (if negative, no checkpoint)", + ) + parser.add_argument( + "--save-replay-buffer", + type=str2bool, + default=False, + help="Save the replay buffer too (when applicable)", + ) + + # Pre-load a replay buffer and start training on it + parser.add_argument( + "--preload-replay-buffer", + type=empty_str2none, + default="", + help="Path to a replay buffer that should be preloaded before starting the training process", + ) + + # Logging + parser.add_argument( + "-f", "--log-folder", type=str, default="logs", help="Path to the log directory" + ) + parser.add_argument( + "-tb", + "--tensorboard-log", + type=empty_str2none, + default="tensorboard_logs", + help="Tensorboard log dir", + ) + parser.add_argument( + "--log-interval", + type=int, + default=-1, + help="Override log interval (default: -1, no change)", + ) + parser.add_argument( + "-uuid", + "--uuid", + type=str2bool, + default=False, + help="Ensure that the run has a unique ID", + ) + + # Evaluation + parser.add_argument( + "--eval-freq", + type=int, + default=-1, + help="Evaluate the agent every n steps (if negative, no evaluation)", + ) + parser.add_argument( + "--eval-episodes", + type=int, + default=5, + help="Number of episodes to use for evaluation", + ) + + # Verbosity + parser.add_argument( + "--verbose", type=int, default=1, help="Verbose mode (0: no output, 1: INFO)" + ) + + # HER specifics + parser.add_argument( + "--truncate-last-trajectory", + type=str2bool, + default=True, + help="When using HER with online sampling the last trajectory in the replay buffer will be truncated after reloading the replay buffer.", + ) + + args, unknown = parser.parse_known_args() + + # Check if the selected environment is valid + # If it could not be found, suggest the closest match + registered_envs = set(gym.envs.registry.keys()) + if args.env not in registered_envs: + try: + closest_match = difflib.get_close_matches(args.env, registered_envs, n=1)[0] + except IndexError: + closest_match = "'no close match found...'" + raise ValueError( + f"{args.env} not found in gym registry, you maybe meant {closest_match}?" + ) + + # If no specific seed is selected, choose a random one + if args.seed < 0: + args.seed = np.random.randint(2**32 - 1, dtype=np.int64).item() + + # Set the random seed across platforms + set_random_seed(args.seed) + + # Setting num threads to 1 makes things run faster on cpu + if args.num_threads > 0: + if args.verbose > 1: + print(f"Setting torch.num_threads to {args.num_threads}") + th.set_num_threads(args.num_threads) + + # Verify that pre-trained agent exists before continuing to train it + if args.trained_agent != "": + assert args.trained_agent.endswith(".zip") and os.path.isfile( + args.trained_agent + ), "The trained_agent must be a valid path to a .zip file" + + # If enabled, ensure that the run has a unique ID + uuid_str = f"_{uuid.uuid4()}" if args.uuid else "" + + print("=" * 10, args.env, "=" * 10) + print(f"Seed: {args.seed}") + env_kwargs = {"render_mode": "human"} + + exp_manager = ExperimentManager( + args, + args.algo, + args.env, + args.log_folder, + args.tensorboard_log, + args.n_timesteps, + args.eval_freq, + args.eval_episodes, + args.save_freq, + args.hyperparams, + args.env_kwargs, + args.trained_agent, + truncate_last_trajectory=args.truncate_last_trajectory, + uuid_str=uuid_str, + seed=args.seed, + log_interval=args.log_interval, + save_replay_buffer=args.save_replay_buffer, + preload_replay_buffer=args.preload_replay_buffer, + verbose=args.verbose, + vec_env_type=args.vec_env, + ) + + # Prepare experiment + results = exp_manager.setup_experiment() + if results is not None: + model, saved_hyperparams = results + + # Normal training + if model is not None: + exp_manager.learn(model) + exp_manager.save_trained_model(model) + else: + exp_manager.hyperparameters_optimization() + + +if __name__ == "__main__": + main() diff --git a/env_manager/rbs_gym/rbs_gym/scripts/test_agent.py b/env_manager/rbs_gym/rbs_gym/scripts/test_agent.py new file mode 100755 index 0000000..e201b4b --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/scripts/test_agent.py @@ -0,0 +1,100 @@ +#!/usr/bin/env python3 + +import argparse +from typing import Dict + +import gymnasium as gym +from stable_baselines3.common.env_checker import check_env + +from rbs_gym import envs as gz_envs +from rbs_gym.utils.utils import StoreDict, str2bool + + +def main(): + parser = argparse.ArgumentParser() + + # Environment and its parameters + parser.add_argument( + "--env", type=str, default="Reach-Gazebo-v0", help="Environment ID" + ) + parser.add_argument( + "--env-kwargs", + type=str, + nargs="+", + action=StoreDict, + help="Optional keyword argument to pass to the env constructor", + ) + + # Number of episodes to run + parser.add_argument( + "-n", + "--n-episodes", + type=int, + default=10000, + help="Overwrite the number of episodes", + ) + + # Random seed + parser.add_argument("--seed", type=int, default=69, help="Random generator seed") + + # Flag to check environment + parser.add_argument( + "--check-env", + type=str2bool, + default=True, + help="Flag to check the environment before running the random agent", + ) + + # Flag to enable rendering + parser.add_argument( + "--render", + type=str2bool, + default=False, + help="Flag to enable rendering", + ) + + args, unknown = parser.parse_known_args() + + # Create the environment + if args.env_kwargs is not None: + env = gym.make(args.env, **args.env_kwargs) + else: + env = gym.make(args.env) + + # Initialize random seed + env.seed(args.seed) + + # Check the environment + if args.check_env: + check_env(env, warn=True, skip_render_check=True) + + # Step environment for bunch of episodes + for episode in range(args.n_episodes): + # Initialize returned values + done = False + total_reward = 0 + + # Reset the environment + observation = env.reset() + + # Step through the current episode until it is done + while not done: + # Sample random action + action = env.action_space.sample() + + # Step the environment with the random action + observation, reward, truncated, terminated, info = env.step(action) + + done = truncated or terminated + + # Accumulate the reward + total_reward += reward + + print(f"Episode #{episode}\n\treward: {total_reward}") + + # Cleanup once done + env.close() + + +if __name__ == "__main__": + main() diff --git a/env_manager/rbs_gym/rbs_gym/scripts/train.py b/env_manager/rbs_gym/rbs_gym/scripts/train.py new file mode 100755 index 0000000..87ea498 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/scripts/train.py @@ -0,0 +1,265 @@ +#!/usr/bin/env -S python3 -O + +import argparse +import difflib +import os +import uuid + +import gymnasium as gym +import numpy as np +import torch as th +from stable_baselines3.common.utils import set_random_seed + +from rbs_gym import envs as gz_envs +from rbs_gym.utils.exp_manager import ExperimentManager +from rbs_gym.utils.utils import ALGOS, StoreDict, empty_str2none, str2bool + + +def main(): + + parser = argparse.ArgumentParser() + + # Environment and its parameters + parser.add_argument( + "--env", type=str, default="Reach-Gazebo-v0", help="Environment ID" + ) + parser.add_argument( + "--env-kwargs", + type=str, + nargs="+", + action=StoreDict, + help="Optional keyword argument to pass to the env constructor", + ) + parser.add_argument( + "--vec-env", + type=str, + choices=["dummy", "subproc"], + default="dummy", + help="Type of VecEnv to use", + ) + + # Algorithm and training + parser.add_argument( + "--algo", + type=str, + choices=list(ALGOS.keys()), + required=False, + default="sac", + help="RL algorithm to use during the training", + ) + parser.add_argument( + "-params", + "--hyperparams", + type=str, + nargs="+", + action=StoreDict, + help="Optional RL hyperparameter overwrite (e.g. learning_rate:0.01 train_freq:10)", + ) + parser.add_argument( + "-n", + "--n-timesteps", + type=int, + default=-1, + help="Overwrite the number of timesteps", + ) + parser.add_argument( + "--num-threads", + type=int, + default=-1, + help="Number of threads for PyTorch (-1 to use default)", + ) + + # Continue training an already trained agent + parser.add_argument( + "-i", + "--trained-agent", + type=str, + default="", + help="Path to a pretrained agent to continue training", + ) + + # Random seed + parser.add_argument("--seed", type=int, default=-1, help="Random generator seed") + + # Saving of model + parser.add_argument( + "--save-freq", + type=int, + default=10000, + help="Save the model every n steps (if negative, no checkpoint)", + ) + parser.add_argument( + "--save-replay-buffer", + type=str2bool, + default=False, + help="Save the replay buffer too (when applicable)", + ) + + # Pre-load a replay buffer and start training on it + parser.add_argument( + "--preload-replay-buffer", + type=empty_str2none, + default="", + help="Path to a replay buffer that should be preloaded before starting the training process", + ) + parser.add_argument( + "--track", + type=str2bool, + default=False, + help="Track experiment using wandb" + ) + # optimization parameters + parser.add_argument( + "--optimize-hyperparameters", + type=str2bool, + default=False, + help="Run optimization or not?" + ) + parser.add_argument( + "--no-optim-plots", action="store_true", default=False, help="Disable hyperparameter optimization plots" + ) + + # Logging + parser.add_argument( + "-f", "--log-folder", type=str, default="logs", help="Path to the log directory" + ) + parser.add_argument( + "-tb", + "--tensorboard-log", + type=empty_str2none, + default="tensorboard_logs", + help="Tensorboard log dir", + ) + parser.add_argument( + "--log-interval", + type=int, + default=-1, + help="Override log interval (default: -1, no change)", + ) + parser.add_argument( + "-uuid", + "--uuid", + type=str2bool, + default=False, + help="Ensure that the run has a unique ID", + ) + + # Evaluation + parser.add_argument( + "--eval-freq", + type=int, + default=-1, + help="Evaluate the agent every n steps (if negative, no evaluation)", + ) + parser.add_argument( + "--eval-episodes", + type=int, + default=5, + help="Number of episodes to use for evaluation", + ) + + # Verbosity + parser.add_argument( + "--verbose", type=int, default=1, help="Verbose mode (0: no output, 1: INFO)" + ) + + # HER specifics + parser.add_argument( + "--truncate-last-trajectory", + type=str2bool, + default=True, + help="When using HER with online sampling the last trajectory in the replay buffer will be truncated after reloading the replay buffer.", + ) + + args, unknown = parser.parse_known_args() + + # Check if the selected environment is valid + # If it could not be found, suggest the closest match + registered_envs = set(gym.envs.registry.keys()) + if args.env not in registered_envs: + try: + closest_match = difflib.get_close_matches(args.env, registered_envs, n=1)[0] + except IndexError: + closest_match = "'no close match found...'" + raise ValueError( + f"{args.env} not found in gym registry, you maybe meant {closest_match}?" + ) + + # If no specific seed is selected, choose a random one + if args.seed < 0: + args.seed = np.random.randint(2**32 - 1, dtype=np.int64).item() + + # Set the random seed across platforms + set_random_seed(args.seed) + + # Setting num threads to 1 makes things run faster on cpu + if args.num_threads > 0: + if args.verbose > 1: + print(f"Setting torch.num_threads to {args.num_threads}") + th.set_num_threads(args.num_threads) + + # Verify that pre-trained agent exists before continuing to train it + if args.trained_agent != "": + assert args.trained_agent.endswith(".zip") and os.path.isfile( + args.trained_agent + ), "The trained_agent must be a valid path to a .zip file" + + # If enabled, ensure that the run has a unique ID + uuid_str = f"_{uuid.uuid4()}" if args.uuid else "" + + print("=" * 10, args.env, "=" * 10) + print(f"Seed: {args.seed}") + + if args.track: + try: + import datetime + except ImportError as e: + raise ImportError( + "if you want to use Weights & Biases to track experiment, please install W&B via `pip install wandb`" + ) from e + + run_name_str = f"{args.env}__{args.algo}__{args.seed}__{datetime.datetime.now().strftime('%Y-%m-%d_%H-%M-%S')}" + args.tensorboard_log = "runs" + + + exp_manager = ExperimentManager( + args, + args.algo, + args.env, + args.log_folder, + args.tensorboard_log, + args.n_timesteps, + args.eval_freq, + args.eval_episodes, + args.save_freq, + args.hyperparams, + args.env_kwargs, + args.trained_agent, + args.optimize_hyperparameters, + run_name=run_name_str, + truncate_last_trajectory=args.truncate_last_trajectory, + uuid_str=uuid_str, + seed=args.seed, + log_interval=args.log_interval, + save_replay_buffer=args.save_replay_buffer, + preload_replay_buffer=args.preload_replay_buffer, + verbose=args.verbose, + vec_env_type=args.vec_env, + no_optim_plots=args.no_optim_plots, + ) + + # Prepare experiment + results = exp_manager.setup_experiment() + if results is not None: + model, saved_hyperparams = results + + # Normal training + if model is not None: + exp_manager.learn(model, saved_hyperparams) + exp_manager.save_trained_model(model) + else: + exp_manager.hyperparameters_optimization() + + +if __name__ == "__main__": + main() diff --git a/env_manager/rbs_gym/rbs_gym/utils/__init__.py b/env_manager/rbs_gym/rbs_gym/utils/__init__.py new file mode 100644 index 0000000..b55f8bc --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/utils/__init__.py @@ -0,0 +1,9 @@ +from .utils import ( + ALGOS, + create_test_env, + get_latest_run_id, + get_saved_hyperparams, + get_trained_models, + get_wrapper_class, + linear_schedule, +) diff --git a/env_manager/rbs_gym/rbs_gym/utils/callbacks.py b/env_manager/rbs_gym/rbs_gym/utils/callbacks.py new file mode 100644 index 0000000..66c6bdd --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/utils/callbacks.py @@ -0,0 +1,306 @@ +import os +import tempfile +import time +from copy import deepcopy +from functools import wraps +from threading import Thread +from typing import Optional + +import optuna +from sb3_contrib import TQC +from stable_baselines3 import SAC +from stable_baselines3.common.callbacks import ( + BaseCallback, + CheckpointCallback, + EvalCallback, +) +from stable_baselines3.common.vec_env import DummyVecEnv, VecEnv + + +class TrialEvalCallback(EvalCallback): + """ + Callback used for evaluating and reporting a trial. + """ + + def __init__( + self, + eval_env: VecEnv, + trial: optuna.Trial, + n_eval_episodes: int = 5, + eval_freq: int = 10000, + deterministic: bool = True, + verbose: int = 0, + best_model_save_path: Optional[str] = None, + log_path: Optional[str] = None, + ): + + super(TrialEvalCallback, self).__init__( + eval_env=eval_env, + n_eval_episodes=n_eval_episodes, + eval_freq=eval_freq, + deterministic=deterministic, + verbose=verbose, + best_model_save_path=best_model_save_path, + log_path=log_path, + ) + self.trial = trial + self.eval_idx = 0 + self.is_pruned = False + + def _on_step(self) -> bool: + if self.eval_freq > 0 and self.n_calls % self.eval_freq == 0: + print("Evaluating trial") + super(TrialEvalCallback, self)._on_step() + self.eval_idx += 1 + # report best or report current ? + # report num_timesteps or elasped time ? + self.trial.report(self.last_mean_reward, self.eval_idx) + # Prune trial if need + if self.trial.should_prune(): + self.is_pruned = True + return False + return True + + +class ParallelTrainCallback(BaseCallback): + """ + Callback to explore (collect experience) and train (do gradient steps) + at the same time using two separate threads. + Normally used with off-policy algorithms and `train_freq=(1, "episode")`. + + - blocking mode: wait for the model to finish updating the policy before collecting new experience + at the end of a rollout + - force sync mode: stop training to update to the latest policy for collecting + new experience + + :param gradient_steps: Number of gradient steps to do before + sending the new policy + :param verbose: Verbosity level + :param sleep_time: Limit the fps in the thread collecting experience. + """ + + def __init__( + self, gradient_steps: int = 100, verbose: int = 0, sleep_time: float = 0.0 + ): + super(ParallelTrainCallback, self).__init__(verbose) + self.batch_size = 0 + self._model_ready = True + self._model = None + self.gradient_steps = gradient_steps + self.process = None + self.model_class = None + self.sleep_time = sleep_time + + def _init_callback(self) -> None: + temp_file = tempfile.TemporaryFile() + + # Windows TemporaryFile is not a io Buffer + # we save the model in the logs/ folder + if os.name == "nt": + temp_file = os.path.join("logs", "model_tmp.zip") + + self.model.save(temp_file) + + # TODO (external): add support for other algorithms + for model_class in [SAC, TQC]: + if isinstance(self.model, model_class): + self.model_class = model_class + break + + assert ( + self.model_class is not None + ), f"{self.model} is not supported for parallel training" + self._model = self.model_class.load(temp_file) + + self.batch_size = self._model.batch_size + + # Disable train method + def patch_train(function): + @wraps(function) + def wrapper(*args, **kwargs): + return + + return wrapper + + # Add logger for parallel training + self._model.set_logger(self.model.logger) + self.model.train = patch_train(self.model.train) + + # Hack: Re-add correct values at save time + def patch_save(function): + @wraps(function) + def wrapper(*args, **kwargs): + return self._model.save(*args, **kwargs) + + return wrapper + + self.model.save = patch_save(self.model.save) + + def train(self) -> None: + self._model_ready = False + + self.process = Thread(target=self._train_thread, daemon=True) + self.process.start() + + def _train_thread(self) -> None: + self._model.train( + gradient_steps=self.gradient_steps, batch_size=self.batch_size + ) + self._model_ready = True + + def _on_step(self) -> bool: + if self.sleep_time > 0: + time.sleep(self.sleep_time) + return True + + def _on_rollout_end(self) -> None: + if self._model_ready: + self._model.replay_buffer = deepcopy(self.model.replay_buffer) + self.model.set_parameters(deepcopy(self._model.get_parameters())) + self.model.actor = self.model.policy.actor + if self.num_timesteps >= self._model.learning_starts: + self.train() + # Do not wait for the training loop to finish + # self.process.join() + + def _on_training_end(self) -> None: + # Wait for the thread to terminate + if self.process is not None: + if self.verbose > 0: + print("Waiting for training thread to terminate") + self.process.join() + + +class SaveVecNormalizeCallback(BaseCallback): + """ + Callback for saving a VecNormalize wrapper every ``save_freq`` steps + + :param save_freq: (int) + :param save_path: (str) Path to the folder where ``VecNormalize`` will be saved, as ``vecnormalize.pkl`` + :param name_prefix: (str) Common prefix to the saved ``VecNormalize``, if None (default) + only one file will be kept. + """ + + def __init__( + self, + save_freq: int, + save_path: str, + name_prefix: Optional[str] = None, + verbose: int = 0, + ): + super(SaveVecNormalizeCallback, self).__init__(verbose) + self.save_freq = save_freq + self.save_path = save_path + self.name_prefix = name_prefix + + def _init_callback(self) -> None: + # Create folder if needed + if self.save_path is not None: + os.makedirs(self.save_path, exist_ok=True) + + def _on_step(self) -> bool: + if self.n_calls % self.save_freq == 0: + if self.name_prefix is not None: + path = os.path.join( + self.save_path, f"{self.name_prefix}_{self.num_timesteps}_steps.pkl" + ) + else: + path = os.path.join(self.save_path, "vecnormalize.pkl") + if self.model.get_vec_normalize_env() is not None: + self.model.get_vec_normalize_env().save(path) + if self.verbose > 1: + print(f"Saving VecNormalize to {path}") + return True + + +class CheckpointCallbackWithReplayBuffer(CheckpointCallback): + """ + Callback for saving a model every ``save_freq`` steps + :param save_freq: + :param save_path: Path to the folder where the model will be saved. + :param name_prefix: Common prefix to the saved models + :param save_replay_buffer: If enabled, save replay buffer together with model (if supported by algorithm). + :param verbose: + """ + + def __init__( + self, + save_freq: int, + save_path: str, + name_prefix: str = "rl_model", + save_replay_buffer: bool = False, + verbose: int = 0, + ): + super(CheckpointCallbackWithReplayBuffer, self).__init__( + save_freq, save_path, name_prefix, verbose + ) + self.save_replay_buffer = save_replay_buffer + # self.save_replay_buffer = hasattr(self.model, "save_replay_buffer") and save_replay_buffer + + def _on_step(self) -> bool: + if self.n_calls % self.save_freq == 0: + path = os.path.join( + self.save_path, f"{self.name_prefix}_{self.num_timesteps}_steps" + ) + self.model.save(path) + if self.verbose > 0: + print(f"Saving model checkpoint to {path}") + if self.save_replay_buffer: + path_replay_buffer = os.path.join(self.save_path, "replay_buffer.pkl") + self.model.save_replay_buffer(path_replay_buffer) + if self.verbose > 0: + print(f"Saving model checkpoint to {path_replay_buffer}") + return True + + +class CurriculumLoggerCallback(BaseCallback): + """ + Custom callback for logging curriculum values. + """ + + def __init__(self, verbose=0): + super(CurriculumLoggerCallback, self).__init__(verbose) + + def _on_step(self) -> bool: + + for infos in self.locals["infos"]: + for info_key, info_value in infos.items(): + if not ( + info_key.startswith("curriculum") + and info_key.count("__mean_step__") + ): + continue + + self.logger.record_mean( + key=info_key.replace("__mean_step__", ""), value=info_value + ) + + return True + + def _on_rollout_end(self) -> None: + + for infos in self.locals["infos"]: + for info_key, info_value in infos.items(): + if not info_key.startswith("curriculum"): + continue + if info_key.count("__mean_step__"): + continue + + if info_key.count("__mean_episode__"): + self.logger.record_mean( + key=info_key.replace("__mean_episode__", ""), value=info_value + ) + else: + if isinstance(info_value, str): + exclude = "tensorboard" + else: + exclude = None + self.logger.record(key=info_key, value=info_value, exclude=exclude) + + +class MetricsCallback(BaseCallback): + def __init__(self, verbose: int = 0): + super(MetricsCallback, self).__init__(verbose) + + def _on_step(self) -> bool: + pass diff --git a/env_manager/rbs_gym/rbs_gym/utils/exp_manager.py b/env_manager/rbs_gym/rbs_gym/utils/exp_manager.py new file mode 100644 index 0000000..eaa0b9b --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/utils/exp_manager.py @@ -0,0 +1,936 @@ +import argparse +import os +import pickle as pkl +import time +import warnings +from collections import OrderedDict +from pprint import pprint +from typing import Any, Callable, Dict, List, Optional, Tuple + +import gymnasium as gym +import numpy as np +import optuna +import yaml +from optuna.integration.skopt import SkoptSampler +from optuna.pruners import BasePruner, MedianPruner, NopPruner, SuccessiveHalvingPruner +from optuna.samplers import BaseSampler, RandomSampler, TPESampler +from optuna.visualization import plot_optimization_history, plot_param_importances +from stable_baselines3 import HerReplayBuffer +from stable_baselines3.common.base_class import BaseAlgorithm +from stable_baselines3.common.callbacks import BaseCallback, EvalCallback +from stable_baselines3.common.env_util import make_vec_env +from stable_baselines3.common.monitor import Monitor +from stable_baselines3.common.noise import ( + NormalActionNoise, + OrnsteinUhlenbeckActionNoise, +) +from stable_baselines3.common.preprocessing import ( + is_image_space, + is_image_space_channels_first, +) +from stable_baselines3.common.utils import constant_fn +from stable_baselines3.common.vec_env import ( + DummyVecEnv, + SubprocVecEnv, + VecEnv, + VecFrameStack, + VecNormalize, + VecTransposeImage, + is_vecenv_wrapped, +) +from torch import nn as nn + +from rbs_gym.utils.callbacks import ( + CheckpointCallbackWithReplayBuffer, + SaveVecNormalizeCallback, + TrialEvalCallback, +) +from rbs_gym.utils.hyperparams_opt import HYPERPARAMS_SAMPLER +from rbs_gym.utils.utils import ( + ALGOS, + get_callback_list, + get_latest_run_id, + get_wrapper_class, + linear_schedule, +) +from aim.sb3 import AimCallback + + +class ExperimentManager(object): + """ + Experiment manager: read the hyperparameters, + preprocess them, create the environment and the RL model. + + Please take a look at `train.py` to have the details for each argument. + """ + + def __init__( + self, + args: argparse.Namespace, + algo: str, + env_id: str, + log_folder: str, + tensorboard_log: str = "", + n_timesteps: int = 0, + eval_freq: int = 10000, + n_eval_episodes: int = 5, + save_freq: int = -1, + hyperparams: Optional[Dict[str, Any]] = None, + env_kwargs: Optional[Dict[str, Any]] = None, + trained_agent: str = "", + optimize_hyperparameters: bool = False, + storage: Optional[str] = None, + study_name: Optional[str] = None, + n_trials: int = 1, + n_jobs: int = 1, + sampler: str = "tpe", + pruner: str = "median", + optimization_log_path: Optional[str] = None, + n_startup_trials: int = 0, + n_evaluations: int = 1, + truncate_last_trajectory: bool = False, + uuid_str: str = "", + seed: int = 0, + log_interval: int = 0, + save_replay_buffer: bool = False, + preload_replay_buffer: str = "", + verbose: int = 1, + vec_env_type: str = "dummy", + n_eval_envs: int = 1, + no_optim_plots: bool = False, + run_name: str = "rbs_gym_run", + ): + super(ExperimentManager, self).__init__() + self.algo = algo + self.env_id = env_id + # Custom params + self.custom_hyperparams = hyperparams + self.env_kwargs = {} if env_kwargs is None else env_kwargs + self.n_timesteps = n_timesteps + self.normalize = False + self.normalize_kwargs = {} + self.env_wrapper = None + self.frame_stack = None + self.seed = seed + self.optimization_log_path = optimization_log_path + self.run_name = run_name + + self.vec_env_class = {"dummy": DummyVecEnv, "subproc": SubprocVecEnv}[ + vec_env_type + ] + + self.vec_env_kwargs = {} + # self.vec_env_kwargs = {} if vec_env_type == "dummy" else {"start_method": "fork"} + + # Callbacks + self.specified_callbacks = [] + self.callbacks = [] + self.save_freq = save_freq + self.eval_freq = eval_freq + self.n_eval_episodes = n_eval_episodes + self.n_eval_envs = n_eval_envs + + self.n_envs = 1 # it will be updated when reading hyperparams + self.n_actions = None # For DDPG/TD3 action noise objects + self._hyperparams = {} + + self.trained_agent = trained_agent + self.continue_training = trained_agent.endswith(".zip") and os.path.isfile( + trained_agent + ) + self.truncate_last_trajectory = truncate_last_trajectory + + self.preload_replay_buffer = preload_replay_buffer + + self._is_atari = self.is_atari(env_id) + self._is_gazebo_env = self.is_gazebo_env(env_id) + + # Hyperparameter optimization config + self.optimize_hyperparameters = optimize_hyperparameters + self.storage = storage + self.study_name = study_name + self.no_optim_plots = no_optim_plots + # maximum number of trials for finding the best hyperparams + self.n_trials = n_trials + # number of parallel jobs when doing hyperparameter search + self.n_jobs = n_jobs + self.sampler = sampler + self.pruner = pruner + self.n_startup_trials = n_startup_trials + self.n_evaluations = n_evaluations + self.deterministic_eval = not self.is_atari(self.env_id) + + # Logging + self.log_folder = log_folder + self.tensorboard_log = ( + None if tensorboard_log == "" else os.path.join(tensorboard_log, run_name, env_id) + ) + self.verbose = verbose + self.args = args + self.log_interval = log_interval + self.save_replay_buffer = save_replay_buffer + + self.log_path = f"{log_folder}/{self.algo}/" + self.save_path = os.path.join( + self.log_path, + f"{self.env_id}_{get_latest_run_id(self.log_path, self.env_id) + 1}{uuid_str}", + ) + self.params_path = f"{self.save_path}/{self.env_id}" + + def setup_experiment(self) -> Optional[Tuple[BaseAlgorithm, Dict[str, Any]]]: + """ + Read hyperparameters, pre-process them (create schedules, wrappers, callbacks, action noise objects) + create the environment and possibly the model. + + :return: the initialized RL model + """ + hyperparams, saved_hyperparams = self.read_hyperparameters() + hyperparams, self.env_wrapper, self.callbacks = self._preprocess_hyperparams( + hyperparams + ) + + # Create env to have access to action space for action noise + self._env = self.create_envs(self.n_envs, no_log=False) + + self.create_log_folder() + self.create_callbacks() + + self._hyperparams = self._preprocess_action_noise(hyperparams, self._env) + + if self.continue_training: + model = self._load_pretrained_agent(self._hyperparams, self._env) + elif self.optimize_hyperparameters: + return None + else: + # Train an agent from scratch + model = ALGOS[self.algo]( + env=self._env, + tensorboard_log=self.tensorboard_log, + seed=self.seed, + verbose=self.verbose, + **self._hyperparams, + ) + + # Pre-load replay buffer if enabled + if self.preload_replay_buffer: + if self.preload_replay_buffer.endswith(".pkl"): + replay_buffer_path = self.preload_replay_buffer + else: + replay_buffer_path = os.path.join( + self.preload_replay_buffer, "replay_buffer.pkl" + ) + if os.path.exists(replay_buffer_path): + print("Pre-loading replay buffer") + if self.algo == "her": + model.load_replay_buffer( + replay_buffer_path, self.truncate_last_trajectory + ) + else: + model.load_replay_buffer(replay_buffer_path) + else: + raise Exception(f"Replay buffer {replay_buffer_path} " "does not exist") + + self._save_config(saved_hyperparams) + return model, saved_hyperparams + + def learn(self, model: BaseAlgorithm, hyperparams: dict = {}) -> None: + """ + :param model: an initialized RL model + """ + kwargs = {} + if self.log_interval > -1: + kwargs = {"log_interval": self.log_interval} + + if len(self.callbacks) > 0: + aim_callback = AimCallback(repo=self.log_folder, experiment_name=self.run_name) + self.callbacks.append(aim_callback) + kwargs["callback"] = self.callbacks + + if self.continue_training: + kwargs["reset_num_timesteps"] = False + model.env.reset() + + try: + model.learn(self.n_timesteps, **kwargs) + except Exception as e: + print(f"Caught an exception during training of the model: {e}") + self.save_trained_model(model) + finally: + # Release resources + try: + model.env.close() + except EOFError: + pass + + def save_trained_model(self, model: BaseAlgorithm) -> None: + """ + Save trained model optionally with its replay buffer + and ``VecNormalize`` statistics + + :param model: + """ + print(f"Saving to {self.save_path}") + model.save(f"{self.save_path}/{self.env_id}") + + if hasattr(model, "save_replay_buffer") and self.save_replay_buffer: + print("Saving replay buffer") + model.save_replay_buffer(os.path.join(self.save_path, "replay_buffer.pkl")) + + if self.normalize: + # Important: save the running average, for testing the agent we need that normalization + model.get_vec_normalize_env().save( + os.path.join(self.params_path, "vecnormalize.pkl") + ) + + def _save_config(self, saved_hyperparams: Dict[str, Any]) -> None: + """ + Save unprocessed hyperparameters, this can be use later + to reproduce an experiment. + + :param saved_hyperparams: + """ + # Save hyperparams + with open(os.path.join(self.params_path, "config.yml"), "w") as f: + yaml.dump(saved_hyperparams, f) + + # save command line arguments + with open(os.path.join(self.params_path, "args.yml"), "w") as f: + ordered_args = OrderedDict( + [(key, vars(self.args)[key]) for key in sorted(vars(self.args).keys())] + ) + yaml.dump(ordered_args, f) + + print(f"Log path: {self.save_path}") + + def read_hyperparameters(self) -> Tuple[Dict[str, Any], Dict[str, Any]]: + # Load hyperparameters from yaml file + hyperparams_dir = os.path.abspath( + os.path.join( + os.path.realpath(__file__), *3 * [os.path.pardir], "hyperparams" + ) + ) + with open(f"{hyperparams_dir}/{self.algo}.yml", "r") as f: + hyperparams_dict = yaml.safe_load(f) + if self.env_id in list(hyperparams_dict.keys()): + hyperparams = hyperparams_dict[self.env_id] + elif self._is_atari: + hyperparams = hyperparams_dict["atari"] + else: + raise ValueError( + f"Hyperparameters not found for {self.algo}-{self.env_id}" + ) + + if self.custom_hyperparams is not None: + # Overwrite hyperparams if needed + hyperparams.update(self.custom_hyperparams) + # Sort hyperparams that will be saved + saved_hyperparams = OrderedDict( + [(key, hyperparams[key]) for key in sorted(hyperparams.keys())] + ) + + if self.verbose > 0: + print( + "Default hyperparameters for environment (ones being tuned will be overridden):" + ) + pprint(saved_hyperparams) + + return hyperparams, saved_hyperparams + + @staticmethod + def _preprocess_schedules(hyperparams: Dict[str, Any]) -> Dict[str, Any]: + # Create schedules + for key in ["learning_rate", "clip_range", "clip_range_vf"]: + if key not in hyperparams: + continue + if isinstance(hyperparams[key], str): + schedule, initial_value = hyperparams[key].split("_") + initial_value = float(initial_value) + hyperparams[key] = linear_schedule(initial_value) + elif isinstance(hyperparams[key], (float, int)): + # Negative value: ignore (ex: for clipping) + if hyperparams[key] < 0: + continue + hyperparams[key] = constant_fn(float(hyperparams[key])) + else: + raise ValueError(f"Invalid value for {key}: {hyperparams[key]}") + return hyperparams + + def _preprocess_normalization(self, hyperparams: Dict[str, Any]) -> Dict[str, Any]: + if "normalize" in hyperparams.keys(): + self.normalize = hyperparams["normalize"] + + # Special case, instead of both normalizing + # both observation and reward, we can normalize one of the two. + # in that case `hyperparams["normalize"]` is a string + # that can be evaluated as python, + # ex: "dict(norm_obs=False, norm_reward=True)" + if isinstance(self.normalize, str): + self.normalize_kwargs = eval(self.normalize) + self.normalize = True + + # Use the same discount factor as for the algorithm + if "gamma" in hyperparams: + self.normalize_kwargs["gamma"] = hyperparams["gamma"] + + del hyperparams["normalize"] + return hyperparams + + def _preprocess_hyperparams( + self, hyperparams: Dict[str, Any] + ) -> Tuple[Dict[str, Any], Optional[Callable], List[BaseCallback]]: + self.n_envs = hyperparams.get("n_envs", 1) + + if self.verbose > 0: + print(f"Using {self.n_envs} environments") + + # Convert schedule strings to objects + hyperparams = self._preprocess_schedules(hyperparams) + + # Pre-process train_freq + if "train_freq" in hyperparams and isinstance(hyperparams["train_freq"], list): + hyperparams["train_freq"] = tuple(hyperparams["train_freq"]) + + # Should we overwrite the number of timesteps? + if self.n_timesteps > 0: + if self.verbose: + print(f"Overwriting n_timesteps with n={self.n_timesteps}") + else: + self.n_timesteps = int(hyperparams["n_timesteps"]) + + # Pre-process normalize config + hyperparams = self._preprocess_normalization(hyperparams) + + # Pre-process policy/buffer keyword arguments + # Convert to python object if needed + # TODO: Use the new replay_buffer_class argument of offpolicy algorithms instead of monkey patch + for kwargs_key in { + "policy_kwargs", + "replay_buffer_class", + "replay_buffer_kwargs", + }: + if kwargs_key in hyperparams.keys() and isinstance( + hyperparams[kwargs_key], str + ): + hyperparams[kwargs_key] = eval(hyperparams[kwargs_key]) + + # Delete keys so the dict can be pass to the model constructor + if "n_envs" in hyperparams.keys(): + del hyperparams["n_envs"] + del hyperparams["n_timesteps"] + + if "frame_stack" in hyperparams.keys(): + self.frame_stack = hyperparams["frame_stack"] + del hyperparams["frame_stack"] + + # obtain a class object from a wrapper name string in hyperparams + # and delete the entry + env_wrapper = get_wrapper_class(hyperparams) + if "env_wrapper" in hyperparams.keys(): + del hyperparams["env_wrapper"] + + callbacks = get_callback_list(hyperparams) + if "callback" in hyperparams.keys(): + self.specified_callbacks = hyperparams["callback"] + del hyperparams["callback"] + + return hyperparams, env_wrapper, callbacks + + def _preprocess_action_noise( + self, hyperparams: Dict[str, Any], env: VecEnv + ) -> Dict[str, Any]: + # Parse noise string + # Note: only off-policy algorithms are supported + if hyperparams.get("noise_type") is not None: + noise_type = hyperparams["noise_type"].strip() + noise_std = hyperparams["noise_std"] + + # Save for later (hyperparameter optimization) + self.n_actions = env.action_space.shape[0] + + if "normal" in noise_type: + hyperparams["action_noise"] = NormalActionNoise( + mean=np.zeros(self.n_actions), + sigma=noise_std * np.ones(self.n_actions), + ) + elif "ornstein-uhlenbeck" in noise_type: + hyperparams["action_noise"] = OrnsteinUhlenbeckActionNoise( + mean=np.zeros(self.n_actions), + sigma=noise_std * np.ones(self.n_actions), + ) + else: + raise RuntimeError(f'Unknown noise type "{noise_type}"') + + print(f"Applying {noise_type} noise with std {noise_std}") + + del hyperparams["noise_type"] + del hyperparams["noise_std"] + + return hyperparams + + def create_log_folder(self): + os.makedirs(self.params_path, exist_ok=True) + + def create_callbacks(self): + + if self.save_freq > 0: + # Account for the number of parallel environments + self.save_freq = max(self.save_freq // self.n_envs, 1) + self.callbacks.append( + CheckpointCallbackWithReplayBuffer( + save_freq=self.save_freq, + save_path=self.save_path, + name_prefix="rl_model", + save_replay_buffer=self.save_replay_buffer, + verbose=self.verbose, + ) + ) + + # Create test env if needed, do not normalize reward + if self.eval_freq > 0 and not self.optimize_hyperparameters: + # Account for the number of parallel environments + self.eval_freq = max(self.eval_freq // self.n_envs, 1) + + if self.verbose > 0: + print("Creating test environment") + + save_vec_normalize = SaveVecNormalizeCallback( + save_freq=1, save_path=self.params_path + ) + eval_callback = EvalCallback( + eval_env=self._env, + # TODO: Use separate environment(s) for evaluation + # self.create_envs(self.n_eval_envs, eval_env=True), + callback_on_new_best=save_vec_normalize, + best_model_save_path=self.save_path, + n_eval_episodes=self.n_eval_episodes, + log_path=self.save_path, + eval_freq=self.eval_freq, + deterministic=self.deterministic_eval, + ) + + self.callbacks.append(eval_callback) + + @staticmethod + def is_atari(env_id: str) -> bool: + entry_point = gym.envs.registry[env_id].entry_point + return "AtariEnv" in str(entry_point) + + @staticmethod + def is_bullet(env_id: str) -> bool: + entry_point = gym.envs.registry[env_id].entry_point + return "pybullet_envs" in str(entry_point) + + @staticmethod + def is_robotics_env(env_id: str) -> bool: + entry_point = gym.envs.registry[env_id].entry_point + return "gym.envs.robotics" in str(entry_point) or "panda_gym.envs" in str( + entry_point + ) + + @staticmethod + def is_gazebo_env(env_id: str) -> bool: + return "Gazebo" in gym.envs.registry[env_id].entry_point + + def _maybe_normalize(self, env: VecEnv, eval_env: bool) -> VecEnv: + """ + Wrap the env into a VecNormalize wrapper if needed + and load saved statistics when present. + + :param env: + :param eval_env: + :return: + """ + # Pretrained model, load normalization + path_ = os.path.join(os.path.dirname(self.trained_agent), self.env_id) + path_ = os.path.join(path_, "vecnormalize.pkl") + + if os.path.exists(path_): + print("Loading saved VecNormalize stats") + env = VecNormalize.load(path_, env) + # Deactivate training and reward normalization + if eval_env: + env.training = False + env.norm_reward = False + + elif self.normalize: + # Copy to avoid changing default values by reference + local_normalize_kwargs = self.normalize_kwargs.copy() + # Do not normalize reward for env used for evaluation + if eval_env: + if len(local_normalize_kwargs) > 0: + local_normalize_kwargs["norm_reward"] = False + else: + local_normalize_kwargs = {"norm_reward": False} + + if self.verbose > 0: + if len(local_normalize_kwargs) > 0: + print(f"Normalization activated: {local_normalize_kwargs}") + else: + print("Normalizing input and reward") + # Note: The following line was added but not sure if it is still required + env.num_envs = self.n_envs + env = VecNormalize(env, **local_normalize_kwargs) + return env + + def create_envs( + self, n_envs: int, eval_env: bool = False, no_log: bool = False + ) -> VecEnv: + """ + Create the environment and wrap it if necessary. + + :param n_envs: + :param eval_env: Whether is it an environment used for evaluation or not + :param no_log: Do not log training when doing hyperparameter optim + (issue with writing the same file) + :return: the vectorized environment, with appropriate wrappers + """ + # Do not log eval env (issue with writing the same file) + log_dir = None if eval_env or no_log else self.save_path + + monitor_kwargs = {} + # Special case for GoalEnvs: log success rate too + if ( + "Neck" in self.env_id + or self.is_robotics_env(self.env_id) + or "parking-v0" in self.env_id + ): + monitor_kwargs = dict(info_keywords=("is_success",)) + + # On most env, SubprocVecEnv does not help and is quite memory hungry + # therefore we use DummyVecEnv by default + env = make_vec_env( + env_id=self.env_id, + n_envs=n_envs, + seed=self.seed, + env_kwargs=self.env_kwargs, + monitor_dir=log_dir, + wrapper_class=self.env_wrapper, + vec_env_cls=self.vec_env_class, + vec_env_kwargs=self.vec_env_kwargs, + monitor_kwargs=monitor_kwargs, + ) + + # Wrap the env into a VecNormalize wrapper if needed + # and load saved statistics when present + env = self._maybe_normalize(env, eval_env) + + # Optional Frame-stacking + if self.frame_stack is not None: + n_stack = self.frame_stack + env = VecFrameStack(env, n_stack) + if self.verbose > 0: + print(f"Stacking {n_stack} frames") + + if not is_vecenv_wrapped(env, VecTransposeImage): + wrap_with_vectranspose = False + if isinstance(env.observation_space, gym.spaces.Dict): + # If even one of the keys is a image-space in need of transpose, apply transpose + # If the image spaces are not consistent (for instance one is channel first, + # the other channel last), VecTransposeImage will throw an error + for space in env.observation_space.spaces.values(): + wrap_with_vectranspose = wrap_with_vectranspose or ( + is_image_space(space) + and not is_image_space_channels_first(space) + ) + else: + wrap_with_vectranspose = is_image_space( + env.observation_space + ) and not is_image_space_channels_first(env.observation_space) + + if wrap_with_vectranspose: + if self.verbose >= 1: + print("Wrapping the env in a VecTransposeImage.") + env = VecTransposeImage(env) + + return env + + def _load_pretrained_agent( + self, hyperparams: Dict[str, Any], env: VecEnv + ) -> BaseAlgorithm: + # Continue training + print( + f"Loading pretrained agent '{self.trained_agent}' to continue its training" + ) + # Policy should not be changed + del hyperparams["policy"] + + if "policy_kwargs" in hyperparams.keys(): + del hyperparams["policy_kwargs"] + + model = ALGOS[self.algo].load( + self.trained_agent, + env=env, + seed=self.seed, + tensorboard_log=self.tensorboard_log, + verbose=self.verbose, + **hyperparams, + ) + + replay_buffer_path = os.path.join( + os.path.dirname(self.trained_agent), "replay_buffer.pkl" + ) + + if not self.preload_replay_buffer and os.path.exists(replay_buffer_path): + print("Loading replay buffer") + # `truncate_last_traj` will be taken into account only if we use HER replay buffer + model.load_replay_buffer( + replay_buffer_path, truncate_last_traj=self.truncate_last_trajectory + ) + return model + + def _create_sampler(self, sampler_method: str) -> BaseSampler: + # n_warmup_steps: Disable pruner until the trial reaches the given number of step. + if sampler_method == "random": + sampler = RandomSampler(seed=self.seed) + elif sampler_method == "tpe": + # TODO (external): try with multivariate=True + sampler = TPESampler(n_startup_trials=self.n_startup_trials, seed=self.seed) + elif sampler_method == "skopt": + # cf https://scikit-optimize.github.io/#skopt.Optimizer + # GP: gaussian process + # Gradient boosted regression: GBRT + sampler = SkoptSampler( + skopt_kwargs={"base_estimator": "GP", "acq_func": "gp_hedge"} + ) + else: + raise ValueError(f"Unknown sampler: {sampler_method}") + return sampler + + def _create_pruner(self, pruner_method: str) -> BasePruner: + if pruner_method == "halving": + pruner = SuccessiveHalvingPruner( + min_resource=1, reduction_factor=4, min_early_stopping_rate=0 + ) + elif pruner_method == "median": + pruner = MedianPruner( + n_startup_trials=self.n_startup_trials, + n_warmup_steps=self.n_evaluations // 3, + ) + elif pruner_method == "none": + # Do not prune + pruner = NopPruner() + else: + raise ValueError(f"Unknown pruner: {pruner_method}") + return pruner + + # Important: Objective changed in this project (rbs_gym) to evaluate on the same environment that is used for training (cannot have two existing simulatenously with the current setup) + def objective(self, trial: optuna.Trial) -> float: + + kwargs = self._hyperparams.copy() + + trial.model_class = None + + # Hack to use DDPG/TD3 noise sampler + trial.n_actions = self._env.action_space.shape[0] + + # Hack when using HerReplayBuffer + if kwargs.get("replay_buffer_class") == HerReplayBuffer: + trial.her_kwargs = kwargs.get("replay_buffer_kwargs", {}) + + # Sample candidate hyperparameters + kwargs.update(HYPERPARAMS_SAMPLER[self.algo](trial)) + print(f"\nRunning a new trial with hyperparameters: {kwargs}") + + # Write hyperparameters into a file + trial_params_path = os.path.join(self.params_path, "optimization") + os.makedirs(trial_params_path, exist_ok=True) + with open( + os.path.join( + trial_params_path, f"hyperparameters_trial_{trial.number}.yml" + ), + "w", + ) as f: + yaml.dump(kwargs, f) + + model = ALGOS[self.algo]( + env=self._env, + # Note: Here I enabled tensorboard logs + tensorboard_log=self.tensorboard_log, + # Note: Here I differ and I seed the trial. I want all trials to have the same starting conditions + seed=self.seed, + verbose=self.verbose, + **kwargs, + ) + + # Pre-load replay buffer if enabled + if self.preload_replay_buffer: + if self.preload_replay_buffer.endswith(".pkl"): + replay_buffer_path = self.preload_replay_buffer + else: + replay_buffer_path = os.path.join( + self.preload_replay_buffer, "replay_buffer.pkl" + ) + if os.path.exists(replay_buffer_path): + print("Pre-loading replay buffer") + if self.algo == "her": + model.load_replay_buffer( + replay_buffer_path, self.truncate_last_trajectory + ) + else: + model.load_replay_buffer(replay_buffer_path) + else: + raise Exception(f"Replay buffer {replay_buffer_path} " "does not exist") + + model.trial = trial + + eval_freq = int(self.n_timesteps / self.n_evaluations) + # Account for parallel envs + eval_freq_ = max(eval_freq // model.get_env().num_envs, 1) + # Use non-deterministic eval for Atari + callbacks = get_callback_list({"callback": self.specified_callbacks}) + path = None + if self.optimization_log_path is not None: + path = os.path.join( + self.optimization_log_path, f"trial_{str(trial.number)}" + ) + eval_callback = TrialEvalCallback( + # TODO: Use a separate environment for evaluation during trial + model.env, + model.trial, + best_model_save_path=path, + log_path=path, + n_eval_episodes=self.n_eval_episodes, + eval_freq=eval_freq_, + deterministic=self.deterministic_eval, + verbose=self.verbose, + ) + callbacks.append(eval_callback) + + try: + model.learn(self.n_timesteps, callback=callbacks) + # Reset env + self._env.reset() + except AssertionError as e: + # Reset env + self._env.reset() + print("Trial stopped:", e) + # Prune hyperparams that generate NaNs + raise optuna.exceptions.TrialPruned() + except Exception as err: + exception_type = type(err).__name__ + print("Trial stopped due to raised exception:", exception_type, err) + # Prune also all other exceptions + raise optuna.exceptions.TrialPruned() + is_pruned = eval_callback.is_pruned + reward = eval_callback.last_mean_reward + + print( + f"\nFinished a trial with reward={reward}, is_pruned={is_pruned} " + f"for hyperparameters: {kwargs}" + ) + + del model + + if is_pruned: + raise optuna.exceptions.TrialPruned() + + return reward + + def hyperparameters_optimization(self) -> None: + + if self.verbose > 0: + print("Optimizing hyperparameters") + + if self.storage is not None and self.study_name is None: + warnings.warn( + f"You passed a remote storage: {self.storage} but no `--study-name`." + "The study name will be generated by Optuna, make sure to re-use the same study name " + "when you want to do distributed hyperparameter optimization." + ) + + if self.tensorboard_log is not None: + warnings.warn( + "Tensorboard log is deactivated when running hyperparameter optimization" + ) + self.tensorboard_log = None + + # TODO (external): eval each hyperparams several times to account for noisy evaluation + sampler = self._create_sampler(self.sampler) + pruner = self._create_pruner(self.pruner) + + if self.verbose > 0: + print(f"Sampler: {self.sampler} - Pruner: {self.pruner}") + + study = optuna.create_study( + sampler=sampler, + pruner=pruner, + storage=self.storage, + study_name=self.study_name, + load_if_exists=True, + direction="maximize", + ) + + try: + study.optimize( + self.objective, + n_trials=self.n_trials, + n_jobs=self.n_jobs, + gc_after_trial=True, + show_progress_bar=True, + ) + except KeyboardInterrupt: + pass + + print("Number of finished trials: ", len(study.trials)) + + print("Best trial:") + trial = study.best_trial + + print("Value: ", trial.value) + + print("Params: ") + for key, value in trial.params.items(): + print(f" {key}: {value}") + + report_name = ( + f"report_{self.env_id}_{self.n_trials}-trials-{self.n_timesteps}" + f"-{self.sampler}-{self.pruner}_{int(time.time())}" + ) + + log_path = os.path.join(self.log_folder, self.algo, report_name) + + if self.verbose: + print(f"Writing report to {log_path}") + + # Write report + os.makedirs(os.path.dirname(log_path), exist_ok=True) + study.trials_dataframe().to_csv(f"{log_path}.csv") + + # Save python object to inspect/re-use it later + with open(f"{log_path}.pkl", "wb+") as f: + pkl.dump(study, f) + + # Skip plots + if self.no_optim_plots: + return + + # Plot optimization result + try: + fig1 = plot_optimization_history(study) + fig2 = plot_param_importances(study) + + fig1.show() + fig2.show() + except (ValueError, ImportError, RuntimeError): + pass + + def collect_demonstration(self, model): + # Any random action will do (this won't actually be used since `preload_replay_buffer` env kwarg is enabled) + action = np.array([model.env.action_space.sample()]) + # Reset env at the beginning + obs = model.env.reset() + # Collect transitions + for i in range(model.replay_buffer.buffer_size): + # Note: If `None` is passed to Grasp env, it uses custom action heuristic to reach the target + next_obs, rewards, dones, infos = model.env.unwrapped.step(action) + # Extract the actual actions from info + actual_actions = [info["actual_actions"] for info in infos] + # Add to replay buffer + model.replay_buffer.add(obs, next_obs, actual_actions, rewards, dones) + # Update current observation + obs = next_obs + + print("Saving replay buffer") + model.save_replay_buffer(os.path.join(self.save_path, "replay_buffer.pkl")) + model.env.close() + exit diff --git a/env_manager/rbs_gym/rbs_gym/utils/hyperparams_opt.py b/env_manager/rbs_gym/rbs_gym/utils/hyperparams_opt.py new file mode 100644 index 0000000..9d36cf5 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/utils/hyperparams_opt.py @@ -0,0 +1,170 @@ +from typing import Any, Dict + +import numpy as np +import optuna +from stable_baselines3.common.noise import NormalActionNoise +from torch import nn as nn + + +def sample_sac_params( + trial: optuna.Trial, +) -> Dict[str, Any]: + """ + Sampler for SAC hyperparameters + """ + + buffer_size = 150000 + # learning_starts = trial.suggest_categorical( + # "learning_starts", [5000, 10000, 20000]) + learning_starts = 5000 + + batch_size = trial.suggest_categorical("batch_size", [32, 64, 128, 256, 512, 1024, 2048]) + learning_rate = trial.suggest_float( + "learning_rate", low=0.000001, high=0.001, log=True + ) + + gamma = trial.suggest_float("gamma", low=0.98, high=1.0, log=True) + tau = trial.suggest_float("tau", low=0.001, high=0.025, log=True) + + ent_coef = "auto_0.5_0.1" + target_entropy = "auto" + + noise_std = trial.suggest_float("noise_std", low=0.01, high=0.2, log=True) + action_noise = NormalActionNoise( + mean=np.zeros(trial.n_actions), sigma=np.ones(trial.n_actions) * noise_std + ) + + train_freq = 1 + gradient_steps = trial.suggest_categorical("gradient_steps", [1, 2]) + + policy_kwargs = dict() + net_arch = trial.suggest_categorical("net_arch", [256, 384, 512]) + policy_kwargs["net_arch"] = [net_arch] * 3 + + return { + "buffer_size": buffer_size, + "learning_starts": learning_starts, + "batch_size": batch_size, + "learning_rate": learning_rate, + "gamma": gamma, + "tau": tau, + "ent_coef": ent_coef, + "target_entropy": target_entropy, + "action_noise": action_noise, + "train_freq": train_freq, + "gradient_steps": gradient_steps, + "policy_kwargs": policy_kwargs, + } + + +def sample_td3_params( + trial: optuna.Trial, +) -> Dict[str, Any]: + """ + Sampler for TD3 hyperparameters + """ + + buffer_size = 150000 + # learning_starts = trial.suggest_categorical( + # "learning_starts", [5000, 10000, 20000]) + learning_starts = 5000 + + batch_size = trial.suggest_categorical("batch_size", [32, 64, 128]) + learning_rate = trial.suggest_float( + "learning_rate", low=0.000001, high=0.001, log=True + ) + + gamma = trial.suggest_float("gamma", low=0.98, high=1.0, log=True) + tau = trial.suggest_float("tau", low=0.001, high=0.025, log=True) + + target_policy_noise = trial.suggest_float( + "target_policy_noise", low=0.00000001, high=0.5, log=True + ) + target_noise_clip = 0.5 + + noise_std = trial.suggest_float("noise_std", low=0.025, high=0.5, log=True) + action_noise = NormalActionNoise( + mean=np.zeros(trial.n_actions), sigma=np.ones(trial.n_actions) * noise_std + ) + + train_freq = 1 + gradient_steps = trial.suggest_categorical("gradient_steps", [1, 2]) + + policy_kwargs = dict() + net_arch = trial.suggest_categorical("net_arch", [256, 384, 512]) + policy_kwargs["net_arch"] = [net_arch] * 3 + + return { + "buffer_size": buffer_size, + "learning_starts": learning_starts, + "batch_size": batch_size, + "learning_rate": learning_rate, + "gamma": gamma, + "tau": tau, + "target_policy_noise": target_policy_noise, + "target_noise_clip": target_noise_clip, + "action_noise": action_noise, + "train_freq": train_freq, + "gradient_steps": gradient_steps, + "policy_kwargs": policy_kwargs, + } + + +def sample_tqc_params( + trial: optuna.Trial, +) -> Dict[str, Any]: + """ + Sampler for TQC hyperparameters + """ + + buffer_size = 25000 + learning_starts = 0 + + batch_size = 32 + learning_rate = trial.suggest_float( + "learning_rate", low=0.000025, high=0.00075, log=True + ) + + gamma = 1.0 - trial.suggest_float("gamma", low=0.0001, high=0.025, log=True) + tau = trial.suggest_float("tau", low=0.0005, high=0.025, log=True) + + ent_coef = "auto_0.1_0.05" + target_entropy = "auto" + + noise_std = trial.suggest_float("noise_std", low=0.01, high=0.1, log=True) + action_noise = NormalActionNoise( + mean=np.zeros(trial.n_actions), sigma=np.ones(trial.n_actions) * noise_std + ) + + train_freq = 1 + gradient_steps = trial.suggest_categorical("gradient_steps", [1, 2]) + + policy_kwargs = dict() + net_arch = trial.suggest_categorical("net_arch", [128, 256, 384, 512]) + policy_kwargs["net_arch"] = [net_arch] * 2 + policy_kwargs["n_quantiles"] = trial.suggest_int("n_quantiles", low=20, high=40) + top_quantiles_to_drop_per_net = round(0.08 * policy_kwargs["n_quantiles"]) + policy_kwargs["n_critics"] = trial.suggest_categorical("n_critics", [2, 3]) + + return { + "buffer_size": buffer_size, + "learning_starts": learning_starts, + "batch_size": batch_size, + "learning_rate": learning_rate, + "gamma": gamma, + "tau": tau, + "ent_coef": ent_coef, + "target_entropy": target_entropy, + "top_quantiles_to_drop_per_net": top_quantiles_to_drop_per_net, + "action_noise": action_noise, + "train_freq": train_freq, + "gradient_steps": gradient_steps, + "policy_kwargs": policy_kwargs, + } + + +HYPERPARAMS_SAMPLER = { + "sac": sample_sac_params, + "td3": sample_td3_params, + "tqc": sample_tqc_params, +} diff --git a/env_manager/rbs_gym/rbs_gym/utils/utils.py b/env_manager/rbs_gym/rbs_gym/utils/utils.py new file mode 100644 index 0000000..c073dd6 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/utils/utils.py @@ -0,0 +1,411 @@ +import argparse +import glob +import importlib +import os +from typing import Any, Callable, Dict, List, Optional, Tuple, Union + +import gymnasium as gym + +# For custom activation fn +import stable_baselines3 as sb3 # noqa: F401 +import torch as th # noqa: F401 +import yaml +from sb3_contrib import QRDQN, TQC +from stable_baselines3 import A2C, DDPG, DQN, PPO, SAC, TD3 +from stable_baselines3.common.callbacks import BaseCallback +from stable_baselines3.common.env_util import make_vec_env +from stable_baselines3.common.monitor import Monitor +from stable_baselines3.common.sb2_compat.rmsprop_tf_like import ( # noqa: F401 + RMSpropTFLike, +) +from stable_baselines3.common.vec_env import ( + DummyVecEnv, + SubprocVecEnv, + VecEnv, + VecFrameStack, + VecNormalize, +) +from torch import nn as nn # noqa: F401 pylint: disable=unused-import + +ALGOS = { + "a2c": A2C, + "ddpg": DDPG, + "dqn": DQN, + "ppo": PPO, + "sac": SAC, + "td3": TD3, + # SB3 Contrib, + "qrdqn": QRDQN, + "tqc": TQC, +} + + +def flatten_dict_observations(env: gym.Env) -> gym.Env: + assert isinstance(env.observation_space, gym.spaces.Dict) + try: + return gym.wrappers.FlattenObservation(env) + except AttributeError: + keys = env.observation_space.spaces.keys() + return gym.wrappers.FlattenDictWrapper(env, dict_keys=list(keys)) + + +def get_wrapper_class( + hyperparams: Dict[str, Any] +) -> Optional[Callable[[gym.Env], gym.Env]]: + """ + Get one or more Gym environment wrapper class specified as a hyper parameter + "env_wrapper". + e.g. + env_wrapper: gym_minigrid.wrappers.FlatObsWrapper + + for multiple, specify a list: + + env_wrapper: + - utils.wrappers.PlotActionWrapper + - utils.wrappers.TimeFeatureWrapper + + + :param hyperparams: + :return: maybe a callable to wrap the environment + with one or multiple gym.Wrapper + """ + + def get_module_name(wrapper_name): + return ".".join(wrapper_name.split(".")[:-1]) + + def get_class_name(wrapper_name): + return wrapper_name.split(".")[-1] + + if "env_wrapper" in hyperparams.keys(): + wrapper_name = hyperparams.get("env_wrapper") + + if wrapper_name is None: + return None + + if not isinstance(wrapper_name, list): + wrapper_names = [wrapper_name] + else: + wrapper_names = wrapper_name + + wrapper_classes = [] + wrapper_kwargs = [] + # Handle multiple wrappers + for wrapper_name in wrapper_names: + # Handle keyword arguments + if isinstance(wrapper_name, dict): + assert len(wrapper_name) == 1, ( + "You have an error in the formatting " + f"of your YAML file near {wrapper_name}. " + "You should check the indentation." + ) + wrapper_dict = wrapper_name + wrapper_name = list(wrapper_dict.keys())[0] + kwargs = wrapper_dict[wrapper_name] + else: + kwargs = {} + wrapper_module = importlib.import_module(get_module_name(wrapper_name)) + wrapper_class = getattr(wrapper_module, get_class_name(wrapper_name)) + wrapper_classes.append(wrapper_class) + wrapper_kwargs.append(kwargs) + + def wrap_env(env: gym.Env) -> gym.Env: + """ + :param env: + :return: + """ + for wrapper_class, kwargs in zip(wrapper_classes, wrapper_kwargs): + env = wrapper_class(env, **kwargs) + return env + + return wrap_env + else: + return None + + +def get_callback_list(hyperparams: Dict[str, Any]) -> List[BaseCallback]: + """ + Get one or more Callback class specified as a hyper-parameter + "callback". + e.g. + callback: stable_baselines3.common.callbacks.CheckpointCallback + + for multiple, specify a list: + + callback: + - utils.callbacks.PlotActionWrapper + - stable_baselines3.common.callbacks.CheckpointCallback + + :param hyperparams: + :return: + """ + + def get_module_name(callback_name): + return ".".join(callback_name.split(".")[:-1]) + + def get_class_name(callback_name): + return callback_name.split(".")[-1] + + callbacks = [] + + if "callback" in hyperparams.keys(): + callback_name = hyperparams.get("callback") + + if callback_name is None: + return callbacks + + if not isinstance(callback_name, list): + callback_names = [callback_name] + else: + callback_names = callback_name + + # Handle multiple wrappers + for callback_name in callback_names: + # Handle keyword arguments + if isinstance(callback_name, dict): + assert len(callback_name) == 1, ( + "You have an error in the formatting " + f"of your YAML file near {callback_name}. " + "You should check the indentation." + ) + callback_dict = callback_name + callback_name = list(callback_dict.keys())[0] + kwargs = callback_dict[callback_name] + else: + kwargs = {} + callback_module = importlib.import_module(get_module_name(callback_name)) + callback_class = getattr(callback_module, get_class_name(callback_name)) + callbacks.append(callback_class(**kwargs)) + + return callbacks + + +def create_test_env( + env_id: str, + n_envs: int = 1, + stats_path: Optional[str] = None, + seed: int = 0, + log_dir: Optional[str] = None, + should_render: bool = True, + hyperparams: Optional[Dict[str, Any]] = None, + env_kwargs: Optional[Dict[str, Any]] = None, +) -> VecEnv: + """ + Create environment for testing a trained agent + + :param env_id: + :param n_envs: number of processes + :param stats_path: path to folder containing saved running averaged + :param seed: Seed for random number generator + :param log_dir: Where to log rewards + :param should_render: For Pybullet env, display the GUI + :param hyperparams: Additional hyperparams (ex: n_stack) + :param env_kwargs: Optional keyword argument to pass to the env constructor + :return: + """ + # Avoid circular import + from rbs_gym.utils.exp_manager import ExperimentManager + + # Create the environment and wrap it if necessary + env_wrapper = get_wrapper_class(hyperparams) + + hyperparams = {} if hyperparams is None else hyperparams + + if "env_wrapper" in hyperparams.keys(): + del hyperparams["env_wrapper"] + + vec_env_kwargs = {} + vec_env_cls = DummyVecEnv + if n_envs > 1 or (ExperimentManager.is_bullet(env_id) and should_render): + # HACK: force SubprocVecEnv for Bullet env + # as Pybullet envs does not follow gym.render() interface + vec_env_cls = SubprocVecEnv + # start_method = 'spawn' for thread safe + + env = make_vec_env( + env_id, + n_envs=n_envs, + monitor_dir=log_dir, + seed=seed, + wrapper_class=env_wrapper, + env_kwargs=env_kwargs, + vec_env_cls=vec_env_cls, + vec_env_kwargs=vec_env_kwargs, + ) + + # Load saved stats for normalizing input and rewards + # And optionally stack frames + if stats_path is not None: + if hyperparams["normalize"]: + print("Loading running average") + print(f"with params: {hyperparams['normalize_kwargs']}") + path_ = os.path.join(stats_path, "vecnormalize.pkl") + if os.path.exists(path_): + env = VecNormalize.load(path_, env) + # Deactivate training and reward normalization + env.training = False + env.norm_reward = False + else: + raise ValueError(f"VecNormalize stats {path_} not found") + + n_stack = hyperparams.get("frame_stack", 0) + if n_stack > 0: + print(f"Stacking {n_stack} frames") + env = VecFrameStack(env, n_stack) + return env + + +def linear_schedule(initial_value: Union[float, str]) -> Callable[[float], float]: + """ + Linear learning rate schedule. + + :param initial_value: (float or str) + :return: (function) + """ + if isinstance(initial_value, str): + initial_value = float(initial_value) + + def func(progress_remaining: float) -> float: + """ + Progress will decrease from 1 (beginning) to 0 + :param progress_remaining: (float) + :return: (float) + """ + return progress_remaining * initial_value + + return func + + +def get_trained_models(log_folder: str) -> Dict[str, Tuple[str, str]]: + """ + :param log_folder: Root log folder + :return: Dict[str, Tuple[str, str]] representing the trained agents + """ + trained_models = {} + for algo in os.listdir(log_folder): + if not os.path.isdir(os.path.join(log_folder, algo)): + continue + for env_id in os.listdir(os.path.join(log_folder, algo)): + # Retrieve env name + env_id = env_id.split("_")[0] + trained_models[f"{algo}-{env_id}"] = (algo, env_id) + return trained_models + + +def get_latest_run_id(log_path: str, env_id: str) -> int: + """ + Returns the latest run number for the given log name and log path, + by finding the greatest number in the directories. + + :param log_path: path to log folder + :param env_id: + :return: latest run number + """ + max_run_id = 0 + for path in glob.glob(os.path.join(log_path, env_id + "_[0-9]*")): + file_name = os.path.basename(path) + ext = file_name.split("_")[-1] + if ( + env_id == "_".join(file_name.split("_")[:-1]) + and ext.isdigit() + and int(ext) > max_run_id + ): + max_run_id = int(ext) + return max_run_id + + +def get_saved_hyperparams( + stats_path: str, + norm_reward: bool = False, + test_mode: bool = False, +) -> Tuple[Dict[str, Any], str]: + """ + :param stats_path: + :param norm_reward: + :param test_mode: + :return: + """ + hyperparams = {} + if not os.path.isdir(stats_path): + stats_path = None + else: + config_file = os.path.join(stats_path, "config.yml") + if os.path.isfile(config_file): + # Load saved hyperparameters + with open(os.path.join(stats_path, "config.yml"), "r") as f: + hyperparams = yaml.load( + f, Loader=yaml.UnsafeLoader + ) # pytype: disable=module-attr + hyperparams["normalize"] = hyperparams.get("normalize", False) + else: + obs_rms_path = os.path.join(stats_path, "obs_rms.pkl") + hyperparams["normalize"] = os.path.isfile(obs_rms_path) + + # Load normalization params + if hyperparams["normalize"]: + if isinstance(hyperparams["normalize"], str): + normalize_kwargs = eval(hyperparams["normalize"]) + if test_mode: + normalize_kwargs["norm_reward"] = norm_reward + else: + normalize_kwargs = { + "norm_obs": hyperparams["normalize"], + "norm_reward": norm_reward, + } + hyperparams["normalize_kwargs"] = normalize_kwargs + return hyperparams, stats_path + + +class StoreDict(argparse.Action): + """ + Custom argparse action for storing dict. + + In: args1:0.0 args2:"dict(a=1)" + Out: {'args1': 0.0, arg2: dict(a=1)} + """ + + def __init__(self, option_strings, dest, nargs=None, **kwargs): + self._nargs = nargs + super(StoreDict, self).__init__(option_strings, dest, nargs=nargs, **kwargs) + + def __call__(self, parser, namespace, values, option_string=None): + + arg_dict = {} + + if hasattr(namespace, self.dest): + current_arg = getattr(namespace, self.dest) + if isinstance(current_arg, Dict): + arg_dict = getattr(namespace, self.dest) + + for arguments in values: + if not arguments: + continue + key = arguments.split(":")[0] + value = ":".join(arguments.split(":")[1:]) + # Evaluate the string as python code + arg_dict[key] = eval(value) + setattr(namespace, self.dest, arg_dict) + + +def str2bool(value: Union[str, bool]) -> bool: + """ + Convert logical string to boolean. Can be used as argparse type. + """ + + if isinstance(value, bool): + return value + if value.lower() in ("yes", "true", "t", "y", "1"): + return True + elif value.lower() in ("no", "false", "f", "n", "0"): + return False + else: + raise argparse.ArgumentTypeError("Boolean value expected.") + + +def empty_str2none(value: Optional[str]) -> Optional[str]: + """ + If string is empty, convert to None. Can be used as argparse type. + """ + + if not value: + return None + return value diff --git a/env_manager/rbs_gym/rbs_gym/utils/wrappers.py b/env_manager/rbs_gym/rbs_gym/utils/wrappers.py new file mode 100644 index 0000000..9107117 --- /dev/null +++ b/env_manager/rbs_gym/rbs_gym/utils/wrappers.py @@ -0,0 +1,395 @@ +import gymnasium as gym +import numpy as np +from matplotlib import pyplot as plt +from scipy.signal import iirfilter, sosfilt, zpk2sos + + +class DoneOnSuccessWrapper(gym.Wrapper): + """ + Reset on success and offsets the reward. + Useful for GoalEnv. + """ + + def __init__(self, env: gym.Env, reward_offset: float = 0.0, n_successes: int = 1): + super(DoneOnSuccessWrapper, self).__init__(env) + self.reward_offset = reward_offset + self.n_successes = n_successes + self.current_successes = 0 + + def reset(self): + self.current_successes = 0 + return self.env.reset() + + def step(self, action): + obs, reward, done, info = self.env.step(action) + if info.get("is_success", False): + self.current_successes += 1 + else: + self.current_successes = 0 + # number of successes in a row + done = done or self.current_successes >= self.n_successes + reward += self.reward_offset + return obs, reward, done, info + + def compute_reward(self, achieved_goal, desired_goal, info): + reward = self.env.compute_reward(achieved_goal, desired_goal, info) + return reward + self.reward_offset + + +class ActionNoiseWrapper(gym.Wrapper): + """ + Add gaussian noise to the action (without telling the agent), + to test the robustness of the control. + + :param env: (gym.Env) + :param noise_std: (float) Standard deviation of the noise + """ + + def __init__(self, env, noise_std=0.1): + super(ActionNoiseWrapper, self).__init__(env) + self.noise_std = noise_std + + def step(self, action): + noise = np.random.normal( + np.zeros_like(action), np.ones_like(action) * self.noise_std + ) + noisy_action = action + noise + return self.env.step(noisy_action) + + +# from https://docs.obspy.org +def lowpass(data, freq, df, corners=4, zerophase=False): + """ + Butterworth-Lowpass Filter. + + Filter data removing data over certain frequency ``freq`` using ``corners`` + corners. + The filter uses :func:`scipy.signal.iirfilter` (for design) + and :func:`scipy.signal.sosfilt` (for applying the filter). + + :type data: numpy.ndarray + :param data: Data to filter. + :param freq: Filter corner frequency. + :param df: Sampling rate in Hz. + :param corners: Filter corners / order. + :param zerophase: If True, apply filter once forwards and once backwards. + This results in twice the number of corners but zero phase shift in + the resulting filtered trace. + :return: Filtered data. + """ + fe = 0.5 * df + f = freq / fe + # raise for some bad scenarios + if f > 1: + f = 1.0 + msg = ( + "Selected corner frequency is above Nyquist. " + + "Setting Nyquist as high corner." + ) + print(msg) + z, p, k = iirfilter(corners, f, btype="lowpass", ftype="butter", output="zpk") + sos = zpk2sos(z, p, k) + if zerophase: + firstpass = sosfilt(sos, data) + return sosfilt(sos, firstpass[::-1])[::-1] + else: + return sosfilt(sos, data) + + +class LowPassFilterWrapper(gym.Wrapper): + """ + Butterworth-Lowpass + + :param env: (gym.Env) + :param freq: Filter corner frequency. + :param df: Sampling rate in Hz. + """ + + def __init__(self, env, freq=5.0, df=25.0): + super(LowPassFilterWrapper, self).__init__(env) + self.freq = freq + self.df = df + self.signal = [] + + def reset(self): + self.signal = [] + return self.env.reset() + + def step(self, action): + self.signal.append(action) + filtered = np.zeros_like(action) + for i in range(self.action_space.shape[0]): + smoothed_action = lowpass( + np.array(self.signal)[:, i], freq=self.freq, df=self.df + ) + filtered[i] = smoothed_action[-1] + return self.env.step(filtered) + + +class ActionSmoothingWrapper(gym.Wrapper): + """ + Smooth the action using exponential moving average. + + :param env: (gym.Env) + :param smoothing_coef: (float) Smoothing coefficient (0 no smoothing, 1 very smooth) + """ + + def __init__(self, env, smoothing_coef: float = 0.0): + super(ActionSmoothingWrapper, self).__init__(env) + self.smoothing_coef = smoothing_coef + self.smoothed_action = None + # from https://github.com/rail-berkeley/softlearning/issues/3 + # for smoothing latent space + # self.alpha = self.smoothing_coef + # self.beta = np.sqrt(1 - self.alpha ** 2) / (1 - self.alpha) + + def reset(self): + self.smoothed_action = None + return self.env.reset() + + def step(self, action): + if self.smoothed_action is None: + self.smoothed_action = np.zeros_like(action) + self.smoothed_action = ( + self.smoothing_coef * self.smoothed_action + + (1 - self.smoothing_coef) * action + ) + return self.env.step(self.smoothed_action) + + +class DelayedRewardWrapper(gym.Wrapper): + """ + Delay the reward by `delay` steps, it makes the task harder but more realistic. + The reward is accumulated during those steps. + + :param env: (gym.Env) + :param delay: (int) Number of steps the reward should be delayed. + """ + + def __init__(self, env, delay=10): + super(DelayedRewardWrapper, self).__init__(env) + self.delay = delay + self.current_step = 0 + self.accumulated_reward = 0.0 + + def reset(self): + self.current_step = 0 + self.accumulated_reward = 0.0 + return self.env.reset() + + def step(self, action): + obs, reward, done, info = self.env.step(action) + + self.accumulated_reward += reward + self.current_step += 1 + + if self.current_step % self.delay == 0 or done: + reward = self.accumulated_reward + self.accumulated_reward = 0.0 + else: + reward = 0.0 + return obs, reward, done, info + + +class HistoryWrapper(gym.Wrapper): + """ + Stack past observations and actions to give an history to the agent. + + :param env: (gym.Env) + :param horizon: (int) Number of steps to keep in the history. + """ + + def __init__(self, env: gym.Env, horizon: int = 5): + assert isinstance(env.observation_space, gym.spaces.Box) + + wrapped_obs_space = env.observation_space + wrapped_action_space = env.action_space + + # TODO (external): double check, it seems wrong when we have different low and highs + low_obs = np.repeat(wrapped_obs_space.low, horizon, axis=-1) + high_obs = np.repeat(wrapped_obs_space.high, horizon, axis=-1) + + low_action = np.repeat(wrapped_action_space.low, horizon, axis=-1) + high_action = np.repeat(wrapped_action_space.high, horizon, axis=-1) + + low = np.concatenate((low_obs, low_action)) + high = np.concatenate((high_obs, high_action)) + + # Overwrite the observation space + env.observation_space = gym.spaces.Box( + low=low, high=high, dtype=wrapped_obs_space.dtype + ) + + super(HistoryWrapper, self).__init__(env) + + self.horizon = horizon + self.low_action, self.high_action = low_action, high_action + self.low_obs, self.high_obs = low_obs, high_obs + self.low, self.high = low, high + self.obs_history = np.zeros(low_obs.shape, low_obs.dtype) + self.action_history = np.zeros(low_action.shape, low_action.dtype) + + def _create_obs_from_history(self): + return np.concatenate((self.obs_history, self.action_history)) + + def reset(self): + # Flush the history + self.obs_history[...] = 0 + self.action_history[...] = 0 + obs = self.env.reset() + self.obs_history[..., -obs.shape[-1] :] = obs + return self._create_obs_from_history() + + def step(self, action): + obs, reward, done, info = self.env.step(action) + last_ax_size = obs.shape[-1] + + self.obs_history = np.roll(self.obs_history, shift=-last_ax_size, axis=-1) + self.obs_history[..., -obs.shape[-1] :] = obs + + self.action_history = np.roll( + self.action_history, shift=-action.shape[-1], axis=-1 + ) + self.action_history[..., -action.shape[-1] :] = action + return self._create_obs_from_history(), reward, done, info + + +class HistoryWrapperObsDict(gym.Wrapper): + """ + History Wrapper for dict observation. + + :param env: (gym.Env) + :param horizon: (int) Number of steps to keep in the history. + """ + + def __init__(self, env, horizon=5): + assert isinstance(env.observation_space.spaces["observation"], gym.spaces.Box) + + wrapped_obs_space = env.observation_space.spaces["observation"] + wrapped_action_space = env.action_space + + # TODO (external): double check, it seems wrong when we have different low and highs + low_obs = np.repeat(wrapped_obs_space.low, horizon, axis=-1) + high_obs = np.repeat(wrapped_obs_space.high, horizon, axis=-1) + + low_action = np.repeat(wrapped_action_space.low, horizon, axis=-1) + high_action = np.repeat(wrapped_action_space.high, horizon, axis=-1) + + low = np.concatenate((low_obs, low_action)) + high = np.concatenate((high_obs, high_action)) + + # Overwrite the observation space + env.observation_space.spaces["observation"] = gym.spaces.Box( + low=low, high=high, dtype=wrapped_obs_space.dtype + ) + + super(HistoryWrapperObsDict, self).__init__(env) + + self.horizon = horizon + self.low_action, self.high_action = low_action, high_action + self.low_obs, self.high_obs = low_obs, high_obs + self.low, self.high = low, high + self.obs_history = np.zeros(low_obs.shape, low_obs.dtype) + self.action_history = np.zeros(low_action.shape, low_action.dtype) + + def _create_obs_from_history(self): + return np.concatenate((self.obs_history, self.action_history)) + + def reset(self): + # Flush the history + self.obs_history[...] = 0 + self.action_history[...] = 0 + obs_dict = self.env.reset() + obs = obs_dict["observation"] + self.obs_history[..., -obs.shape[-1] :] = obs + + obs_dict["observation"] = self._create_obs_from_history() + + return obs_dict + + def step(self, action): + obs_dict, reward, done, info = self.env.step(action) + obs = obs_dict["observation"] + last_ax_size = obs.shape[-1] + + self.obs_history = np.roll(self.obs_history, shift=-last_ax_size, axis=-1) + self.obs_history[..., -obs.shape[-1] :] = obs + + self.action_history = np.roll( + self.action_history, shift=-action.shape[-1], axis=-1 + ) + self.action_history[..., -action.shape[-1] :] = action + + obs_dict["observation"] = self._create_obs_from_history() + + return obs_dict, reward, done, info + + +class PlotActionWrapper(gym.Wrapper): + """ + Wrapper for plotting the taken actions. + Only works with 1D actions for now. + Optionally, it can be used to plot the observations too. + + :param env: (gym.Env) + :param plot_freq: (int) Plot every `plot_freq` episodes + """ + + def __init__(self, env, plot_freq=5): + super(PlotActionWrapper, self).__init__(env) + self.plot_freq = plot_freq + self.current_episode = 0 + # Observation buffer (Optional) + # self.observations = [] + # Action buffer + self.actions = [] + + def reset(self): + self.current_episode += 1 + if self.current_episode % self.plot_freq == 0: + self.plot() + # Reset + self.actions = [] + obs = self.env.reset() + self.actions.append([]) + # self.observations.append(obs) + return obs + + def step(self, action): + obs, reward, done, info = self.env.step(action) + + self.actions[-1].append(action) + # self.observations.append(obs) + + return obs, reward, done, info + + def plot(self): + actions = self.actions + x = np.arange(sum([len(episode) for episode in actions])) + plt.figure("Actions") + plt.title("Actions during exploration", fontsize=14) + plt.xlabel("Timesteps", fontsize=14) + plt.ylabel("Action", fontsize=14) + + start = 0 + for i in range(len(self.actions)): + end = start + len(self.actions[i]) + plt.plot(x[start:end], self.actions[i]) + # Clipped actions: real behavior, note that it is between [-2, 2] for the Pendulum + # plt.scatter(x[start:end], np.clip(self.actions[i], -1, 1), s=1) + # plt.scatter(x[start:end], self.actions[i], s=1) + start = end + + plt.show() + + +class FeatureExtractorFreezeParammetersWrapper(gym.Wrapper): + """ + Freezes parameters of the feature extractor. + """ + + def __init__(self, env: gym.Env): + + super(FeatureExtractorFreezeParammetersWrapper, self).__init__(env) + for param in self.feature_extractor.parameters(): + param.requires_grad = False diff --git a/env_manager/rbs_gym/resource/rbs_gym b/env_manager/rbs_gym/resource/rbs_gym new file mode 100644 index 0000000..e69de29 diff --git a/env_manager/rbs_gym/setup.cfg b/env_manager/rbs_gym/setup.cfg new file mode 100644 index 0000000..759913d --- /dev/null +++ b/env_manager/rbs_gym/setup.cfg @@ -0,0 +1,4 @@ +[develop] +script_dir=$base/lib/rbs_gym +[install] +install_scripts=$base/lib/rbs_gym diff --git a/env_manager/rbs_gym/setup.py b/env_manager/rbs_gym/setup.py new file mode 100644 index 0000000..e280fa4 --- /dev/null +++ b/env_manager/rbs_gym/setup.py @@ -0,0 +1,36 @@ +import os +from glob import glob + +from setuptools import find_packages, setup + +package_name = "rbs_gym" + +setup( + name=package_name, + version="0.0.0", + packages=find_packages(exclude=["test"]), + data_files=[ + ("share/ament_index/resource_index/packages", ["resource/" + package_name]), + ("share/" + package_name, ["package.xml"]), + ( + os.path.join("share", package_name, "launch"), + glob(os.path.join("launch", "*launch.[pxy][yma]*")), + ), + ], + install_requires=["setuptools"], + zip_safe=True, + maintainer="narmak", + maintainer_email="ur.narmak@gmail.com", + description="TODO: Package description", + license="Apache-2.0", + tests_require=["pytest"], + entry_points={ + "console_scripts": [ + "train = rbs_gym.scripts.train:main", + "spawner = rbs_gym.scripts.spawner:main", + "velocity = rbs_gym.scripts.velocity:main", + "test_agent = rbs_gym.scripts.test_agent:main", + "evaluate = rbs_gym.scripts.evaluate:main", + ], + }, +) diff --git a/env_manager/rbs_gym/test/test_copyright.py b/env_manager/rbs_gym/test/test_copyright.py new file mode 100644 index 0000000..97a3919 --- /dev/null +++ b/env_manager/rbs_gym/test/test_copyright.py @@ -0,0 +1,25 @@ +# Copyright 2015 Open Source Robotics Foundation, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from ament_copyright.main import main +import pytest + + +# Remove the `skip` decorator once the source file(s) have a copyright header +@pytest.mark.skip(reason='No copyright header has been placed in the generated source file.') +@pytest.mark.copyright +@pytest.mark.linter +def test_copyright(): + rc = main(argv=['.', 'test']) + assert rc == 0, 'Found errors' diff --git a/env_manager/rbs_gym/test/test_flake8.py b/env_manager/rbs_gym/test/test_flake8.py new file mode 100644 index 0000000..27ee107 --- /dev/null +++ b/env_manager/rbs_gym/test/test_flake8.py @@ -0,0 +1,25 @@ +# Copyright 2017 Open Source Robotics Foundation, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from ament_flake8.main import main_with_errors +import pytest + + +@pytest.mark.flake8 +@pytest.mark.linter +def test_flake8(): + rc, errors = main_with_errors(argv=[]) + assert rc == 0, \ + 'Found %d code style errors / warnings:\n' % len(errors) + \ + '\n'.join(errors) diff --git a/env_manager/rbs_gym/test/test_pep257.py b/env_manager/rbs_gym/test/test_pep257.py new file mode 100644 index 0000000..b234a38 --- /dev/null +++ b/env_manager/rbs_gym/test/test_pep257.py @@ -0,0 +1,23 @@ +# Copyright 2015 Open Source Robotics Foundation, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from ament_pep257.main import main +import pytest + + +@pytest.mark.linter +@pytest.mark.pep257 +def test_pep257(): + rc = main(argv=['.', 'test']) + assert rc == 0, 'Found code style errors / warnings' diff --git a/env_manager/rbs_runtime/LICENSE b/env_manager/rbs_runtime/LICENSE new file mode 100644 index 0000000..d645695 --- /dev/null +++ b/env_manager/rbs_runtime/LICENSE @@ -0,0 +1,202 @@ + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/env_manager/rbs_runtime/config/default-scene-config.yaml b/env_manager/rbs_runtime/config/default-scene-config.yaml new file mode 100644 index 0000000..7016a9a --- /dev/null +++ b/env_manager/rbs_runtime/config/default-scene-config.yaml @@ -0,0 +1,249 @@ +camera: + - clip_color: !tuple + - 0.01 + - 1000.0 + clip_depth: !tuple + - 0.05 + - 10.0 + enable: true + height: 128 + horizontal_fov: 1.0471975511965976 + image_format: R8G8B8 + name: robot_camera + noise_mean: null + noise_stddev: null + publish_color: true + publish_depth: true + publish_points: true + random_pose_focal_point_z_offset: 0.0 + random_pose_mode: orbit + random_pose_orbit_distance: 1.0 + random_pose_orbit_height_range: !tuple + - 0.1 + - 0.7 + random_pose_orbit_ignore_arc_behind_robot: 0.39269908169872414 + random_pose_rollout_counter: 0.0 + random_pose_rollouts_num: 1 + random_pose_select_position_options: [] + relative_to: base_link + spawn_position: !tuple + - 0.0 + - 0.0 + - 1.0 + spawn_quat_xyzw: !tuple + - 0.0 + - 0.70710678118 + - 0.0 + - 0.70710678118 + type: rgbd_camera + update_rate: 10 + vertical_fov: 1.0471975511965976 + width: 128 +gravity: !tuple + - 0.0 + - 0.0 + - -9.80665 +gravity_std: !tuple + - 0.0 + - 0.0 + - 0.0232 +light: + color: !tuple + - 1.0 + - 1.0 + - 1.0 + - 1.0 + direction: !tuple + - 0.5 + - -0.25 + - -0.75 + distance: 1000.0 + model_rollouts_num: 1 + radius: 25.0 + random_minmax_elevation: !tuple + - -0.15 + - -0.65 + type: sun + visual: true +objects: + - color: null + name: star + orientation: !tuple + - 1.0 + - 0.0 + - 0.0 + - 0.0 + position: !tuple + - -0.1 + - -0.40 + - 0.1 + randomize: + count: 0 + models_rollouts_num: 0 + random_color: false + random_model: false + random_orientation: false + random_pose: false + random_position: false + random_spawn_position_segments: [] + random_spawn_position_update_workspace_centre: false + random_spawn_volume: !tuple + - 0.5 + - 0.5 + - 0.5 + relative_to: world + static: false + texture: [] + type: "model" + + - color: null + name: box + mass: 1.0 + size: !tuple + - 0.02 + - 0.02 + - 0.05 + orientation: !tuple + - 1.0 + - 0.0 + - 0.0 + - 0.0 + position: !tuple + - -0.1 + - -0.37 + - 0.1 + randomize: + count: 0 + models_rollouts_num: 0 + random_color: false + random_model: false + random_orientation: false + random_pose: false + random_position: false + random_spawn_position_segments: [] + random_spawn_position_update_workspace_centre: false + random_spawn_volume: !tuple + - 0.5 + - 0.5 + - 0.5 + relative_to: world + static: false + type: "box" + + + - color: null + name: cylinder + mass: 1.0 + radius: 0.01 + length: 0.05 + orientation: !tuple + - 1.0 + - 0.0 + - 0.0 + - 0.0 + position: !tuple + - -0.1 + - -0.34 + - 0.1 + randomize: + count: 0 + models_rollouts_num: 0 + random_color: false + random_model: false + random_orientation: false + random_pose: false + random_position: false + random_spawn_position_segments: [] + random_spawn_position_update_workspace_centre: false + random_spawn_volume: !tuple + - 0.5 + - 0.5 + - 0.5 + relative_to: world + static: false + type: "cylinder" + + - color: null + name: board + orientation: !tuple + - 1.0 + - 0.0 + - 0.0 + - 0.0 + position: !tuple + - 0.0 + - -0.37 + - 0.01 + randomize: + count: 0 + models_rollouts_num: 0 + random_color: false + random_model: false + random_orientation: false + random_pose: false + random_position: false + random_spawn_position_segments: [] + random_spawn_position_update_workspace_centre: false + random_spawn_volume: !tuple + - 0.5 + - 0.5 + - 0.5 + relative_to: world + static: true + texture: [] + type: "model" +physics_rollouts_num: 0 +plugins: + fts_broadcaster: false + scene_broadcaster: false + sensors_render_engine: ogre2 + user_commands: false +robot: + gripper_joint_positions: 0.0 + joint_positions: + - -1.57 + - 0.5 + - 3.14159 + - 1.5 + - 0.0 + - 1.4 + - 0.0 + name: rbs_arm + randomizer: + joint_positions: false + joint_positions_above_object_spawn: false + joint_positions_above_object_spawn_elevation: 0.2 + joint_positions_above_object_spawn_xy_randomness: 0.2 + joint_positions_std: 0.1 + pose: false + spawn_volume: !tuple + - 1.0 + - 1.0 + - 0.0 + spawn_position: !tuple + - 0.0 + - 0.0 + - 0.0 + spawn_quat_xyzw: !tuple + - 0.0 + - 0.0 + - 0.0 + - 1.0 + urdf_string: "" + with_gripper: true +terrain: + model_rollouts_num: 1 + name: ground + size: !tuple + - 1.5 + - 1.5 + spawn_position: !tuple + - 0 + - 0 + - 0 + spawn_quat_xyzw: !tuple + - 0 + - 0 + - 0 + - 1 + type: flat diff --git a/env_manager/rbs_runtime/launch/runtime.launch.py b/env_manager/rbs_runtime/launch/runtime.launch.py new file mode 100644 index 0000000..fa5387f --- /dev/null +++ b/env_manager/rbs_runtime/launch/runtime.launch.py @@ -0,0 +1,330 @@ +import os + +import xacro +import yaml +from ament_index_python.packages import get_package_share_directory +from launch import LaunchDescription +from launch.actions import ( + DeclareLaunchArgument, + IncludeLaunchDescription, + OpaqueFunction, + TimerAction, +) +from launch.launch_description_sources import PythonLaunchDescriptionSource +from launch.launch_introspector import indent +from launch.substitutions import LaunchConfiguration, PathJoinSubstitution +from launch_ros.actions import Node +from launch_ros.substitutions import FindPackageShare +from robot_builder.external.ros2_control import ControllerManager +from robot_builder.parser.urdf import URDF_parser +from rbs_utils.launch import load_xacro_args + + +def launch_setup(context, *args, **kwargs): + # Initialize Arguments + robot_type = LaunchConfiguration("robot_type") + # General arguments + with_gripper_condition = LaunchConfiguration("with_gripper") + description_package = LaunchConfiguration("description_package") + description_file = LaunchConfiguration("description_file") + use_moveit = LaunchConfiguration("use_moveit") + moveit_config_package = LaunchConfiguration("moveit_config_package") + moveit_config_file = LaunchConfiguration("moveit_config_file") + use_sim_time = LaunchConfiguration("use_sim_time") + scene_config_file = LaunchConfiguration("scene_config_file").perform(context) + ee_link_name = LaunchConfiguration("ee_link_name").perform(context) + base_link_name = LaunchConfiguration("base_link_name").perform(context) + control_space = LaunchConfiguration("control_space").perform(context) + control_strategy = LaunchConfiguration("control_strategy").perform(context) + interactive = LaunchConfiguration("interactive").perform(context) + real_robot = LaunchConfiguration("real_robot").perform(context) + + use_rbs_utils = LaunchConfiguration("use_rbs_utils") + assembly_config_name = LaunchConfiguration("assembly_config_name") + + if not scene_config_file == "": + config_file = {"config_file": scene_config_file} + else: + config_file = {} + + description_package_abs_path = get_package_share_directory( + description_package.perform(context) + ) + + controllers_file = os.path.join( + description_package_abs_path, "config", "controllers.yaml" + ) + + xacro_file = os.path.join( + description_package_abs_path, + "urdf", + description_file.perform(context), + ) + + # xacro_config_file = f"{description_package_abs_path}/config/xacro_args.yaml" + xacro_config_file = os.path.join( + description_package_abs_path, "urdf", "xacro_args.yaml" + ) + + + mappings_data = load_xacro_args(xacro_config_file, locals()) + + robot_description_doc = xacro.process_file(xacro_file, mappings=mappings_data) + + robot_description_semantic_content = "" + + if use_moveit.perform(context) == "true": + srdf_config_file = os.path.join( + get_package_share_directory(moveit_config_package.perform(context)), + "srdf", + "xacro_args.yaml", + ) + srdf_file = os.path.join( + get_package_share_directory(moveit_config_package.perform(context)), + "srdf", + moveit_config_file.perform(context), + ) + srdf_mappings = load_xacro_args(srdf_config_file, locals()) + robot_description_semantic_content = xacro.process_file( + srdf_file, mappings=srdf_mappings + ) + robot_description_semantic_content = ( + robot_description_semantic_content.toprettyxml(indent=" ") + ) + control_space = "joint" + control_strategy = "position" + interactive = "false" + + robot_description_content = robot_description_doc.toprettyxml(indent=" ") + robot_description = {"robot_description": robot_description_content} + + # Parse robot and configure controller's file for ControllerManager + robot = URDF_parser.load_string( + robot_description_content, ee_link_name=ee_link_name + ) + ControllerManager.save_to_yaml( + robot, description_package_abs_path, "controllers.yaml" + ) + + rbs_robot_setup = IncludeLaunchDescription( + PythonLaunchDescriptionSource( + [ + PathJoinSubstitution( + [FindPackageShare("rbs_bringup"), "launch", "rbs_robot.launch.py"] + ) + ] + ), + launch_arguments={ + "with_gripper": with_gripper_condition, + "controllers_file": controllers_file, + "robot_type": robot_type, + "description_package": description_package, + "description_file": description_file, + "robot_name": robot_type, + "use_moveit": use_moveit, + "moveit_config_package": moveit_config_package, + "moveit_config_file": moveit_config_file, + "use_sim_time": use_sim_time, + "use_controllers": "true", + "robot_description": robot_description_content, + "robot_description_semantic": robot_description_semantic_content, + "base_link_name": base_link_name, + "ee_link_name": ee_link_name, + "control_space": control_space, + "control_strategy": control_strategy, + "interactive_control": interactive, + "use_rbs_utils": use_rbs_utils, + "assembly_config_name": assembly_config_name, + }.items(), + ) + + if real_robot == "true": + controller_manager_node = Node( + package="controller_manager", + executable="ros2_control_node", + parameters=[ + robot_description, + controllers_file, + ], + output="screen", + ) + return [rbs_robot_setup, controller_manager_node] + + rbs_runtime = Node( + package="rbs_runtime", + executable="runtime", + arguments=[("--ros-args --remap log_level:=debug")], + parameters=[robot_description, config_file, {"use_sim_time": True}], + ) + + clock_bridge = Node( + package="ros_gz_bridge", + executable="parameter_bridge", + arguments=["/clock@rosgraph_msgs/msg/Clock[ignition.msgs.Clock"], + output="screen", + ) + + delay_robot_control_stack = TimerAction(period=10.0, actions=[rbs_robot_setup]) + + nodes_to_start = [rbs_runtime, clock_bridge, delay_robot_control_stack] + return nodes_to_start + + +def generate_launch_description(): + declared_arguments = [] + declared_arguments.append( + DeclareLaunchArgument( + "robot_type", + description="Type of robot by name", + choices=[ + "rbs_arm", + "ar4", + "ur3", + "ur3e", + "ur5", + "ur5e", + "ur10", + "ur10e", + "ur16e", + ], + default_value="rbs_arm", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "description_package", + default_value="rbs_arm", + description="Description package with robot URDF/XACRO files. Usually the argument \ + is not set, it enables use of a custom description.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "description_file", + default_value="rbs_arm_modular.xacro", + description="URDF/XACRO description file with the robot.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "robot_name", + default_value="arm0", + description="Name for robot, used to apply namespace for specific robot in multirobot setup", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "moveit_config_package", + default_value="rbs_arm", + description="MoveIt config package with robot SRDF/XACRO files. Usually the argument \ + is not set, it enables use of a custom moveit config.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "moveit_config_file", + default_value="rbs_arm.srdf.xacro", + description="MoveIt SRDF/XACRO description file with the robot.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "use_sim_time", + default_value="true", + description="Make MoveIt to use simulation time.\ + This is needed for the trajectory planing in simulation.", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "with_gripper", default_value="true", description="With gripper or not?" + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "use_moveit", default_value="false", description="Launch moveit?" + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "launch_perception", default_value="false", description="Launch perception?" + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "use_controllers", + default_value="true", + description="Launch controllers?", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "scene_config_file", + default_value="", + description="Path to a scene configuration file", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "ee_link_name", + default_value="", + description="End effector name of robot arm", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "base_link_name", + default_value="", + description="Base link name if robot arm", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "control_space", + default_value="task", + choices=["task", "joint"], + description="Specify the control space for the robot (e.g., task space).", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "control_strategy", + default_value="position", + choices=["position", "velocity", "effort"], + description="Specify the control strategy (e.g., position control).", + ) + ) + declared_arguments.append( + DeclareLaunchArgument( + "interactive", + default_value="true", + description="Wheter to run the motion_control_handle controller", + ), + ) + declared_arguments.append( + DeclareLaunchArgument( + "real_robot", + default_value="false", + description="Wheter to run on the real robot", + ), + ) + + declared_arguments.append( + DeclareLaunchArgument( + "use_rbs_utils", + default_value="true", + description="Wheter to use rbs_utils", + ), + ) + + declared_arguments.append( + DeclareLaunchArgument( + "assembly_config_name", + default_value="", + description="Assembly config name from rbs_assets_library", + ), + ) + + return LaunchDescription( + declared_arguments + [OpaqueFunction(function=launch_setup)] + ) diff --git a/env_manager/rbs_runtime/package.nix b/env_manager/rbs_runtime/package.nix new file mode 100644 index 0000000..7b9613b --- /dev/null +++ b/env_manager/rbs_runtime/package.nix @@ -0,0 +1,31 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license +{ + lib, + buildRosPackage, + ament-copyright, + ament-flake8, + ament-pep257, + env-manager, + env-manager-interfaces, + pythonPackages, + scenario, + robot-builder, + rbs-utils +}: +buildRosPackage rec { + pname = "ros-jazzy-rbs-runtime"; + version = "0.0.0"; + + src = ./.; + + buildType = "ament_python"; + checkInputs = [ament-copyright ament-flake8 ament-pep257 pythonPackages.pytest]; + propagatedBuildInputs = [pythonPackages.dacite scenario env-manager env-manager-interfaces robot-builder rbs-utils]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [asl20]; + }; +} diff --git a/env_manager/rbs_runtime/package.xml b/env_manager/rbs_runtime/package.xml new file mode 100644 index 0000000..420d865 --- /dev/null +++ b/env_manager/rbs_runtime/package.xml @@ -0,0 +1,22 @@ + + + + rbs_runtime + 0.0.0 + TODO: Package description + narmak + Apache-2.0 + + env_manager + env_manager_interfaces + robot_builder + + ament_copyright + ament_flake8 + ament_pep257 + python3-pytest + + + ament_python + + diff --git a/env_manager/rbs_runtime/rbs_runtime/__init__.py b/env_manager/rbs_runtime/rbs_runtime/__init__.py new file mode 100644 index 0000000..029c56e --- /dev/null +++ b/env_manager/rbs_runtime/rbs_runtime/__init__.py @@ -0,0 +1,41 @@ +from pathlib import Path + +import yaml +from dacite import from_dict +from env_manager.models.configs import SceneData + +from typing import Dict, Any +from env_manager.models.configs import ( + BoxObjectData, CylinderObjectData, MeshData, ModelData, ObjectData, ObjectRandomizerData +) + +def object_factory(obj_data: Dict[str, Any]) -> ObjectData: + obj_type = obj_data.get('type', '') + + if "randomize" in obj_data and isinstance(obj_data["randomize"], dict): + obj_data["randomize"] = from_dict(data_class=ObjectRandomizerData, data=obj_data["randomize"]) + + if obj_type == 'box': + return from_dict(data_class=BoxObjectData, data=obj_data) + elif obj_type == 'cylinder': + return from_dict(data_class=CylinderObjectData, data=obj_data) + elif obj_type == 'mesh': + return from_dict(data_class=MeshData, data=obj_data) + elif obj_type == 'model': + return from_dict(data_class=ModelData, data=obj_data) + else: + return from_dict(data_class=ObjectData, data=obj_data) + +def scene_config_loader(file: str | Path) -> SceneData: + def tuple_constructor(loader, node): + return tuple(loader.construct_sequence(node)) + + with open(file, "r") as yaml_file: + yaml.SafeLoader.add_constructor("!tuple", tuple_constructor) + scene_cfg = yaml.load(yaml_file, Loader=yaml.SafeLoader) + + scene_data = from_dict(data_class=SceneData, data=scene_cfg) + + scene_data.objects = [object_factory(obj) for obj in scene_cfg.get('objects', [])] + + return scene_data diff --git a/env_manager/rbs_runtime/rbs_runtime/scripts/__init__.py b/env_manager/rbs_runtime/rbs_runtime/scripts/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/env_manager/rbs_runtime/rbs_runtime/scripts/runtime.py b/env_manager/rbs_runtime/rbs_runtime/scripts/runtime.py new file mode 100755 index 0000000..e234263 --- /dev/null +++ b/env_manager/rbs_runtime/rbs_runtime/scripts/runtime.py @@ -0,0 +1,73 @@ +#!/usr/bin/python3 + +import rclpy +from ament_index_python.packages import get_package_share_directory +from env_manager.scene import Scene +from env_manager_interfaces.srv import ResetEnv +from rbs_assets_library import get_world_file +from rclpy.node import Node +from scenario.bindings.gazebo import GazeboSimulator +from rclpy.executors import MultiThreadedExecutor, ExternalShutdownException + +from .. import scene_config_loader + +class GazeboRuntime(Node): + def __init__(self) -> None: + super().__init__(node_name="rbs_gz_runtime") + self.declare_parameter("robot_description", "") + self.declare_parameter( + "config_file", + get_package_share_directory("rbs_runtime") + + "/config/default-scene-config.yaml", + ) + + self.gazebo = GazeboSimulator(step_size=0.001, rtf=1.0, steps_per_run=1) + + self.gazebo.insert_world_from_sdf(get_world_file("default")) + if not self.gazebo.initialize(): + raise RuntimeError("Gazebo cannot be initialized") + + config_file = ( + self.get_parameter("config_file").get_parameter_value().string_value + ) + + scene_data = scene_config_loader(config_file) + + self.scene = Scene( + node=self, + gazebo=self.gazebo, + scene=scene_data, + robot_urdf_string=self.get_parameter("robot_description") + .get_parameter_value() + .string_value, + ) + self.scene.init_scene() + + self.reset_env_srv = self.create_service( + ResetEnv, "/env_manager/reset_env", self.reset_env + ) + self.is_env_reset = False + self.timer = self.create_timer(self.gazebo.step_size(), self.gazebo_run) + + def gazebo_run(self): + if self.is_env_reset: + self.scene.reset_scene() + self.is_env_reset = False + self.gazebo.run() + + def reset_env(self, req, res): + self.is_env_reset = True + res.ok = self.is_env_reset + return res + + +def main(): + rclpy.init() + + executor = MultiThreadedExecutor() + node = GazeboRuntime() + executor.add_node(node) + try: + executor.spin() + except (KeyboardInterrupt, ExternalShutdownException): + node.destroy_node() diff --git a/env_manager/rbs_runtime/resource/rbs_runtime b/env_manager/rbs_runtime/resource/rbs_runtime new file mode 100644 index 0000000..e69de29 diff --git a/env_manager/rbs_runtime/setup.cfg b/env_manager/rbs_runtime/setup.cfg new file mode 100644 index 0000000..27e6f37 --- /dev/null +++ b/env_manager/rbs_runtime/setup.cfg @@ -0,0 +1,4 @@ +[develop] +script_dir=$base/lib/rbs_runtime +[install] +install_scripts=$base/lib/rbs_runtime diff --git a/env_manager/rbs_runtime/setup.py b/env_manager/rbs_runtime/setup.py new file mode 100644 index 0000000..12ce2cd --- /dev/null +++ b/env_manager/rbs_runtime/setup.py @@ -0,0 +1,36 @@ +import os +from glob import glob + +from setuptools import find_packages, setup + +package_name = "rbs_runtime" + +setup( + name=package_name, + version="0.0.0", + packages=find_packages(exclude=["test"]), + data_files=[ + ("share/ament_index/resource_index/packages", ["resource/" + package_name]), + ("share/" + package_name, ["package.xml"]), + ( + os.path.join("share", package_name, "launch"), + glob(os.path.join("launch", "*launch.[pxy][yma]*")), + ), + ( + os.path.join("share", package_name, "config"), + glob(os.path.join("config", "*config.[yma]*")), + ), + ], + install_requires=["setuptools", "dacite"], + zip_safe=True, + maintainer="narmak", + maintainer_email="ur.narmak@gmail.com", + description="TODO: Package description", + license="Apache-2.0", + tests_require=["pytest"], + entry_points={ + "console_scripts": [ + "runtime = rbs_runtime.scripts.runtime:main", + ], + }, +) diff --git a/env_manager/rbs_runtime/test/test_copyright.py b/env_manager/rbs_runtime/test/test_copyright.py new file mode 100644 index 0000000..97a3919 --- /dev/null +++ b/env_manager/rbs_runtime/test/test_copyright.py @@ -0,0 +1,25 @@ +# Copyright 2015 Open Source Robotics Foundation, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from ament_copyright.main import main +import pytest + + +# Remove the `skip` decorator once the source file(s) have a copyright header +@pytest.mark.skip(reason='No copyright header has been placed in the generated source file.') +@pytest.mark.copyright +@pytest.mark.linter +def test_copyright(): + rc = main(argv=['.', 'test']) + assert rc == 0, 'Found errors' diff --git a/env_manager/rbs_runtime/test/test_flake8.py b/env_manager/rbs_runtime/test/test_flake8.py new file mode 100644 index 0000000..27ee107 --- /dev/null +++ b/env_manager/rbs_runtime/test/test_flake8.py @@ -0,0 +1,25 @@ +# Copyright 2017 Open Source Robotics Foundation, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from ament_flake8.main import main_with_errors +import pytest + + +@pytest.mark.flake8 +@pytest.mark.linter +def test_flake8(): + rc, errors = main_with_errors(argv=[]) + assert rc == 0, \ + 'Found %d code style errors / warnings:\n' % len(errors) + \ + '\n'.join(errors) diff --git a/env_manager/rbs_runtime/test/test_pep257.py b/env_manager/rbs_runtime/test/test_pep257.py new file mode 100644 index 0000000..b234a38 --- /dev/null +++ b/env_manager/rbs_runtime/test/test_pep257.py @@ -0,0 +1,23 @@ +# Copyright 2015 Open Source Robotics Foundation, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from ament_pep257.main import main +import pytest + + +@pytest.mark.linter +@pytest.mark.pep257 +def test_pep257(): + rc = main(argv=['.', 'test']) + assert rc == 0, 'Found code style errors / warnings' diff --git a/flake.lock b/flake.lock new file mode 100644 index 0000000..c0748ae --- /dev/null +++ b/flake.lock @@ -0,0 +1,84 @@ +{ + "nodes": { + "flake-utils": { + "inputs": { + "systems": "systems" + }, + "locked": { + "lastModified": 1731533236, + "narHash": "sha256-l0KFg5HjrsfsO/JpG+r7fRrqm12kzFHyUHqHCVpMMbI=", + "owner": "numtide", + "repo": "flake-utils", + "rev": "11707dc2f618dd54ca8739b309ec4fc024de578b", + "type": "github" + }, + "original": { + "owner": "numtide", + "repo": "flake-utils", + "type": "github" + } + }, + "nix-ros-overlay": { + "inputs": { + "flake-utils": "flake-utils", + "nixpkgs": "nixpkgs" + }, + "locked": { + "lastModified": 1745796487, + "narHash": "sha256-xvre4xiezhPhU794dpjcHusVLBIfA4jPg9Kq439x4yY=", + "owner": "lopsided98", + "repo": "nix-ros-overlay", + "rev": "4072d6ed51d9053d2cc85c0ec4f69884cc99f392", + "type": "github" + }, + "original": { + "owner": "lopsided98", + "ref": "develop", + "repo": "nix-ros-overlay", + "type": "github" + } + }, + "nixpkgs": { + "locked": { + "lastModified": 1744849697, + "narHash": "sha256-S9hqvanPSeRu6R4cw0OhvH1rJ+4/s9xIban9C4ocM/0=", + "owner": "lopsided98", + "repo": "nixpkgs", + "rev": "6318f538166fef9f5118d8d78b9b43a04bb049e4", + "type": "github" + }, + "original": { + "owner": "lopsided98", + "ref": "nix-ros", + "repo": "nixpkgs", + "type": "github" + } + }, + "root": { + "inputs": { + "nix-ros-overlay": "nix-ros-overlay", + "nixpkgs": [ + "nix-ros-overlay", + "nixpkgs" + ] + } + }, + "systems": { + "locked": { + "lastModified": 1681028828, + "narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=", + "owner": "nix-systems", + "repo": "default", + "rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e", + "type": "github" + }, + "original": { + "owner": "nix-systems", + "repo": "default", + "type": "github" + } + } + }, + "root": "root", + "version": 7 +} diff --git a/flake.nix b/flake.nix new file mode 100644 index 0000000..9be5c16 --- /dev/null +++ b/flake.nix @@ -0,0 +1,124 @@ +{ + inputs = { + nix-ros-overlay.url = "github:lopsided98/nix-ros-overlay/develop"; + nixpkgs.follows = "nix-ros-overlay/nixpkgs"; # IMPORTANT!!! + }; + outputs = { + self, + nix-ros-overlay, + nixpkgs, + }: + nix-ros-overlay.inputs.flake-utils.lib.eachDefaultSystem (system: let + applyDistroOverlay = rosOverlay: rosPackages: + rosPackages + // builtins.mapAttrs ( + rosDistro: rosPkgs: + if rosPkgs ? overrideScope + then rosPkgs.overrideScope rosOverlay + else rosPkgs + ) + rosPackages; + rosDistroOverlays = self: super: { + rosPackages = applyDistroOverlay (import ./nix/overlay.nix) super.rosPackages; + }; + pythonOverlay = self: super: { + pythonPackagesExtensions = super.pythonPackagesExtensions ++ [ + ( + python-final: python-prev: { + rbs-assets-library = self.python3Packages.callPackage ./nix/repos/rbs-assets-library.nix { }; + } + ) + ]; + }; + pkgs = import nixpkgs { + inherit system; + overlays = [ + nix-ros-overlay.overlays.default + rosDistroOverlays + pythonOverlay + ]; + config.permittedInsecurePackages = [ + "freeimage-3.18.0-unstable-2024-04-18" + ]; + }; + zsh-autocompletions = pkgs.runCommand "ros-autocompletions" {} '' + for dir in {bash-completion/completions,zsh/site-functions}; do + mkdir -p $out/share/$dir + for program in {ros2,colcon,rosidl}; do + ${pkgs.python3.pkgs.argcomplete}/bin/register-python-argcomplete $program > $out/share/$dir/_$program + done + done + ''; + use_zsh = true; + + rosDistro = "jazzy"; + in { + legacyPackages = pkgs.rosPackages; + packages = builtins.intersectAttrs (import ./nix/overlay.nix null null) pkgs.rosPackages.${rosDistro}; + checks = builtins.intersectAttrs (import ./nix/overlay.nix null null) pkgs.rosPackages.${rosDistro}; + devShells.default = pkgs.mkShell { + name = "Robossembler ROS2"; + packages = + [ + pkgs.colcon + # ... other non-ROS packages + (with pkgs.rosPackages.${rosDistro}; + buildEnv { + paths = [ + ros-core + rbs-bringup + # Include simulation runtime + rbs-runtime + # robot package + rbs-arm + + # dynamixel + dynamixel-hardware + dynamixel-hardware-interface + dynamixel-interfaces + dynamixel-sdk + dynamixel-sdk-custom-interfaces + dynamixel-sdk-examples + dynamixel-workbench + dynamixel-workbench-msgs + dynamixel-workbench-toolbox + + ffw + ffw-bringup + ffw-description + ffw-joint-trajectory-command-broadcaster + ffw-joystick-controller + ffw-moveit-config + ffw-spring-actuator-controller + ffw-teleop + ]; + }) + ] + ++ ( + if use_zsh + then [zsh-autocompletions pkgs.zsh] + else [] + ); + shellHook = '' + ${ + if use_zsh + then '' + echo "Swithching to ZSH shell..." + export SHELL=$(which zsh) + exec zsh + '' + else '''' + } + nix store gc + ''; + }; + }); + nixConfig = { + extra-substituters = ["https://ros.cachix.org" "https://robossembler.cachix.org" "https://cuda-maintainers.cachix.org"]; + extra-trusted-public-keys = [ + "ros.cachix.org-1:dSyZxI8geDCJrwgvCOHDoAfOm5sV1wCPjBkKL+38Rvo=" + "robossembler.cachix.org-1:56jBJHroRQSGpZFkW8XMquuzQTjAF/XTo6MogmBM7SQ=" + "cuda-maintainers.cachix.org-1:0dq3bujKpuEPMCX6U4WylrUDZ9JyUG0VpVZa7CNfq5E=" + ]; + }; +} diff --git a/nix/behaviortree-ros2.nix b/nix/behaviortree-ros2.nix new file mode 100644 index 0000000..487a5f3 --- /dev/null +++ b/nix/behaviortree-ros2.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, behaviortree-cpp, boost, btcpp-ros2-interfaces, fmt, generate-parameter-library, rclcpp, rclcpp-action }: +buildRosPackage rec { + pname = "ros-jazzy-behaviortree-ros2"; + version = "0.2.0"; + + src = fetchFromGitHub { + owner = "BehaviorTree"; + repo = "BehaviorTree.ROS2"; + rev = "cc31ea7b97947f1aac6e8c37df6cec379c84a7d9"; + sha256 = "0m0n85jab14rfssyjf9sf05rq1rdzs6kqwb467953f26bvcnckkh"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/behaviortree_ros2/"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ behaviortree-cpp boost btcpp-ros2-interfaces fmt generate-parameter-library rclcpp rclcpp-action ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "This package provides a ROS2 wrapper, on top of BehaviorTree.CPP."; + license = with lib.licenses; [ mit ]; + }; +} diff --git a/nix/btcpp-ros2-interfaces.nix b/nix/btcpp-ros2-interfaces.nix new file mode 100644 index 0000000..4d2c2a4 --- /dev/null +++ b/nix/btcpp-ros2-interfaces.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, action-msgs, ament-cmake, rosidl-default-generators, rosidl-default-runtime }: +buildRosPackage rec { + pname = "ros-jazzy-btcpp-ros2-interfaces"; + version = "0.2.0"; + + src = fetchFromGitHub { + owner = "BehaviorTree"; + repo = "BehaviorTree.ROS2"; + rev = "cc31ea7b97947f1aac6e8c37df6cec379c84a7d9"; + sha256 = "0m0n85jab14rfssyjf9sf05rq1rdzs6kqwb467953f26bvcnckkh"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/btcpp_ros2_interfaces/"; + buildInputs = [ ament-cmake rosidl-default-generators ]; + propagatedBuildInputs = [ action-msgs rosidl-default-runtime ]; + nativeBuildInputs = [ ament-cmake rosidl-default-generators ]; + + meta = { + description = "ROS2 interfaces, mostly used to demonstrate behaviortree_ros2"; + license = with lib.licenses; [ mit ]; + }; +} diff --git a/nix/btcpp-ros2-samples.nix b/nix/btcpp-ros2-samples.nix new file mode 100644 index 0000000..65e2fdb --- /dev/null +++ b/nix/btcpp-ros2-samples.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, behaviortree-ros2, btcpp-ros2-interfaces, std-msgs, std-srvs }: +buildRosPackage rec { + pname = "ros-jazzy-btcpp-ros2-samples"; + version = "0.2.0"; + + src = fetchFromGitHub { + owner = "BehaviorTree"; + repo = "BehaviorTree.ROS2"; + rev = "cc31ea7b97947f1aac6e8c37df6cec379c84a7d9"; + sha256 = "0m0n85jab14rfssyjf9sf05rq1rdzs6kqwb467953f26bvcnckkh"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/btcpp_ros2_samples/"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ behaviortree-ros2 btcpp-ros2-interfaces std-msgs std-srvs ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "Examples related to behaviortree_ros2"; + license = with lib.licenses; [ mit ]; + }; +} diff --git a/nix/cartesian-compliance-controller.nix b/nix/cartesian-compliance-controller.nix new file mode 100644 index 0000000..5223d8b --- /dev/null +++ b/nix/cartesian-compliance-controller.nix @@ -0,0 +1,25 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, ament-lint-common, cartesian-controller-base, cartesian-force-controller, cartesian-motion-controller, controller-interface, hardware-interface, pluginlib, rclcpp }: +buildRosPackage rec { + pname = "ros-jazzy-cartesian-compliance-controller"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "cartesian_controllers"; + rev = "9ade57d3ef7f1bf6d514551e710110b014b4a664"; + sha256 = "0sgh7r30ga5lkx5kbdb6ms5arc4rhpbwky6k85xrgpjy1gs5nx1v"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/cartesian_compliance_controller/"; + buildInputs = [ ament-cmake ]; + checkInputs = [ ament-lint-common ]; + propagatedBuildInputs = [ cartesian-controller-base cartesian-force-controller cartesian-motion-controller controller-interface hardware-interface pluginlib rclcpp ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "Control your robot through Cartesian target poses and target wrenches"; + license = with lib.licenses; [ bsd3 ]; + }; +} diff --git a/nix/cartesian-controller-base.nix b/nix/cartesian-controller-base.nix new file mode 100644 index 0000000..ba90730 --- /dev/null +++ b/nix/cartesian-controller-base.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, controller-interface, kdl-parser, pluginlib, rclcpp, realtime-tools, ros-environment, trajectory-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-cartesian-controller-base"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "cartesian_controllers"; + rev = "9ade57d3ef7f1bf6d514551e710110b014b4a664"; + sha256 = "0sgh7r30ga5lkx5kbdb6ms5arc4rhpbwky6k85xrgpjy1gs5nx1v"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/cartesian_controller_base/"; + buildInputs = [ ament-cmake ros-environment ]; + propagatedBuildInputs = [ controller-interface kdl-parser pluginlib rclcpp realtime-tools trajectory-msgs ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "The cartesian_controller_base package"; + license = with lib.licenses; [ bsd3 ]; + }; +} diff --git a/nix/cartesian-controller-handles.nix b/nix/cartesian-controller-handles.nix new file mode 100644 index 0000000..54002bb --- /dev/null +++ b/nix/cartesian-controller-handles.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, cartesian-controller-base, controller-interface, geometry-msgs, interactive-markers, kdl-parser, pluginlib, rclcpp, urdf }: +buildRosPackage rec { + pname = "ros-jazzy-cartesian-controller-handles"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "cartesian_controllers"; + rev = "9ade57d3ef7f1bf6d514551e710110b014b4a664"; + sha256 = "0sgh7r30ga5lkx5kbdb6ms5arc4rhpbwky6k85xrgpjy1gs5nx1v"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/cartesian_controller_handles/"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ cartesian-controller-base controller-interface geometry-msgs interactive-markers kdl-parser pluginlib rclcpp urdf ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "The cartesian_controller_handles package"; + license = with lib.licenses; [ bsd3 ]; + }; +} diff --git a/nix/cartesian-controller-utilities.nix b/nix/cartesian-controller-utilities.nix new file mode 100644 index 0000000..2211793 --- /dev/null +++ b/nix/cartesian-controller-utilities.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, geometry-msgs, launch, launch-ros, rclcpp, sensor-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-cartesian-controller-utilities"; + version = "0.1.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "cartesian_controllers"; + rev = "9ade57d3ef7f1bf6d514551e710110b014b4a664"; + sha256 = "0sgh7r30ga5lkx5kbdb6ms5arc4rhpbwky6k85xrgpjy1gs5nx1v"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/cartesian_controller_utilities/"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ geometry-msgs launch launch-ros rclcpp sensor-msgs ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "Make the spacemouse a teach device for contact-based teleoperation"; + license = with lib.licenses; [ bsd3 ]; + }; +} diff --git a/nix/cartesian-force-controller.nix b/nix/cartesian-force-controller.nix new file mode 100644 index 0000000..6c68e6e --- /dev/null +++ b/nix/cartesian-force-controller.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, cartesian-controller-base, controller-interface, rclcpp }: +buildRosPackage rec { + pname = "ros-jazzy-cartesian-force-controller"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "cartesian_controllers"; + rev = "9ade57d3ef7f1bf6d514551e710110b014b4a664"; + sha256 = "0sgh7r30ga5lkx5kbdb6ms5arc4rhpbwky6k85xrgpjy1gs5nx1v"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/cartesian_force_controller/"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ cartesian-controller-base controller-interface rclcpp ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "The cartesian_force_controller package"; + license = with lib.licenses; [ bsd3 ]; + }; +} diff --git a/nix/cartesian-motion-controller.nix b/nix/cartesian-motion-controller.nix new file mode 100644 index 0000000..ce41e6c --- /dev/null +++ b/nix/cartesian-motion-controller.nix @@ -0,0 +1,22 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, cartesian-controller-base, controller-interface, rclcpp }: +buildRosPackage rec { + pname = "ros-jazzy-cartesian-motion-controller"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "cartesian_controllers"; + rev = "9ade57d3ef7f1bf6d514551e710110b014b4a664"; + sha256 = "0sgh7r30ga5lkx5kbdb6ms5arc4rhpbwky6k85xrgpjy1gs5nx1v"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/cartesian_motion_controller/"; + propagatedBuildInputs = [ cartesian-controller-base controller-interface rclcpp ]; + + meta = { + description = "The cartesian_motion_controller package"; + license = with lib.licenses; [ bsd3 ]; + }; +} diff --git a/nix/cartesian-twist-controller.nix b/nix/cartesian-twist-controller.nix new file mode 100644 index 0000000..b79550c --- /dev/null +++ b/nix/cartesian-twist-controller.nix @@ -0,0 +1,22 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, cartesian-controller-base, controller-interface, rclcpp }: +buildRosPackage rec { + pname = "ros-jazzy-cartesian-twist-controller"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "cartesian_controllers"; + rev = "9ade57d3ef7f1bf6d514551e710110b014b4a664"; + sha256 = "0sgh7r30ga5lkx5kbdb6ms5arc4rhpbwky6k85xrgpjy1gs5nx1v"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/cartesian_twist_controller/"; + propagatedBuildInputs = [ cartesian-controller-base controller-interface rclcpp ]; + + meta = { + description = "The cartesian_twist_controller package"; + license = with lib.licenses; [ bsd3 ]; + }; +} diff --git a/nix/default.nix b/nix/default.nix new file mode 100644 index 0000000..00a2377 --- /dev/null +++ b/nix/default.nix @@ -0,0 +1,18 @@ +{ + nix-ros-overlay ? builtins.fetchTarball "https://github.com/lopsided98/nix-ros-overlay/archive/master.tar.gz", +}: +let + applyDistroOverlay = + rosOverlay: rosPackages: + rosPackages + // builtins.mapAttrs ( + rosDistro: rosPkgs: if rosPkgs ? overrideScope then rosPkgs.overrideScope rosOverlay else rosPkgs + ) rosPackages; + rosDistroOverlays = final: prev: { + # Apply the overlay to multiple ROS distributions + rosPackages = applyDistroOverlay (import ./overlay.nix) prev.rosPackages; + }; +in +import nix-ros-overlay { + overlays = [ rosDistroOverlays ]; +} diff --git a/nix/env-manager-interfaces.nix b/nix/env-manager-interfaces.nix new file mode 100644 index 0000000..bdd110d --- /dev/null +++ b/nix/env-manager-interfaces.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-cmake, ament-lint-auto, ament-lint-common, builtin-interfaces, lifecycle-msgs, rosidl-default-generators, rosidl-default-runtime }: +buildRosPackage rec { + pname = "ros-jazzy-env-manager-interfaces"; + version = "0.0.0"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/env_manager/env_manager_interfaces/"; + buildInputs = [ ament-cmake rosidl-default-generators ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ builtin-interfaces lifecycle-msgs rosidl-default-runtime ]; + nativeBuildInputs = [ ament-cmake rosidl-default-generators ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/env-manager.nix b/nix/env-manager.nix new file mode 100644 index 0000000..1d94318 --- /dev/null +++ b/nix/env-manager.nix @@ -0,0 +1,21 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-copyright, ament-flake8, ament-pep257, python3Packages }: +buildRosPackage rec { + pname = "ros-jazzy-env-manager"; + version = "0.0.0"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_python"; + sourceRoot = "${src.name}/env_manager/env_manager/"; + checkInputs = [ ament-copyright ament-flake8 ament-pep257 python3Packages.pytest ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/ffw-bringup.nix b/nix/ffw-bringup.nix new file mode 100644 index 0000000..6693d24 --- /dev/null +++ b/nix/ffw-bringup.nix @@ -0,0 +1,21 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub }: +buildRosPackage rec { + pname = "ros-jazzy-ffw-bringup"; + version = "1.0.5"; + + src = fetchFromGitHub { + owner = "ROBOTIS-GIT"; + repo = "ai_worker"; + rev = "e53bb7266841d2cc99e1566ff3922f023a079b3b"; + sha256 = "0q02igrwfc4n7g51h3250lapkvmpaapxd35b1k5mzdxfmlz4rqcl"; + }; + + buildType = "ament_python"; + sourceRoot = "${src.name}/ffw_bringup/"; + + meta = { + description = "ROS 2 launch scripts for starting the FFW"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/ffw-description.nix b/nix/ffw-description.nix new file mode 100644 index 0000000..7b29316 --- /dev/null +++ b/nix/ffw-description.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, realsense2-description, urdf, xacro }: +buildRosPackage rec { + pname = "ros-jazzy-ffw-description"; + version = "1.0.5"; + + src = fetchFromGitHub { + owner = "ROBOTIS-GIT"; + repo = "ai_worker"; + rev = "e53bb7266841d2cc99e1566ff3922f023a079b3b"; + sha256 = "0q02igrwfc4n7g51h3250lapkvmpaapxd35b1k5mzdxfmlz4rqcl"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/ffw_description/"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ realsense2-description urdf xacro ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "3D models of the FFW for simulation and visualization"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/ffw-joint-trajectory-command-broadcaster.nix b/nix/ffw-joint-trajectory-command-broadcaster.nix new file mode 100644 index 0000000..5ddf151 --- /dev/null +++ b/nix/ffw-joint-trajectory-command-broadcaster.nix @@ -0,0 +1,25 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, ament-cmake-gmock, backward-ros, builtin-interfaces, control-msgs, controller-interface, controller-manager, generate-parameter-library, hardware-interface, hardware-interface-testing, pluginlib, rclcpp, rclcpp-lifecycle, rcutils, realtime-tools, ros2-control-test-assets, sensor-msgs, trajectory-msgs, urdf }: +buildRosPackage rec { + pname = "ros-jazzy-ffw-joint-trajectory-command-broadcaster"; + version = "1.0.5"; + + src = fetchFromGitHub { + owner = "ROBOTIS-GIT"; + repo = "ai_worker"; + rev = "e53bb7266841d2cc99e1566ff3922f023a079b3b"; + sha256 = "0q02igrwfc4n7g51h3250lapkvmpaapxd35b1k5mzdxfmlz4rqcl"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/ffw_joint_trajectory_command_broadcaster/"; + buildInputs = [ ament-cmake ]; + checkInputs = [ ament-cmake-gmock controller-manager hardware-interface hardware-interface-testing rclcpp ros2-control-test-assets ]; + propagatedBuildInputs = [ backward-ros builtin-interfaces control-msgs controller-interface generate-parameter-library pluginlib rclcpp-lifecycle rcutils realtime-tools sensor-msgs trajectory-msgs urdf ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "Joint Trajectory Command Broadcaster ROS 2 package."; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/ffw-joystick-controller.nix b/nix/ffw-joystick-controller.nix new file mode 100644 index 0000000..1c37586 --- /dev/null +++ b/nix/ffw-joystick-controller.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, controller-interface, hardware-interface, pluginlib, rclcpp, rclcpp-lifecycle, std-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-ffw-joystick-controller"; + version = "1.0.5"; + + src = fetchFromGitHub { + owner = "ROBOTIS-GIT"; + repo = "ai_worker"; + rev = "e53bb7266841d2cc99e1566ff3922f023a079b3b"; + sha256 = "0q02igrwfc4n7g51h3250lapkvmpaapxd35b1k5mzdxfmlz4rqcl"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/ffw_joystick_controller/"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ controller-interface hardware-interface pluginlib rclcpp rclcpp-lifecycle std-msgs ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "ROS 2 controller for reading joystick values"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/ffw-moveit-config.nix b/nix/ffw-moveit-config.nix new file mode 100644 index 0000000..634385a --- /dev/null +++ b/nix/ffw-moveit-config.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, controller-manager, joint-state-publisher, joint-state-publisher-gui, moveit-configs-utils, moveit-kinematics, moveit-planners, moveit-ros-move-group, moveit-ros-visualization, moveit-setup-assistant, moveit-simple-controller-manager, robot-state-publisher, rviz-common, rviz-default-plugins, rviz2, tf2-ros, xacro }: +buildRosPackage rec { + pname = "ros-jazzy-ffw-moveit-config"; + version = "1.0.5"; + + src = fetchFromGitHub { + owner = "ROBOTIS-GIT"; + repo = "ai_worker"; + rev = "e53bb7266841d2cc99e1566ff3922f023a079b3b"; + sha256 = "0q02igrwfc4n7g51h3250lapkvmpaapxd35b1k5mzdxfmlz4rqcl"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/ffw_moveit_config/"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ controller-manager joint-state-publisher joint-state-publisher-gui moveit-configs-utils moveit-kinematics moveit-planners moveit-ros-move-group moveit-ros-visualization moveit-setup-assistant moveit-simple-controller-manager robot-state-publisher rviz-common rviz-default-plugins rviz2 tf2-ros xacro ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "An automatically generated package with all the configuration and launch files for using the ffw with the MoveIt Motion Planning Framework"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/ffw-spring-actuator-controller.nix b/nix/ffw-spring-actuator-controller.nix new file mode 100644 index 0000000..f753f39 --- /dev/null +++ b/nix/ffw-spring-actuator-controller.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, angles, backward-ros, control-msgs, control-toolbox, controller-interface, generate-parameter-library, hardware-interface, pluginlib, rclcpp, rclcpp-lifecycle, realtime-tools, rsl, tl-expected, urdf }: +buildRosPackage rec { + pname = "ros-jazzy-ffw-spring-actuator-controller"; + version = "1.0.5"; + + src = fetchFromGitHub { + owner = "ROBOTIS-GIT"; + repo = "ai_worker"; + rev = "e53bb7266841d2cc99e1566ff3922f023a079b3b"; + sha256 = "0q02igrwfc4n7g51h3250lapkvmpaapxd35b1k5mzdxfmlz4rqcl"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/ffw_spring_actuator_controller/"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ angles backward-ros control-msgs control-toolbox controller-interface generate-parameter-library hardware-interface pluginlib rclcpp rclcpp-lifecycle realtime-tools rsl tl-expected urdf ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "Spring Actuator Controller ROS 2 package."; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/ffw-teleop.nix b/nix/ffw-teleop.nix new file mode 100644 index 0000000..17bdef0 --- /dev/null +++ b/nix/ffw-teleop.nix @@ -0,0 +1,22 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, python3Packages, rclpy }: +buildRosPackage rec { + pname = "ros-jazzy-ffw-teleop"; + version = "1.0.5"; + + src = fetchFromGitHub { + owner = "ROBOTIS-GIT"; + repo = "ai_worker"; + rev = "e53bb7266841d2cc99e1566ff3922f023a079b3b"; + sha256 = "0q02igrwfc4n7g51h3250lapkvmpaapxd35b1k5mzdxfmlz4rqcl"; + }; + + buildType = "ament_python"; + sourceRoot = "${src.name}/ffw_teleop/"; + propagatedBuildInputs = [ python3Packages.tkinter rclpy ]; + + meta = { + description = "FFW teleop ROS 2 package."; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/ffw.nix b/nix/ffw.nix new file mode 100644 index 0000000..2f7c38a --- /dev/null +++ b/nix/ffw.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, ffw-bringup, ffw-description, ffw-joint-trajectory-command-broadcaster, ffw-joystick-controller, ffw-moveit-config, ffw-spring-actuator-controller, ffw-teleop }: +buildRosPackage rec { + pname = "ros-jazzy-ffw"; + version = "1.0.5"; + + src = fetchFromGitHub { + owner = "ROBOTIS-GIT"; + repo = "ai_worker"; + rev = "e53bb7266841d2cc99e1566ff3922f023a079b3b"; + sha256 = "0q02igrwfc4n7g51h3250lapkvmpaapxd35b1k5mzdxfmlz4rqcl"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/ffw/"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ ffw-bringup ffw-description ffw-joint-trajectory-command-broadcaster ffw-joystick-controller ffw-moveit-config ffw-spring-actuator-controller ffw-teleop ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "ROS 2 meta package for FFW"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/gym-gz.nix b/nix/gym-gz.nix new file mode 100644 index 0000000..09e8fea --- /dev/null +++ b/nix/gym-gz.nix @@ -0,0 +1,20 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-copyright, ament-flake8, ament-pep257, python3Packages }: +buildRosPackage rec { + pname = "ros-jazzy-gym-gz"; + version = "1.5.0"; + + src = fetchgit { + url = "rad://z33HXHSaU12N1tEgJCWJpB58w4KR"; + rev = "48a8a56d5f2441627cabdf0f85b3adab3eea33af"; + sha256 = "0hs3rmszdizbkxpvvkihrki61l4whnhsf1a6dwjw9ahgh98yc0qf"; + }; + + buildType = "ament_python"; + checkInputs = [ ament-copyright ament-flake8 ament-pep257 python3Packages.pytest ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ "TODO-License-declaration" ]; + }; +} diff --git a/nix/overlay.nix b/nix/overlay.nix new file mode 100644 index 0000000..1f45492 --- /dev/null +++ b/nix/overlay.nix @@ -0,0 +1,54 @@ +final: prev: +{ + behaviortree-ros2 = final.callPackage ./behaviortree-ros2.nix {}; + btcpp-ros2-interfaces = final.callPackage ./btcpp-ros2-interfaces.nix {}; + btcpp-ros2-samples = final.callPackage ./btcpp-ros2-samples.nix {}; + cartesian-compliance-controller = final.callPackage ./cartesian-compliance-controller.nix {}; + cartesian-controller-base = final.callPackage ./cartesian-controller-base.nix {}; + cartesian-controller-handles = final.callPackage ./cartesian-controller-handles.nix {}; + cartesian-controller-utilities = final.callPackage ./cartesian-controller-utilities.nix {}; + cartesian-force-controller = final.callPackage ./cartesian-force-controller.nix {}; + cartesian-motion-controller = final.callPackage ./cartesian-motion-controller.nix {}; + cartesian-twist-controller = final.callPackage ./cartesian-twist-controller.nix {}; + dynamixel-sdk = prev.dynamixel-sdk.overrideAttrs ({ propagatedBuildInputs = [ prev.python3Packages.pyserial ]; }); + env-manager = final.callPackage ./env-manager.nix {}; + env-manager-interfaces = final.callPackage ./env-manager-interfaces.nix {}; + ffw = final.callPackage ./ffw.nix {}; + ffw-bringup = final.callPackage ./ffw-bringup.nix {}; + ffw-description = final.callPackage ./ffw-description.nix {}; + ffw-joint-trajectory-command-broadcaster = final.callPackage ./ffw-joint-trajectory-command-broadcaster.nix {}; + ffw-joystick-controller = (final.callPackage ./ffw-joystick-controller.nix {}).overrideAttrs ({ + propagatedBuildInputs ? [],... + }: + { + propagatedBuildInputs = propagatedBuildInputs ++ [ prev.generate-parameter-library ]; + }); + ffw-moveit-config = final.callPackage ./ffw-moveit-config.nix {}; + ffw-spring-actuator-controller = (final.callPackage ./ffw-spring-actuator-controller.nix {}).overrideAttrs ({ + propagatedBuildInputs ? [],... + }: + { + propagatedBuildInputs = propagatedBuildInputs ++ [ prev.kdl-parser ]; + }); + ffw-teleop = final.callPackage ./ffw-teleop.nix {}; + gym-gz = final.callPackage ./gym-gz.nix {}; + rbs-arm = final.callPackage ./rbs-arm.nix {}; + rbs-bringup = final.callPackage ./rbs-bringup.nix {}; + rbs-bt-executor = final.callPackage ./rbs-bt-executor.nix {}; + rbs-gym = final.callPackage ./rbs-gym.nix {}; + rbs-perception = final.callPackage ./rbs-perception.nix {}; + rbs-runtime = final.callPackage ./rbs-runtime.nix {}; + rbs-skill-interfaces = final.callPackage ./rbs-skill-interfaces.nix {}; + rbs-skill-servers = final.callPackage ./rbs-skill-servers.nix {}; + rbs-task-planner = final.callPackage ./rbs-task-planner.nix {}; + rbs-tests = final.callPackage ./rbs-tests.nix {}; + rbs-utils = final.callPackage ./rbs-utils.nix {}; + rbs-utils-interfaces = final.callPackage ./rbs-utils-interfaces.nix {}; + rbss-aruco-pe = final.callPackage ./rbss-aruco-pe.nix {}; + rbss-movetopose = final.callPackage ./rbss-movetopose.nix {}; + rbss-objectdetection = final.callPackage ./rbss-objectdetection.nix {}; + rbss-poseestimation = final.callPackage ./rbss-poseestimation.nix {}; + robonomics = final.callPackage ./robonomics.nix {}; + robot-builder = final.callPackage ./robot-builder.nix {}; + scenario = final.callPackage ./scenario.nix {}; +} diff --git a/nix/rbs-arm.nix b/nix/rbs-arm.nix new file mode 100644 index 0000000..dd9a037 --- /dev/null +++ b/nix/rbs-arm.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, ament-lint-auto, ament-lint-common, joint-trajectory-controller, ros-gz, ros2-control, ros2-controllers }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-arm"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "rbs-arm"; + rev = "c7c02247fdb4a65cd9bc0a6e6b01e429c3523558"; + sha256 = "0ja9y52g3g172pcr9jr7ww68yh4qcj65j679hdv39cca53h4ljzx"; + }; + + buildType = "ament_cmake"; + buildInputs = [ ament-cmake ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ joint-trajectory-controller ros-gz ros2-control ros2-controllers ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/rbs-bringup.nix b/nix/rbs-bringup.nix new file mode 100644 index 0000000..8b1abc6 --- /dev/null +++ b/nix/rbs-bringup.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-cmake, ament-lint-auto, ament-lint-common, nav2-common, rbs-bt-executor, rbs-perception, rbs-skill-interfaces, rbs-skill-servers, rbs-utils, rbs-utils-interfaces, robot-builder }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-bringup"; + version = "0.0.0"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/rbs_bringup/"; + buildInputs = [ ament-cmake rbs-bt-executor rbs-perception rbs-skill-interfaces rbs-utils-interfaces ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ nav2-common rbs-skill-servers rbs-utils robot-builder ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ "TODO-License-declaration" ]; + }; +} diff --git a/nix/rbs-bt-executor.nix b/nix/rbs-bt-executor.nix new file mode 100644 index 0000000..b686bbf --- /dev/null +++ b/nix/rbs-bt-executor.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-cmake, ament-cmake-python, ament-lint-auto, ament-lint-common, behaviortree-cpp, behaviortree-ros2, control-msgs, env-manager-interfaces, geometry-msgs, lifecycle-msgs, moveit-core, moveit-ros-planning, moveit-ros-planning-interface, rbs-skill-interfaces, rbs-utils, rclpy }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-bt-executor"; + version = "0.0.0"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/rbs_bt_executor/"; + buildInputs = [ ament-cmake ament-cmake-python ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ behaviortree-cpp behaviortree-ros2 control-msgs env-manager-interfaces geometry-msgs lifecycle-msgs moveit-core moveit-ros-planning moveit-ros-planning-interface rbs-skill-interfaces rbs-utils rclpy ]; + nativeBuildInputs = [ ament-cmake ament-cmake-python ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ "TODO-License-declaration" ]; + }; +} diff --git a/nix/rbs-gym.nix b/nix/rbs-gym.nix new file mode 100644 index 0000000..c1ba026 --- /dev/null +++ b/nix/rbs-gym.nix @@ -0,0 +1,21 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-copyright, ament-flake8, ament-pep257, python3Packages }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-gym"; + version = "0.0.0"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_python"; + sourceRoot = "${src.name}/env_manager/rbs_gym/"; + checkInputs = [ ament-copyright ament-flake8 ament-pep257 python3Packages.pytest ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/rbs-perception.nix b/nix/rbs-perception.nix new file mode 100644 index 0000000..e8c4bde --- /dev/null +++ b/nix/rbs-perception.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-cmake, ament-cmake-python, ament-lint-auto, ament-lint-common, cv-bridge, image-transport, perception-pcl, rbs-skill-interfaces, rclcpp, rclpy, sensor-msgs, std-msgs, tf2-eigen, tf2-ros, visualization-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-perception"; + version = "0.0.0"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/rbs_perception/"; + buildInputs = [ ament-cmake ament-cmake-python ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ cv-bridge image-transport perception-pcl rbs-skill-interfaces rclcpp rclpy sensor-msgs std-msgs tf2-eigen tf2-ros visualization-msgs ]; + nativeBuildInputs = [ ament-cmake ament-cmake-python ]; + + meta = { + description = "An node for robot perception"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/rbs-runtime.nix b/nix/rbs-runtime.nix new file mode 100644 index 0000000..0bf7a52 --- /dev/null +++ b/nix/rbs-runtime.nix @@ -0,0 +1,22 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-copyright, ament-flake8, ament-pep257, env-manager, env-manager-interfaces, python3Packages, robot-builder }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-runtime"; + version = "0.0.0"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_python"; + sourceRoot = "${src.name}/env_manager/rbs_runtime/"; + checkInputs = [ ament-copyright ament-flake8 ament-pep257 python3Packages.pytest ]; + propagatedBuildInputs = [ env-manager env-manager-interfaces robot-builder ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/rbs-skill-interfaces.nix b/nix/rbs-skill-interfaces.nix new file mode 100644 index 0000000..608c77f --- /dev/null +++ b/nix/rbs-skill-interfaces.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-cmake, ament-cmake-gtest, ament-lint-auto, ament-lint-common, geometry-msgs, moveit-msgs, rosidl-default-generators, rosidl-default-runtime, shape-msgs, std-msgs, test-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-skill-interfaces"; + version = "0.0.0"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/rbs_skill_interfaces/"; + buildInputs = [ ament-cmake rosidl-default-generators ]; + checkInputs = [ ament-cmake-gtest ament-lint-auto ament-lint-common test-msgs ]; + propagatedBuildInputs = [ geometry-msgs moveit-msgs rosidl-default-runtime shape-msgs std-msgs ]; + nativeBuildInputs = [ ament-cmake rosidl-default-generators ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/rbs-skill-servers.nix b/nix/rbs-skill-servers.nix new file mode 100644 index 0000000..3120c9f --- /dev/null +++ b/nix/rbs-skill-servers.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, action-msgs, ament-cmake, ament-lint-auto, ament-lint-common, cartesian-compliance-controller, cartesian-controller-base, cartesian-controller-handles, cartesian-controller-utilities, cartesian-force-controller, cartesian-motion-controller, cartesian-twist-controller, controller-manager-msgs, geometric-shapes, geometry-msgs, moveit-core, moveit-msgs, moveit-ros-planning, moveit-ros-planning-interface, rbs-skill-interfaces, rbs-utils, rclcpp, rclcpp-action, rclcpp-components, tf2-eigen, tf2-ros }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-skill-servers"; + version = "0.0.0"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/rbs_skill_servers/"; + buildInputs = [ ament-cmake cartesian-compliance-controller cartesian-controller-base cartesian-controller-handles cartesian-controller-utilities cartesian-force-controller cartesian-motion-controller cartesian-twist-controller controller-manager-msgs ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ action-msgs geometric-shapes geometry-msgs moveit-core moveit-msgs moveit-ros-planning moveit-ros-planning-interface rbs-skill-interfaces rbs-utils rclcpp rclcpp-action rclcpp-components tf2-eigen tf2-ros ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/rbs-task-planner.nix b/nix/rbs-task-planner.nix new file mode 100644 index 0000000..913418e --- /dev/null +++ b/nix/rbs-task-planner.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-cmake, ament-cmake-gtest, ament-index-cpp, ament-lint-auto, ament-lint-common, plansys2-bringup, plansys2-bt-actions, plansys2-domain-expert, plansys2-executor, plansys2-msgs, plansys2-pddl-parser, plansys2-planner, plansys2-problem-expert, plansys2-terminal, popf, test-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-task-planner"; + version = "0.0.1"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/rbs_task_planner/"; + buildInputs = [ ament-cmake ]; + checkInputs = [ ament-cmake-gtest ament-lint-auto ament-lint-common test-msgs ]; + propagatedBuildInputs = [ ament-index-cpp plansys2-bringup plansys2-bt-actions plansys2-domain-expert plansys2-executor plansys2-msgs plansys2-pddl-parser plansys2-planner plansys2-problem-expert plansys2-terminal popf ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "ROS2 task planner for manipulator"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/rbs-tests.nix b/nix/rbs-tests.nix new file mode 100644 index 0000000..2c8026c --- /dev/null +++ b/nix/rbs-tests.nix @@ -0,0 +1,21 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, launch, launch-ros, launch-testing-ament-cmake, rbs-utils }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-tests"; + version = "0.0.1"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "catkin"; + sourceRoot = "${src.name}/rbs_tests/"; + checkInputs = [ launch launch-ros launch-testing-ament-cmake rbs-utils ]; + + meta = { + description = "Integration tests for the Robossembler-ROS2"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/rbs-utils-interfaces.nix b/nix/rbs-utils-interfaces.nix new file mode 100644 index 0000000..a500a5e --- /dev/null +++ b/nix/rbs-utils-interfaces.nix @@ -0,0 +1,23 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-cmake, geometry-msgs, rosidl-default-generators, rosidl-default-runtime }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-utils-interfaces"; + version = "0.0.0"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/rbs_utils/rbs_utils_interfaces/"; + buildInputs = [ ament-cmake rosidl-default-generators ]; + propagatedBuildInputs = [ geometry-msgs rosidl-default-runtime ]; + nativeBuildInputs = [ ament-cmake rosidl-default-generators ]; + + meta = { + description = "Interfaces for read robossembler_db config"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/rbs-utils.nix b/nix/rbs-utils.nix new file mode 100644 index 0000000..fdc3b22 --- /dev/null +++ b/nix/rbs-utils.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-cmake, ament-cmake-python, ament-lint-auto, ament-lint-common, controller-manager-msgs, geometry-msgs, image-transport, nlohmann_json, rbs-utils-interfaces, rclcpp, rclcpp-lifecycle, rclpy, rosbag2-cpp, rosidl-default-generators, rviz-visual-tools, sensor-msgs, std-msgs, tf2-eigen, tf2-ros }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-utils"; + version = "0.0.0"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/rbs_utils/rbs_utils/"; + buildInputs = [ ament-cmake ament-cmake-python ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ controller-manager-msgs geometry-msgs image-transport nlohmann_json rbs-utils-interfaces rclcpp rclcpp-lifecycle rclpy rosbag2-cpp rosidl-default-generators rviz-visual-tools sensor-msgs std-msgs tf2-eigen tf2-ros ]; + nativeBuildInputs = [ ament-cmake ament-cmake-python ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/rbss-aruco-pe.nix b/nix/rbss-aruco-pe.nix new file mode 100644 index 0000000..a680f4c --- /dev/null +++ b/nix/rbss-aruco-pe.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-cmake, ament-cmake-python, ament-lint-auto, ament-lint-common, cv-bridge, geometry-msgs, lifecycle-msgs, rbs-skill-interfaces, rclpy, sensor-msgs, std-msgs, tf-transformations }: +buildRosPackage rec { + pname = "ros-jazzy-rbss-aruco-pe"; + version = "0.0.1"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/rbss_aruco_pe/"; + buildInputs = [ ament-cmake ament-cmake-python ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ cv-bridge geometry-msgs lifecycle-msgs rbs-skill-interfaces rclpy sensor-msgs std-msgs tf-transformations ]; + nativeBuildInputs = [ ament-cmake ament-cmake-python ]; + + meta = { + description = "Aruco Marker Tracking and Pose Estimation wrapper for ROS2, using RGB cameras"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/rbss-movetopose.nix b/nix/rbss-movetopose.nix new file mode 100644 index 0000000..8e928a3 --- /dev/null +++ b/nix/rbss-movetopose.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-cmake, ament-cmake-python, ament-lint-auto, ament-lint-common, geometry-msgs, rbs-skill-interfaces, rclcpp, rclpy, std-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-rbss-movetopose"; + version = "0.0.1"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/rbss_movetopose/"; + buildInputs = [ ament-cmake ament-cmake-python ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ geometry-msgs rbs-skill-interfaces rclcpp rclpy std-msgs ]; + nativeBuildInputs = [ ament-cmake ament-cmake-python ]; + + meta = { + description = "The Move to pose skill"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/rbss-objectdetection.nix b/nix/rbss-objectdetection.nix new file mode 100644 index 0000000..5897926 --- /dev/null +++ b/nix/rbss-objectdetection.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-cmake, ament-cmake-python, ament-lint-auto, ament-lint-common, cv-bridge, image-transport, lifecycle-msgs, rbs-skill-interfaces, rclpy, sensor-msgs, std-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-rbss-objectdetection"; + version = "0.0.1"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/rbss_objectdetection/"; + buildInputs = [ ament-cmake ament-cmake-python ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ cv-bridge image-transport lifecycle-msgs rbs-skill-interfaces rclpy sensor-msgs std-msgs ]; + nativeBuildInputs = [ ament-cmake ament-cmake-python ]; + + meta = { + description = "The Object Detection skill"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/rbss-poseestimation.nix b/nix/rbss-poseestimation.nix new file mode 100644 index 0000000..b075268 --- /dev/null +++ b/nix/rbss-poseestimation.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-cmake, ament-cmake-python, ament-lint-auto, ament-lint-common, cv-bridge, geometry-msgs, image-transport, rclpy, sensor-msgs, std-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-rbss-poseestimation"; + version = "0.0.1"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/rbss_poseestimation/"; + buildInputs = [ ament-cmake ament-cmake-python ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ cv-bridge geometry-msgs image-transport rclpy sensor-msgs std-msgs ]; + nativeBuildInputs = [ ament-cmake ament-cmake-python ]; + + meta = { + description = "The Pose Estimation skill"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/robonomics.nix b/nix/robonomics.nix new file mode 100644 index 0000000..229adf5 --- /dev/null +++ b/nix/robonomics.nix @@ -0,0 +1,22 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-copyright, ament-flake8, ament-pep257, python3Packages, rclpy }: +buildRosPackage rec { + pname = "ros-jazzy-robonomics"; + version = "0.1.0"; + + src = fetchgit { + url = "git@gitlab.com:robossembler/robossembler-ros2.git"; + rev = "a87d5779895cadca4ef5a121d03156e85387b199"; + sha256 = "0zxx8pd8y5f8qi6phwr88zx502i31clsx3wk78rsjs9zp4q3zlmm"; + }; + + buildType = "ament_python"; + sourceRoot = "${src.name}/robonomics/"; + checkInputs = [ ament-copyright ament-flake8 ament-pep257 python3Packages.pytest ]; + propagatedBuildInputs = [ rclpy ]; + + meta = { + description = "Package for Robossember-Robonomics interoperability"; + license = with lib.licenses; [ "Apache-license-2.0" ]; + }; +} diff --git a/nix/robot-builder.nix b/nix/robot-builder.nix new file mode 100644 index 0000000..faddde5 --- /dev/null +++ b/nix/robot-builder.nix @@ -0,0 +1,21 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchFromGitHub, ament-copyright, ament-flake8, ament-pep257, python3Packages }: +buildRosPackage rec { + pname = "ros-jazzy-robot-builder"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "robot-builder"; + rev = "abad78494eea370d825c0e60805639f5f3b8af02"; + sha256 = "1sl3gghi3fgp946ddj5dhzx7p500yaqgklnyc15nchym0xh144lf"; + }; + + buildType = "ament_python"; + checkInputs = [ ament-copyright ament-flake8 ament-pep257 python3Packages.pytest ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/nix/scenario.nix b/nix/scenario.nix new file mode 100644 index 0000000..9f27e3d --- /dev/null +++ b/nix/scenario.nix @@ -0,0 +1,22 @@ +# Automatically generated by: ros2nix --output-as-nix-pkg-name --fetch --output-dir nix --distro jazzy +{ lib, buildRosPackage, fetchgit, ament-cmake, gz-math-vendor, gz-msgs-vendor, gz-sim-vendor, gz-transport-vendor }: +buildRosPackage rec { + pname = "ros-jazzy-scenario"; + version = "1.5.0"; + + src = fetchgit { + url = "rad://z3RBwHLb4j66Q12dwkK1RGQj3ufhi"; + rev = "cb8227d85455d32fd6df4f931b4ce031c3063007"; + sha256 = "05110l7l533crkk632mvsz5li5ws3pvh8s2l5j11qsi6qfsx291d"; + }; + + buildType = "ament_cmake"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ gz-math-vendor gz-msgs-vendor gz-sim-vendor gz-transport-vendor ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/overlay.nix b/overlay.nix new file mode 100644 index 0000000..92ae919 --- /dev/null +++ b/overlay.nix @@ -0,0 +1,36 @@ +self: super: { + + # generated from this repo + env-manager = super.callPackage ./env_manager/env_manager/package.nix {}; + env-manager-interfaces = super.callPackage ./env_manager/env_manager_interfaces/package.nix {}; + rbs-bringup = super.callPackage ./rbs_bringup/package.nix {}; + rbs-bt-executor = super.callPackage ./rbs_bt_executor/package.nix {}; + rbs-gym = super.callPackage ./env_manager/rbs_gym/package.nix {}; + rbs-perception = super.callPackage ./rbs_perception/package.nix {}; + rbs-runtime = super.callPackage ./env_manager/rbs_runtime/package.nix {}; + rbs-skill-interfaces = super.callPackage ./rbs_skill_interfaces/package.nix {}; + rbs-skill-servers = super.callPackage ./rbs_skill_servers/package.nix {}; + rbs-task-planner = super.callPackage ./rbs_task_planner/package.nix {}; + rbs-utils = super.callPackage ./rbs_utils/rbs_utils/package.nix {}; + rbs-utils-interfaces = super.callPackage ./rbs_utils/rbs_utils_interfaces/package.nix {}; + rbss-movetopose = super.callPackage ./rbss_movetopose/package.nix {}; + rbss-objectdetection = super.callPackage ./rbss_objectdetection/package.nix {}; + rbss-poseestimation = super.callPackage ./rbss_poseestimation/package.nix {}; + robonomics = super.callPackage ./robonomics/package.nix {}; + + # generated from external repos + behaviortree-ros2 = super.callPackage ./repos/nix/behaviortree-ros2.nix {}; + btcpp-ros2-interfaces = super.callPackage ./repos/nix/btcpp-ros2-interfaces.nix {}; + btcpp-ros2-samples = super.callPackage ./repos/nix/btcpp-ros2-samples.nix {}; + cartesian-compliance-controller = super.callPackage ./repos/nix/cartesian-compliance-controller.nix {}; + cartesian-controller-base = super.callPackage ./repos/nix/cartesian-controller-base.nix {}; + cartesian-controller-handles = super.callPackage ./repos/nix/cartesian-controller-handles.nix {}; + cartesian-controller-utilities = super.callPackage ./repos/nix/cartesian-controller-utilities.nix {}; + cartesian-force-controller = super.callPackage ./repos/nix/cartesian-force-controller.nix {}; + cartesian-motion-controller = super.callPackage ./repos/nix/cartesian-motion-controller.nix {}; + cartesian-twist-controller = super.callPackage ./repos/nix/cartesian-twist-controller.nix {}; + gym-gz = super.callPackage ./repos/nix/gym-gz.nix {}; + rbs-arm = super.callPackage ./repos/nix/rbs-arm.nix {}; + robot-builder = super.callPackage ./repos/nix/robot-builder.nix {}; + scenario = super.callPackage ./repos/nix/scenario.nix {}; +} diff --git a/rbs_bringup/launch/control.launch.py b/rbs_bringup/launch/control.launch.py index a2d6df6..162f64a 100644 --- a/rbs_bringup/launch/control.launch.py +++ b/rbs_bringup/launch/control.launch.py @@ -35,6 +35,8 @@ def launch_setup(context, *args, **kwargs): and control_space == "task", "cartesian_force_controller": control_strategy == "effort" and control_space == "task", + "cartesian_twist_controller": control_strategy == "velocity" + and control_space == "task", "joint_effort_controller": control_strategy == "effort" and control_space == "joint", "force_torque_sensor_broadcaster": control_strategy == "effort" @@ -74,10 +76,9 @@ def generate_launch_description(): default_value="true", description="Whether to activate the gripper_controller.", ), - DeclareLaunchArgument( "interactive_control", - default_value="true", + default_value="false", description="Wheter to run the motion_control_handle controller", ), ] diff --git a/rbs_bringup/launch/rbs_bringup.launch.py b/rbs_bringup/launch/rbs_bringup.launch.py index 50db4b6..f67895d 100644 --- a/rbs_bringup/launch/rbs_bringup.launch.py +++ b/rbs_bringup/launch/rbs_bringup.launch.py @@ -20,7 +20,7 @@ def launch_setup(context, *args, **kwargs): ] ), launch_arguments={ - "with_gripper": "true", + "with_gripper": "false", "robot_type": "rbs_arm", "description_package": "rbs_arm", "description_file": "rbs_arm_modular.xacro", @@ -32,10 +32,10 @@ def launch_setup(context, *args, **kwargs): "use_controllers": "true", "scene_config_file": "", "base_link_name": "base_link", - "ee_link_name": "gripper_grasp_point", + "ee_link_name": "tool0", "control_space": "task", "control_strategy": "position", - "interactive": "false", + "interactive": "true", "use_rbs_utils": "true", "assembly_config_name": "board_pick_and_place" }.items(), diff --git a/rbs_bringup/launch/rbs_robot.launch.py b/rbs_bringup/launch/rbs_robot.launch.py index a36b396..7216429 100644 --- a/rbs_bringup/launch/rbs_robot.launch.py +++ b/rbs_bringup/launch/rbs_robot.launch.py @@ -33,6 +33,7 @@ def launch_setup(context, *args, **kwargs): use_skills = LaunchConfiguration("use_skills") namespace = LaunchConfiguration("namespace") multi_robot = LaunchConfiguration("multi_robot") + interactive_control = LaunchConfiguration("interactive_control").perform(context) robot_name = robot_name.perform(context) namespace = namespace.perform(context) robot_type = robot_type.perform(context) @@ -59,11 +60,11 @@ def launch_setup(context, *args, **kwargs): "robot_description": robot_description_content.perform(context) } - robot_description_kinematics_filepath = os.path.join( - get_package_share_directory(moveit_config_package.perform(context)), - "config", - "kinematics.yaml", - ) + # robot_description_kinematics_filepath = os.path.join( + # get_package_share_directory(moveit_config_package.perform(context)), + # "moveit", + # "kinematics.yaml", + # ) # robot_description_kinematics = { # "robot_description_kinematics": robot_description_kinematics @@ -93,6 +94,7 @@ def launch_setup(context, *args, **kwargs): launch_arguments={ "control_space": control_space, "control_strategy": control_strategy, + "interactive_control": interactive_control, "has_gripper": with_gripper_condition, "namespace": namespace, }.items(), @@ -118,8 +120,8 @@ def launch_setup(context, *args, **kwargs): "tf_prefix": robot_name, "with_gripper": with_gripper_condition, "robot_description": robot_description_content, - "robot_description_semantic": robot_description_semantic_content, - "robot_description_kinematics": robot_description_kinematics_filepath, + # "robot_description_semantic": robot_description_semantic_content, + # "robot_description_kinematics": robot_description_kinematics_filepath, "namespace": namespace, }.items(), condition=IfCondition(use_moveit), @@ -140,7 +142,7 @@ def launch_setup(context, *args, **kwargs): launch_arguments={ "robot_description": robot_description_content, "robot_description_semantic": robot_description_semantic_content, - "robot_description_kinematics": robot_description_kinematics_filepath, + # "robot_description_kinematics": robot_description_kinematics_filepath, "use_sim_time": use_sim_time, "with_gripper_condition": with_gripper_condition, "namespace": namespace, @@ -199,6 +201,7 @@ def generate_launch_description(): "ur10", "ur10e", "ur16e", + "aubo-i5", ], default_value="rbs_arm", ) @@ -399,10 +402,17 @@ def generate_launch_description(): declared_arguments.append( DeclareLaunchArgument( "use_rbs_utils", - default_value="true", + default_value="false", description="Whwther use utils", ) ) + declared_arguments.append( + DeclareLaunchArgument( + "interactive_control", + default_value="false", + description="Use motion_control_handle to interact with InteractiveMarker in Rviz2", + ) + ) return LaunchDescription( declared_arguments + [OpaqueFunction(function=launch_setup)] diff --git a/rbs_bringup/package.nix b/rbs_bringup/package.nix new file mode 100644 index 0000000..2a04599 --- /dev/null +++ b/rbs_bringup/package.nix @@ -0,0 +1,40 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license +{ + lib, + buildRosPackage, + ament-cmake, + ament-lint-auto, + ament-lint-common, + env-manager, + env-manager-interfaces, + rbs-bt-executor, + rbs-gym, + rbs-perception, + rbs-runtime, + rbs-skill-interfaces, + rbs-skill-servers, + rbs-utils, + rbs-utils-interfaces, + rbss-movetopose, + rbss-objectdetection, + rbss-poseestimation, + robot-builder, +}: +buildRosPackage rec { + pname = "ros-jazzy-rbs-bringup"; + version = "0.0.0"; + + src = ./.; + + buildType = "ament_cmake"; + buildInputs = [ament-cmake env-manager env-manager-interfaces rbs-bt-executor rbs-gym rbs-perception rbs-runtime rbs-skill-interfaces rbs-skill-servers rbs-utils rbs-utils-interfaces rbss-movetopose rbss-objectdetection rbss-poseestimation robot-builder]; + checkInputs = [ament-lint-auto ament-lint-common]; + nativeBuildInputs = [ament-cmake]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [asl20]; + }; +} diff --git a/rbs_bringup/package.xml b/rbs_bringup/package.xml index a256110..73f25bd 100644 --- a/rbs_bringup/package.xml +++ b/rbs_bringup/package.xml @@ -10,6 +10,14 @@ ament_cmake nav2_common + rbs_utils + robot_builder + rbs_skill_servers + + rbs_bt_executor + rbs_perception + rbs_skill_interfaces + rbs_utils_interfaces ament_lint_auto ament_lint_common diff --git a/rbs_bt_executor/CMakeLists.txt b/rbs_bt_executor/CMakeLists.txt index 0bb5ed0..9705cc7 100644 --- a/rbs_bt_executor/CMakeLists.txt +++ b/rbs_bt_executor/CMakeLists.txt @@ -83,8 +83,8 @@ list(APPEND plugin_libs rbs_skill_move_joint_state) # add_library(rbs_pose_estimation SHARED src/PoseEstimation.cpp) # list(APPEND plugin_libs rbs_pose_estimation) -add_library(rbs_object_detection SHARED src/ObjectDetection.cpp) -list(APPEND plugin_libs rbs_object_detection) +# add_library(rbs_object_detection SHARED src/ObjectDetection.cpp) +# list(APPEND plugin_libs rbs_object_detection) # add_library(rbs_env_manager_starter SHARED src/EnvManager.cpp) # list(APPEND plugin_libs rbs_env_manager_starter) @@ -95,9 +95,16 @@ list(APPEND plugin_libs rbs_skill_move_topose_array_bt_action_client) add_library(rbs_get_workspace SHARED src/GetWorkspace.cpp) list(APPEND plugin_libs rbs_get_workspace) -add_library(rbs_act SHARED src/rbsBTAction.cpp) +add_library(rbs_move_to_pose_orientation_constraint_bt_action_client + SHARED src/MoveToPoseOrientationConstraint.cpp) +list(APPEND plugin_libs rbs_move_to_pose_orientation_constraint_bt_action_client) + +add_library(rbs_act SHARED src/rbssAction.cpp) list(APPEND plugin_libs rbs_act) +add_library(rbs_cond SHARED src/rbssCondition.cpp) +list(APPEND plugin_libs rbs_cond) + add_executable(rbs_bt_executor src/TreeRunner.cpp) ament_target_dependencies(rbs_bt_executor ${dependencies}) diff --git a/rbs_bt_executor/config/skills.json b/rbs_bt_executor/config/skills.json new file mode 100644 index 0000000..c7e33ab --- /dev/null +++ b/rbs_bt_executor/config/skills.json @@ -0,0 +1,241 @@ +{ + "skills": [ + { + "sid": "c4aaffa2-7bef-4f0e-981f-ab7cd627b93d", + "SkillPackage": { "name": "Robossembler", "version": "1", "format": "1.0" }, + "Module": { "node_name": "lc_yolo", "name": "ObjectDetection", "description": "Object detection skill with YOLOv8" }, + "BTAction": [ + { + "name": "odConfigure", + "type": "run", + "param": [ + { + "type": "topic", + "dependency": { + "type": "topic", + "topicType": "sensor_msgs/msg/Image", + "topicOut": "/rgbd_camera/image" + }, + "isFilled": true + }, + { + "type": "formBuilder", + "dependency": { + "result": "{\"process\":\\${:OBJECT:{\"type\":\"WEIGHTS\"},\"object_name\":\\${object_name:string:}}", + "context": "", + "form": [ + "{\"name\":\"\",\"type\":\"OBJECT\",\"defaultValue\":{\"type\":\"WEIGHTS\"},\"totalValue\":\"{\\\"type\\\":\\\"WEIGHTS\\\",\\\"selectProcess\\\":{\\\"value\\\":{\\\"_id\\\":\\\"67af21227ccd2ccaf17318fb\\\",\\\"script\\\":\\\"python3 $PYTHON_EDUCATION\\\",\\\"type\\\":\\\"WEIGHTS\\\",\\\"instanceName\\\":\\\"wod_shildik_sh\\\",\\\"name\\\":\\\"pWod\\\",\\\"isEnd\\\":true,\\\"createDate\\\":\\\"1737729633581\\\",\\\"card\\\":\\\"pose_estimate\\\",\\\"path\\\":\\\"/home/shalenikol/webservice/server/build/public/process/pWod\\\",\\\"instancePath\\\":\\\"/home/shalenikol/webservice/server/build/public/process/pWod/wod_shildik_sh\\\",\\\"project\\\":{\\\"_id\\\":\\\"678a2a17b960c6f1e7228577\\\",\\\"description\\\":\\\"exhibition_01\\\",\\\"rootDir\\\":\\\"/home/shalenikol/webservice/server/build/public/a54164c1-c4f8-44ff-adef-0d4f377fba65\\\",\\\"isActive\\\":true,\\\"__v\\\":0},\\\"__v\\\":0,\\\"lastProcessExecCommand\\\":\\\"python3 $PYTHON_EDUCATION --path /home/shalenikol/webservice/server/build/public/process/pWod/wod_shildik_sh --form /home/shalenikol/webservice/server/build/public/process/pWod/wod_shildik_sh/form.json\\\",\\\"processStatus\\\":\\\"endOk\\\",\\\"lastProcessLogs\\\":\\\"Downloading https://github.com/ultralytics/assets/releases/download/v8.1.0/yolov8n.pt to '/home/shalenikol/webservice/server/build/public/process/pWod/wod_shildik_sh/yolov8n.pt'...\\\\n\\\\n\\\\n 0%| | 0.00/6.23M [00:00:[]}}", + "context": "type ITEM = {\"name\": \\${NAME:string:default},\"value\": \\${VALUE:string:default}};", + "form": [ + "{\"name\":\"ITEM\",\"type\":\"Array\",\"defaultValue\":\"[]\",\"values\":[{\"name\":\"NAME\",\"type\":\"string\",\"defaultValue\":\"default\",\"isOpen\":false,\"id\":\"fa8b442a-101b-448b-b5fd-55ad64f8e578\"},{\"name\":\"VALUE\",\"type\":\"string\",\"defaultValue\":\"default\",\"isOpen\":false,\"id\":\"c59b86d8-a54b-42da-b2bf-5fdfeff7f711\"}],\"totalValue\":[],\"isOpen\":true,\"subType\":\"ITEM\",\"id\":\"8be7af67-5860-4a3f-bdab-09c75a53bff7\"}" + ], + "output": { + "params": [ + { + "name": "is_image_mode", + "value": "True" + }, + { + "name": "threshold", + "value": "0.25" + }, + { + "name": "publishDelay", + "value": "0.33" + } + ] + }, + "type": "formBuilder" + }, + "__v": 0 + }, + { + "_id": "67b33b15f3412f3530fdb337", + "bgColor": "rgba(5, 26, 39, 1)", + "borderColor": "rgba(25, 130, 196, 1)", + "sid": "4006188a-a4b4-4ca3-b0bf-11fad7f81263", + "SkillPackage": { + "name": "Robossembler", + "version": "1", + "format": "1.0" + }, + "Module": { + "node_name": "lc_yolo", + "name": "ObjectDetection", + "description": "Object detection skill with YOLOv8" + }, + "BTAction": [ + { + "name": "odStop", + "type": "stop", + "param": [], + "typeAction": "ACTION" + } + ], + "topicsOut": [ + { + "name": "lc_yolo/object_detection", + "type": "rbs_skill_interfaces/msg/BoundBox" + }, + { + "name": "lc_yolo/detect_image", + "type": "sensor_msgs/msg/Image" + } + ], + "Launch": { + "executable": "od_yolo_lc.py", + "package": "rbss_objectdetection" + }, + "Settings": { + "result": "{\"params\": \\${ITEM:Array:[]}}", + "context": "type ITEM = {\"name\": \\${NAME:string:default},\"value\": \\${VALUE:string:default}};", + "form": [ + "{\"name\":\"ITEM\",\"type\":\"Array\",\"defaultValue\":\"[]\",\"values\":[{\"name\":\"NAME\",\"type\":\"string\",\"defaultValue\":\"default\",\"isOpen\":false,\"id\":\"fa8b442a-101b-448b-b5fd-55ad64f8e578\"},{\"name\":\"VALUE\",\"type\":\"string\",\"defaultValue\":\"default\",\"isOpen\":false,\"id\":\"c59b86d8-a54b-42da-b2bf-5fdfeff7f711\"}],\"totalValue\":[],\"isOpen\":true,\"subType\":\"ITEM\",\"id\":\"8be7af67-5860-4a3f-bdab-09c75a53bff7\"}" + ], + "output": { + "params": [] + }, + "type": "formBuilder" + }, + "__v": 0 + }, + { + "sid": "805dcd18-264c-4c5f-a874-76d98e98f2b7", + "SkillPackage": { "name": "Robossembler", "version": "1", "format": "1.0" }, + "Module": { "node_name": "skill_mtp", "name": "MoveToPose", "description": "Move to Pose skill" }, + "Launch": { "executable": "skill_movetopose.py", "package": "rbss_movetopose" }, + "BTAction": [ + { + "name": "move", + "type": "action", + "param": [ + { + "type": "formBuilder", + "dependency": { + "result": "{\"robot_name\": \\${ROBOT_NAME:string:rbs_arm}, \"pose\": {\"position\": { \"x\": \\${X:number:0.1}, \"y\": \\${Y:number:0.1}, \"z\": \\${Z:number:0.7} }, \"orientation\": { \"x\": \\${X:number:0.1}, \"y\": \\${Y:number:0.1}, \"z\": \\${Z:number:0.7}, \"w\": \\${W:number:1.0} }}}", + "context": "type ITEM = {\"name\": \\${NAME:string:default}};", + "form": [ + "{\"name\":\"ROBOT_NAME\",\"type\":\"string\",\"defaultValue\":\"rbs_arm\",\"isOpen\":false,\"id\":\"7b2611d6-ff4d-4eb9-a210-e5c146722906\"}", + "{\"name\":\"X\",\"type\":\"number\",\"defaultValue\":\"0.1\",\"totalValue\":\"0\",\"isOpen\":false,\"id\":\"5df2228b-fd4a-4937-9386-d6e149eedb89\"}", + "{\"name\":\"Y\",\"type\":\"number\",\"defaultValue\":\"0.1\",\"totalValue\":\"0.2\",\"isOpen\":false,\"id\":\"9161f3c4-5d8f-4f76-9e1f-375bb664c51b\"}", + "{\"name\":\"Z\",\"type\":\"number\",\"defaultValue\":\"0.7\",\"totalValue\":\"0.6\",\"isOpen\":false,\"id\":\"6798619e-6ff5-46d5-9477-90dd7454c123\"}", + "{\"name\":\"X\",\"type\":\"number\",\"defaultValue\":\"0.1\",\"totalValue\":\"0.55\",\"isOpen\":false,\"id\":\"60e3c96a-101c-4fe5-9899-b2dbdf0448c1\"}", + "{\"name\":\"Y\",\"type\":\"number\",\"defaultValue\":\"0.1\",\"totalValue\":\"0.44\",\"isOpen\":false,\"id\":\"31539e2b-f081-4d58-ac4b-044326f87fac\"}", + "{\"name\":\"Z\",\"type\":\"number\",\"defaultValue\":\"0.7\",\"totalValue\":\"0.0\",\"isOpen\":false,\"id\":\"7fa23bfd-5dc5-4397-b559-f45dc7fc5cff\"}", + "{\"name\":\"W\",\"type\":\"number\",\"defaultValue\":\"1.0\",\"isOpen\":false,\"id\":\"a9411bdf-b600-4616-9cd4-4c4d34da72fd\"}" + ], + "output": { + "robot_name": "rbs_arm", + "pose": { + "position": { + "x": 0.104, + "y": -0.28, + "z": 0.1 + }, + "orientation": { + "x": 0, + "y": 1, + "z": 0, + "w": 0 + } + } + }, + "type": "formBuilder" + }, + "isFilled": true + } + ], + "result": [], + "typeAction": "ACTION" + } + ], + "topicsOut": [], + "Settings": { + "result": "{\"params\": \\${ITEM:Array:[]}}", + "context": "type ITEM = {\"name\": \\${NAME:string:default},\"value\": \\${VALUE:string:default}};", + "form": [], + "output": { + "params": [ + { + "name": "server_name", + "value": "mtp_jtc", + "value2": "mtp_moveit", + "value3": "mtp_cart" + }, + { + "name": "duration", + "value": "2.0" + }, + { + "name": "end_effector_velocity", + "value": "1.0" + }, + { + "name": "end_effector_acceleration", + "value": "1.0" + } + ] + }, + "type": "formBuilder" + }, + "__v": 0 + } + ] +} \ No newline at end of file diff --git a/rbs_bt_executor/launch/interface.launch.py b/rbs_bt_executor/launch/interface.launch.py index ba2de13..1e9700f 100644 --- a/rbs_bt_executor/launch/interface.launch.py +++ b/rbs_bt_executor/launch/interface.launch.py @@ -1,9 +1,13 @@ """ Launching interface node with connecting skills ROS 2 launch program for Robossembler + ```bash + ros2 launch rbs_bt_executor bt_path:= mode:=benchmark @shalenikol release 0.1 @shalenikol release 0.2 mode + @shalenikol release 0.3 {"bt_path": bt_path} # included as default path + @shalenikol release 0.4 bt_path : either name of skills config file or path to default skills config file """ import os import json @@ -16,15 +20,12 @@ from launch import LaunchDescription FILE_SKILLS = "skills.json" PARAM_SUFFIX = "_cfg" -def get_skill_list_(path: str) -> list: - f = os.path.join(path, FILE_SKILLS) +def get_skill_list(f: str) -> list: if not os.path.isfile(f): return [] with open(f, "r") as fh: data = json.load(fh) - # str_data = fh.read() - # data = json.loads(str_data) nn_skills = 0 excluding = {} @@ -48,16 +49,17 @@ def launch_setup(context, *args, **kwargs): # Initialize Arguments bt_path = LaunchConfiguration("bt_path") bt_path = bt_path.perform(context) + skills_cfg_file = bt_path if bt_path.endswith(".json") else os.path.join(bt_path, FILE_SKILLS) + mode = LaunchConfiguration("mode") mode = mode.perform(context) - skills = get_skill_list_(bt_path) + skills = get_skill_list(skills_cfg_file) rbs_interface = Node( package="rbs_bt_executor", executable="rbs_interface.py", - parameters = [{"mode": mode},{"use_sim_time": True}] - # parameters = [{"bt_path": bt_path}] # can be included as default path + parameters = [{"bt_path": skills_cfg_file},{"mode": mode},{"use_sim_time": True}] ) nodes_to_start = [rbs_interface] return nodes_to_start + skills diff --git a/rbs_bt_executor/launch/rbs_bt_web.launch.py b/rbs_bt_executor/launch/rbs_bt_web.launch.py index 707d773..acd9598 100644 --- a/rbs_bt_executor/launch/rbs_bt_web.launch.py +++ b/rbs_bt_executor/launch/rbs_bt_web.launch.py @@ -1,25 +1,36 @@ """ rbs_bt_web ROS 2 launch program for Robossembler + ```bash + ros2 launch rbs_bt_executor rbs_bt_web.launch.py bt_path:= @shalenikol release 0.1 @shalenikol release 0.2 BT v.4 @shalenikol release 0.3 bt_path = os.path.dirname(bt_path) + @shalenikol release 0.4 bt_path : either name of BT-file or path to default BT-file """ +import os + from launch import LaunchDescription from launch_ros.actions import Node from launch.actions import DeclareLaunchArgument, OpaqueFunction, RegisterEventHandler from launch.substitutions import LaunchConfiguration from launch.event_handlers import OnExecutionComplete +FILE_BT = "bt.xml" +FILE_SKILLS = "skills.json" + def launch_setup(context, *args, **kwargs): # Initialize Arguments bt_path = LaunchConfiguration("bt_path") bt_path = bt_path.perform(context) if bt_path[-4:] == ".xml": - import os - bt_path = os.path.dirname(bt_path) + bt_file = bt_path + skills_file = os.path.join(os.path.dirname(bt_path), FILE_SKILLS) + else: + bt_file = os.path.join(bt_path, FILE_BT) + skills_file = os.path.join(bt_path, FILE_SKILLS) # rbs_bt = Node( # package = "rbs_bt_executor", @@ -35,14 +46,14 @@ def launch_setup(context, *args, **kwargs): bt_exec = Node( package="rbs_bt_executor", executable="bt_exec", - arguments=[bt_path] + arguments=[bt_file] # prefix=['gdbserver localhost:3000'], ) bt_param = Node( package="rbs_bt_executor", executable="bt_param.py", - parameters=[{"bt_path": bt_path}] + parameters=[{"bt_path": skills_file}] ) return [ RegisterEventHandler( diff --git a/rbs_bt_executor/package.nix b/rbs_bt_executor/package.nix new file mode 100644 index 0000000..fc732a7 --- /dev/null +++ b/rbs_bt_executor/package.nix @@ -0,0 +1,23 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 + +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license + +{ lib, buildRosPackage, ament-cmake, ament-cmake-python, ament-lint-auto, ament-lint-common, behaviortree-cpp, behaviortree-ros2, control-msgs, env-manager-interfaces, geometry-msgs, lifecycle-msgs, moveit-core, moveit-ros-planning, moveit-ros-planning-interface, rbs-skill-interfaces, rbs-utils, rclpy }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-bt-executor"; + version = "0.0.0"; + + src = ./.; + + buildType = "ament_cmake"; + buildInputs = [ ament-cmake ament-cmake-python ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ behaviortree-cpp behaviortree-ros2 control-msgs env-manager-interfaces geometry-msgs lifecycle-msgs moveit-core moveit-ros-planning moveit-ros-planning-interface rbs-skill-interfaces rbs-utils rclpy ]; + nativeBuildInputs = [ ament-cmake ament-cmake-python ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ "TODO-License-declaration" ]; + }; +} diff --git a/rbs_bt_executor/package.xml b/rbs_bt_executor/package.xml index 5f109c6..e70a912 100644 --- a/rbs_bt_executor/package.xml +++ b/rbs_bt_executor/package.xml @@ -10,6 +10,11 @@ ament_cmake ament_cmake_python + moveit_core + moveit_ros_planning + moveit_ros_planning_interface + control_msgs + rclpy rbs_utils rbs_skill_interfaces diff --git a/rbs_bt_executor/scripts/rbs_interface.py b/rbs_bt_executor/scripts/rbs_interface.py index 4836604..9790b2c 100755 --- a/rbs_bt_executor/scripts/rbs_interface.py +++ b/rbs_bt_executor/scripts/rbs_interface.py @@ -7,6 +7,8 @@ @shalenikol release 0.2 BT v.4 @shalenikol release 0.3 synchronize @shalenikol release 0.4 mode:="benchmark" + @shalenikol release 0.5 bt_path # included as default path (in __init__) + @shalenikol release 0.6 """ import os import json @@ -39,17 +41,20 @@ SERVER_NAME = "rbs_interface_a" FILE_SKILLS = "skills.json" PARAM_SUFFIX = "_cfg" KEY_BTPARAM = "BTAction" +KEY_SIDPATH = "@path@" # prefix for filepath class rbsInterface(Node): def __init__(self, node_name): """Construct the node.""" - self.bt_path = "" # path to the current BehaviorTree + # self.bt_path = "" # path to the current BehaviorTree # self._mode = "" # run mode of the interface node + self.file_skills = FILE_SKILLS self.cfg_data = None # config for current action super().__init__(node_name) self.declare_parameter(BT_PARAM, rclpy.Parameter.Type.STRING) self.declare_parameter(MODE_PARAM, rclpy.Parameter.Type.STRING) self._mode = self.get_parameter(MODE_PARAM).get_parameter_value().string_value + self.bt_path = self.get_parameter(BT_PARAM).get_parameter_value().string_value self.cb_group = ReentrantCallbackGroup() # for Condition @@ -60,7 +65,7 @@ class rbsInterface(Node): # self.client = AsyncParameterClient(self.client_node, 'test_parameter_client_target') # only Iron self.add_on_set_parameters_callback(self._on_set_btpath_param) - def get_transfer_path(self): + def get_skillcfg_file(self): if self.bt_path: return self.bt_path return os.path.join(get_package_share_directory("rbs_bt_executor"), "config") @@ -117,9 +122,12 @@ class rbsInterface(Node): assert False, f"Error: sid not valid '{sid}'" def _load_config(self, sid: str): - p = os.path.join(self.get_transfer_path(), FILE_SKILLS) # action+".json") + if sid.startswith(KEY_SIDPATH): + p = sid[len(KEY_SIDPATH):] + else: + p = self.get_skillcfg_file() #os.path.join(self.get_transfer_path(), self.file_skills) # load config - return self._deserialize(p,sid) + return self._deserialize(p, sid) def run_action(self, command_data: dict) -> bool: p_list = command_data["param"] diff --git a/rbs_bt_executor/src/BTExec.cpp b/rbs_bt_executor/src/BTExec.cpp index 5f7aba1..8f95883 100644 --- a/rbs_bt_executor/src/BTExec.cpp +++ b/rbs_bt_executor/src/BTExec.cpp @@ -14,7 +14,7 @@ #define NODE_NAME "rbs_interface" #define SERVICE_NAME "rbs_interface_s" #define SERVER_NAME "rbs_interface_a" -#define FILE_BT "bt.xml" +// #define FILE_BT "bt.xml" template std::string to_string(const T &t) { @@ -161,7 +161,7 @@ private: int main(int argc, char** argv) { // filename Behavior Tree - std::string bt = std::string(argv[1]) + "/" FILE_BT; + std::string bt = std::string(argv[1]); // + "/" FILE_BT std::ifstream fh(bt, std::ios::in); // reading xml std::string xml{std::istreambuf_iterator(fh), std::istreambuf_iterator()}; diff --git a/rbs_bt_executor/src/MoveToJointStates.cpp b/rbs_bt_executor/src/MoveToJointStates.cpp index 893ab4f..5901f8b 100644 --- a/rbs_bt_executor/src/MoveToJointStates.cpp +++ b/rbs_bt_executor/src/MoveToJointStates.cpp @@ -18,17 +18,22 @@ public: static PortsList providedPorts() { return providedBasicPorts({InputPort("robot_name"), - InputPort>("JointState")}); + InputPort>("joint_state"), + InputPort("duration")}); } bool setGoal(RosActionNode::Goal &goal) override { + RCLCPP_INFO(this->logger(), "[%s] Starting send goal [%s]", name().c_str(), + this->action_name_.c_str()); getInput("robot_name", goal.robot_name); - getInput("JointState", goal.joint_values); + getInput("joint_state", goal.joint_values); + getInput("duration", goal.duration); return true; } NodeStatus onResultReceived(const WrappedResult &wr) override { - + RCLCPP_INFO(this->logger(), "[%s] Starting get response %s with status %b", + name().c_str(), this->action_name_.c_str(), wr.result->success); if (!wr.result->success) { return NodeStatus::FAILURE; } diff --git a/rbs_bt_executor/src/MoveToPose.cpp b/rbs_bt_executor/src/MoveToPose.cpp index e3c9259..c09e25e 100644 --- a/rbs_bt_executor/src/MoveToPose.cpp +++ b/rbs_bt_executor/src/MoveToPose.cpp @@ -1,8 +1,10 @@ #include "behaviortree_ros2/bt_action_node.hpp" #include "rbs_skill_interfaces/action/moveit_send_pose.hpp" +#include #include #include #include +#include using namespace BT; using MoveitSendPoseAction = rbs_skill_interfaces::action::MoveitSendPose; @@ -17,29 +19,63 @@ public: } static BT::PortsList providedPorts() { - return providedBasicPorts( - {BT::InputPort("robot_name"), - BT::InputPort>("pose"), - BT::InputPort("duration")}); + return providedBasicPorts({ + BT::InputPort("robot_name"), + BT::InputPort>("pose"), + BT::InputPort("duration"), + BT::InputPort("try_plan_untill_success", false, "Replan if failure to plan"), + BT::InputPort("allowed_planning_time", 5.0, "Maximal time to plan"), + }); } bool setGoal(RosActionNode::Goal &goal) override { - RCLCPP_INFO(this->logger(), "Starting send request"); - getInput("robot_name", goal.robot_name); - getInput("pose", m_target_pose); - getInput("duration", goal.duration); + RCLCPP_INFO(this->logger(), "[%s] Starting send goal [%s]", name().c_str(), + this->action_name_.c_str()); + if (!getInput("robot_name", goal.robot_name)) { + RCLCPP_FATAL(this->logger(), + "[%s] Could not get robot_name from input port", + name().c_str()); + return false; + } + if (!getInput("pose", m_target_pose)) { + RCLCPP_FATAL(this->logger(), + "[%s] Could not get target_pose from input port", + name().c_str()); + return false; + } + if (!getInput("duration", goal.duration)) { + RCLCPP_FATAL(this->logger(), + "[%s] Could not get duration from input port", + name().c_str()); + return false; + } + + RCLCPP_INFO_STREAM( + this->logger(), + "[" << name().c_str() << "]" << "Got target_pose: \nPosition [ " + << m_target_pose->position.x << ", " << m_target_pose->position.y + << ", " << m_target_pose->position.z << " ];\n" + << "Orientation: [ " << m_target_pose->orientation.x << ", " + << m_target_pose->orientation.y << ", " + << m_target_pose->orientation.z << ", " + << m_target_pose->orientation.w << "] "); + goal.target_pose = *m_target_pose; + getInput("try_plan_untill_success", goal.try_plan_untill_success); + getInput("allowed_planning_time", goal.allowed_planning_time); return true; } NodeStatus onResultReceived(const WrappedResult &wr) override { - RCLCPP_INFO(this->logger(), "Starting get response"); + RCLCPP_INFO(this->logger(), "[%s] Starting get response %s with status %b", + name().c_str(), this->action_name_.c_str(), wr.result->success); if (!wr.result->success) { return NodeStatus::FAILURE; } return NodeStatus::SUCCESS; } + private: std::shared_ptr m_target_pose; }; diff --git a/rbs_bt_executor/src/MoveToPoseOrientationConstraint.cpp b/rbs_bt_executor/src/MoveToPoseOrientationConstraint.cpp new file mode 100644 index 0000000..f8c65d3 --- /dev/null +++ b/rbs_bt_executor/src/MoveToPoseOrientationConstraint.cpp @@ -0,0 +1,62 @@ +#include "behaviortree_ros2/bt_action_node.hpp" +#include "rbs_skill_interfaces/action/moveit_send_pose_with_constraints.hpp" +#include +#include +#include +#include + +using namespace BT; +using MoveitSendPoseWithConstraintAction = + rbs_skill_interfaces::action::MoveitSendPoseWithConstraints; + +class MoveToPoseOrientationConstraint + : public RosActionNode { +public: + MoveToPoseOrientationConstraint(const std::string &name, + const NodeConfig &conf, + const RosNodeParams ¶ms) + : RosActionNode(name, conf, params) { + + RCLCPP_INFO(this->logger(), "Starting MoveToPose"); + } + + static BT::PortsList providedPorts() { + return providedBasicPorts( + {BT::InputPort("robot_name"), + BT::InputPort>("pose"), + BT::InputPort("x_tol"), BT::InputPort("y_tol"), + BT::InputPort("z_tol"), BT::InputPort("weight"), + BT::InputPort("duration")}); + } + + bool setGoal(RosActionNode::Goal &goal) override { + RCLCPP_INFO(this->logger(), "[%s] Starting send goal [%s]", name().c_str(), + this->action_name_.c_str()); + + getInput("x_tol", goal.orientation_constraint.absolute_x_axis_tolerance); + getInput("y_tol", goal.orientation_constraint.absolute_y_axis_tolerance); + getInput("z_tol", goal.orientation_constraint.absolute_z_axis_tolerance); + getInput("weight", goal.orientation_constraint.weight); + getInput("robot_name", goal.robot_name); + getInput("pose", m_target_pose); + getInput("duration", goal.duration); + goal.target_pose = *m_target_pose; + return true; + } + + NodeStatus onResultReceived(const WrappedResult &wr) override { + + RCLCPP_INFO(this->logger(), "[%s] Starting get response %s with status %b", + name().c_str(), this->action_name_.c_str(), wr.result->success); + if (!wr.result->success) { + return NodeStatus::FAILURE; + } + return NodeStatus::SUCCESS; + } + +private: + std::shared_ptr m_target_pose; +}; + +CreateRosNodePlugin(MoveToPoseOrientationConstraint, + "MtpOrientationConstraint"); diff --git a/rbs_bt_executor/src/ObjectDetection.cpp b/rbs_bt_executor/src/ObjectDetection.cpp deleted file mode 100644 index b010271..0000000 --- a/rbs_bt_executor/src/ObjectDetection.cpp +++ /dev/null @@ -1,90 +0,0 @@ -#include "behaviortree_ros2/bt_service_node.hpp" -#include "lifecycle_msgs/msg/transition.hpp" -#include "lifecycle_msgs/srv/change_state.hpp" -#include "rcl_interfaces/msg/parameter.hpp" -#include "rcl_interfaces/srv/set_parameters.hpp" -#include -#include -#include -#include -#include - -using namespace BT; -using namespace std::chrono_literals; -using ObjDetectionSrv = lifecycle_msgs::srv::ChangeState; - -class ObjectDetection : public RosServiceNode { -public: - ObjectDetection(const std::string &name, const NodeConfig &conf, - const RosNodeParams ¶ms) - : RosServiceNode(name, conf, params) { - m_params_client = std::make_shared( - node_.lock(), "/object_detection"); - while (!m_params_client->wait_for_service(1s)) { - if (!rclcpp::ok()) { - RCLCPP_ERROR(logger(), - "Interrupted while waiting for the service. Exiting."); - break; - } - } - getInput("SettingPath", m_settings_path); - } - - static PortsList providedPorts() { - return providedBasicPorts({ - InputPort("ReqKind"), - InputPort("SettingPath"), - }); - } - - bool setRequest(Request::SharedPtr &request) override { - getInput("ReqKind", m_req_type); - auto transition = transition_event(m_req_type); - request->set__transition(transition); - return true; - } - - NodeStatus onResponseReceived(const Response::SharedPtr &response) override { - if (!response->success) { - return NodeStatus::FAILURE; - } - return NodeStatus::SUCCESS; - } - -private: - uint8_t transition_id_{}; - std::string m_settings_path{}; - // std::string _model_path{}; - std::string m_req_type{}; - std::shared_ptr m_params_client; - std::vector _params; - rcl_interfaces::msg::Parameter m_param; - - lifecycle_msgs::msg::Transition - transition_event(const std::string &req_type) { - lifecycle_msgs::msg::Transition translation{}; - if (req_type == "configure") { - set_str_param(); - transition_id_ = lifecycle_msgs::msg::Transition::TRANSITION_CONFIGURE; - } else if (req_type == "activate") { - transition_id_ = lifecycle_msgs::msg::Transition::TRANSITION_ACTIVATE; - } else if (req_type == "deactivate") { - transition_id_ = lifecycle_msgs::msg::Transition::TRANSITION_DEACTIVATE; - } else if (req_type == "cleanup") { - transition_id_ = lifecycle_msgs::msg::Transition::TRANSITION_CLEANUP; - } - translation.set__id(transition_id_); - return translation; - } - - void set_str_param() { - RCLCPP_INFO_STREAM(logger(), - "Set string parameter: <" + m_settings_path + ">"); - - std::vector t_parameters{ - rclcpp::Parameter("setting_path", m_settings_path)}; - m_params_client->set_parameters(t_parameters); - } -}; - -CreateRosNodePlugin(ObjectDetection, "ObjectDetection"); diff --git a/rbs_bt_executor/src/PoseEstimation.cpp b/rbs_bt_executor/src/PoseEstimation.cpp deleted file mode 100644 index df63330..0000000 --- a/rbs_bt_executor/src/PoseEstimation.cpp +++ /dev/null @@ -1,126 +0,0 @@ -#include "behaviortree_ros2/bt_service_node.hpp" - -#include "rcl_interfaces/msg/parameter.hpp" -#include "rcl_interfaces/srv/set_parameters.hpp" - -#include "ament_index_cpp/get_package_share_directory.hpp" -#include "lifecycle_msgs/msg/transition.hpp" -#include "lifecycle_msgs/srv/change_state.hpp" -#include -#include - -using namespace BT; -using namespace std::chrono_literals; -using PoseEstimationSrv = lifecycle_msgs::srv::ChangeState; - -class PoseEstimation : public RosServiceNode { -public: - PoseEstimation(const std::string &name, const NodeConfig &conf, - const RosNodeParams ¶ms) - : RosServiceNode(name, conf, params) { - RCLCPP_INFO_STREAM(logger(), "Start node."); - - m_params_client = std::make_shared( - node_.lock(), "/pose_estimation"); - - while (!m_params_client->wait_for_service(1s)) { - if (!rclcpp::ok()) { - RCLCPP_ERROR(logger(), - "Interrupted while waiting for the service. Exiting."); - break; - } - RCLCPP_WARN(logger(), "service not available, waiting again..."); - } - - // Get model name paramter from BT ports - getInput("ObjectName", m_model_name); - } - - bool setRequest(Request::SharedPtr &request) override { - getInput("ReqKind", m_req_type); - request->set__transition(transition_event(m_req_type)); - return true; - } - - NodeStatus onResponseReceived(const Response::SharedPtr &response) override { - if (!response->success) { - return NodeStatus::FAILURE; - } - return NodeStatus::SUCCESS; - } - - static PortsList providedPorts() { - return providedBasicPorts({ - InputPort("ReqKind"), - InputPort("ObjectName"), - InputPort("ObjectPath"), - }); - } - -private: - uint8_t m_transition_id{}; - std::string m_model_name{}; - std::string m_model_type{}; - std::string m_req_type{}; - std::shared_ptr m_params_client; - std::vector m_params; - rcl_interfaces::msg::Parameter m_param; - - lifecycle_msgs::msg::Transition - transition_event(const std::string &req_type) { - lifecycle_msgs::msg::Transition translation{}; - // ParamSetter param_setter(m_params_client); - if (req_type == "configure") { - set_mesh_param(); - // auto str_mesh_param = - // std::make_shared("model_name", - // m_model_name); param_setter.setStrategy(str_mesh_param); - // param_setter.setParam() - - m_transition_id = lifecycle_msgs::msg::Transition::TRANSITION_CONFIGURE; - } else if (req_type == "calibrate") { - set_str_param(); - m_transition_id = lifecycle_msgs::msg::Transition::TRANSITION_CONFIGURE; - } else if (req_type == "activate") { - m_transition_id = lifecycle_msgs::msg::Transition::TRANSITION_ACTIVATE; - } else if (req_type == "deactivate") { - m_transition_id = lifecycle_msgs::msg::Transition::TRANSITION_DEACTIVATE; - } else if (req_type == "cleanup") { - m_transition_id = lifecycle_msgs::msg::Transition::TRANSITION_CLEANUP; - } - // calibrate - translation.set__id(m_transition_id); - return translation; - } - - inline std::string build_model_path(const std::string &model_name, - const std::string &package_path) { - return package_path + "/config/" + model_name + ".ply"; - } - - inline std::string build_model_path(const std::string &model_path) { - return model_path; - } - - void set_str_param() { - RCLCPP_INFO_STREAM(logger(), - "Set string parameter: <" + m_model_name + ">"); - - std::vector params{ - rclcpp::Parameter("model_name", m_model_name)}; - m_params_client->set_parameters(params); - } - - void set_mesh_param() { - auto t_package_name = - ament_index_cpp::get_package_share_directory("rbs_perception"); - m_model_type = build_model_path(m_model_name, t_package_name); - RCLCPP_INFO_STREAM(logger(), m_model_type); - - std::vector params{ - rclcpp::Parameter("mesh_path", m_model_name)}; - m_params_client->set_parameters(params); - } -}; - -CreateRosNodePlugin(PoseEstimation, "PoseEstimation"); diff --git a/rbs_bt_executor/src/rbsBTAction.cpp b/rbs_bt_executor/src/rbsBTAction.cpp deleted file mode 100644 index 0675785..0000000 --- a/rbs_bt_executor/src/rbsBTAction.cpp +++ /dev/null @@ -1,64 +0,0 @@ -// #include "behavior_tree/BtService.hpp" -#include "behaviortree_ros2/bt_service_node.hpp" -#include "rbs_skill_interfaces/srv/rbs_bt.hpp" -#include -#include -#include - -#define STR_ACTION "do" -#define STR_SID "sid" -#define STR_COMMAND "command" -#define NODE_NAME "rbs_interface" - -using namespace BT; -using namespace std::chrono_literals; -using RbsBtActionSrv = rbs_skill_interfaces::srv::RbsBt; - -class RbsBtAction : public RosServiceNode { -public: - RbsBtAction(const std::string &name, const NodeConfig& conf, const RosNodeParams& params) - : RosServiceNode(name, conf, params) { - - m_action_name = getInput(STR_ACTION).value(); - RCLCPP_INFO_STREAM(logger(), "Start node RbsBtAction: " + m_action_name); - - m_params_client = std::make_shared(node_.lock(), NODE_NAME); - - while (!m_params_client->wait_for_service(1s)) { - if (!rclcpp::ok()) { - RCLCPP_ERROR(logger(), "Interrupted while waiting for the service. Exiting."); - break; - } - RCLCPP_WARN(logger(), NODE_NAME " service not available, waiting again..."); - } - } - - bool setRequest(Request::SharedPtr &request) override { - request->action = m_action_name; - getInput(STR_SID, request->sid); - getInput(STR_COMMAND, request->command); - return true; - } - - NodeStatus onResponseReceived(const Response::SharedPtr &response) override { - if (!response->ok) { - return NodeStatus::FAILURE; - } - return NodeStatus::SUCCESS; - } - - static PortsList providedPorts() { - return providedBasicPorts({ - InputPort(STR_SID), - InputPort(STR_ACTION), - InputPort(STR_COMMAND) - }); - } - -private: - std::string m_action_name{}; - std::shared_ptr m_params_client; -}; - -// !!! теперь устаревшая версия !!! -CreateRosNodePlugin(RbsBtAction, "RbsBtAction") diff --git a/rbs_bt_executor/src/rbssAction.cpp b/rbs_bt_executor/src/rbssAction.cpp new file mode 100644 index 0000000..6f1ce6f --- /dev/null +++ b/rbs_bt_executor/src/rbssAction.cpp @@ -0,0 +1,84 @@ +// #include "behavior_tree/BtService.hpp" +// #include "behaviortree_ros2/bt_service_node.hpp" +#include "behaviortree_ros2/bt_action_node.hpp" +// #include "rbs_skill_interfaces/srv/rbs_bt.hpp" +#include "rbs_skill_interfaces/action/rbs_bt.hpp" +#include +#include +#include + +#define STR_ACTION "do" +#define STR_SID "sid" +#define STR_COMMAND "command" +#define NODE_NAME "rbs_interface" + +template std::string to_string(const T &t) +{ + std::stringstream ss; + ss << t; + return ss.str(); +} + +using namespace BT; +using namespace std::chrono_literals; +using RbssActionSrv = rbs_skill_interfaces::action::RbsBt; + +class RbssAction : public RosActionNode { +public: + RbssAction(const std::string &name, const NodeConfig &conf, const RosNodeParams ¶ms) + : RosActionNode(name, conf, params) { + + m_action = getInput(STR_ACTION).value(); + m_command = getInput(STR_COMMAND).value(); + RCLCPP_INFO_STREAM(logger(), "Start node RbssAction: " + m_action + "/" + m_command); + + m_client = std::make_shared(node_.lock(), NODE_NAME); + + while (!m_client->wait_for_service(1s)) { + if (!rclcpp::ok()) { + RCLCPP_ERROR(logger(), "Interrupted while waiting for the service. Exiting."); + break; + } + RCLCPP_WARN(logger(), NODE_NAME " service not available, waiting again..."); + } + + } + + static BT::PortsList providedPorts() { + return providedBasicPorts({ + BT::InputPort(STR_SID), + BT::InputPort(STR_ACTION), + BT::InputPort(STR_COMMAND) + }); + } + + bool setGoal(RosActionNode::Goal& goal) override { + getInput(STR_ACTION, goal.action); + getInput(STR_COMMAND, goal.command); + getInput(STR_SID, goal.sid); + m_action = goal.action; + m_command = goal.command; + + m_i++; + RCLCPP_INFO_STREAM(logger(), "setGoal: " + to_string(m_i) + ") " + goal.action + "/" + goal.command + " goal.sid = " + to_string(goal.sid)); + return true; + } + + NodeStatus onResultReceived(const WrappedResult& wr) override { + m_i++; + RCLCPP_INFO_STREAM(logger(), "onResultReceived: " + to_string(m_i) + ") " + m_action + "/" + m_command + " wr.result->ok - " + to_string(wr.result->ok)); + + if (!wr.result->ok) { + return NodeStatus::FAILURE; + } + return NodeStatus::SUCCESS; + } + +private: + int m_i{0}; + std::string m_action{}; + std::string m_command{}; + std::shared_ptr m_client; +}; + +CreateRosNodePlugin(RbssAction, "RbssAction") diff --git a/rbs_bt_executor/src/rbssCondition.cpp b/rbs_bt_executor/src/rbssCondition.cpp new file mode 100644 index 0000000..95cc33b --- /dev/null +++ b/rbs_bt_executor/src/rbssCondition.cpp @@ -0,0 +1,81 @@ +// #include "behavior_tree/BtService.hpp" +#include "behaviortree_ros2/bt_service_node.hpp" +// #include "behaviortree_ros2/bt_action_node.hpp" +#include "rbs_skill_interfaces/srv/rbs_bt.hpp" +// #include "rbs_skill_interfaces/action/rbs_bt.hpp" +#include +#include +#include + +#define STR_ACTION "do" +#define STR_SID "sid" +#define STR_COMMAND "command" +#define NODE_NAME "rbs_interface" + +template std::string to_string(const T &t) +{ + std::stringstream ss; + ss << t; + return ss.str(); +} + +using namespace BT; +using namespace std::chrono_literals; +using RbssConditionSrv = rbs_skill_interfaces::srv::RbsBt; + +class RbssCondition : public RosServiceNode { + public: + RbssCondition(const std::string &name, const NodeConfig& conf, const RosNodeParams& params) + : RosServiceNode(name, conf, params) { + + m_action_name = getInput(STR_ACTION).value(); + m_command = getInput(STR_COMMAND).value(); + RCLCPP_INFO_STREAM(logger(), "Start node RbssCondition: " + m_action_name + "/" + m_command); + + m_params_client = std::make_shared(node_.lock(), NODE_NAME); + + while (!m_params_client->wait_for_service(1s)) { + if (!rclcpp::ok()) { + RCLCPP_ERROR(logger(), "Interrupted while waiting for the service. Exiting."); + break; + } + RCLCPP_WARN(logger(), NODE_NAME " service not available, waiting again..."); + } + } + + bool setRequest(Request::SharedPtr &request) override { + request->action = m_action_name; + request->command = m_command; + getInput(STR_SID, request->sid); + + m_i++; + RCLCPP_INFO_STREAM(logger(), "setRequest: " + to_string(m_i) + ") " + m_action_name + "/" + m_command + " request->sid = " + to_string(request->sid)); + return true; + } + + NodeStatus onResponseReceived(const Response::SharedPtr &response) override { + m_i++; + RCLCPP_INFO_STREAM(logger(), "onResponseReceived: " + to_string(m_i) + ") " + m_action_name + "/" + m_command + " response->ok - " + to_string(response->ok)); + + if (!response->ok) { + return NodeStatus::FAILURE; + } + return NodeStatus::SUCCESS; + } + + static PortsList providedPorts() { + return providedBasicPorts({ + InputPort(STR_SID), + InputPort(STR_ACTION), + InputPort(STR_COMMAND) + }); + } + + private: + int m_i{0}; + std::string m_action_name{}; + std::string m_command{}; + std::shared_ptr m_params_client; +}; + +CreateRosNodePlugin(RbssCondition, "RbssCondition") diff --git a/rbs_perception/package.nix b/rbs_perception/package.nix new file mode 100644 index 0000000..154eaf4 --- /dev/null +++ b/rbs_perception/package.nix @@ -0,0 +1,23 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 + +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license + +{ lib, buildRosPackage, ament-cmake, ament-cmake-python, ament-lint-auto, ament-lint-common, cv-bridge, image-transport, perception-pcl, rbs-skill-interfaces, rclcpp, rclpy, sensor-msgs, std-msgs, tf2-eigen, tf2-ros, visualization-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-perception"; + version = "0.0.0"; + + src = ./.; + + buildType = "ament_cmake"; + buildInputs = [ ament-cmake ament-cmake-python ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ cv-bridge image-transport perception-pcl rbs-skill-interfaces rclcpp rclpy sensor-msgs std-msgs tf2-eigen tf2-ros visualization-msgs ]; + nativeBuildInputs = [ ament-cmake ament-cmake-python ]; + + meta = { + description = "An node for robot perception"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/rbs_simulation/launch/simulation.launch.py b/rbs_simulation/launch/simulation.launch.py deleted file mode 100644 index 7932e03..0000000 --- a/rbs_simulation/launch/simulation.launch.py +++ /dev/null @@ -1,127 +0,0 @@ -import os -from launch_ros.actions import Node -from launch import LaunchDescription -from launch.actions import DeclareLaunchArgument, IncludeLaunchDescription -from launch_ros.substitutions import FindPackageShare -from launch.substitutions import Command, FindExecutable, LaunchConfiguration, PathJoinSubstitution -from launch.conditions import IfCondition, UnlessCondition -from launch.launch_description_sources import PythonLaunchDescriptionSource -from ament_index_python.packages import get_package_share_directory - - -def generate_launch_description(): - declared_arguments = [] - declared_arguments.append( - DeclareLaunchArgument("sim_gazebo", - default_value="false", - description="Gazebo Simulation") - ) - declared_arguments.append( - DeclareLaunchArgument("rbs_robot_type", - description="Type of robot by name", - choices=["rbs_arm" ,"ur3", "ur3e", "ur5", "ur5e", "ur10", "ur10e", "ur16e"], - default_value="rbs_arm",) - ) - declared_arguments.append( - DeclareLaunchArgument("gazebo_gui", - default_value="true", - description="Launch gazebo_gui?") - ) - declared_arguments.append( - DeclareLaunchArgument("debugger", - default_value="false", - description="launch Gazebo with debugger?") - ) - declared_arguments.append( - DeclareLaunchArgument("vision_bridge", - default_value="false", - description="Create bridge for rgbd cameras") - ) - - sim_gazebo = LaunchConfiguration("sim_gazebo") - rbs_robot_type = LaunchConfiguration("rbs_robot_type") - gazebo_gui = LaunchConfiguration("gazebo_gui") - debugger = LaunchConfiguration("debugger") - vision_bridge = LaunchConfiguration("vision_bridge") - - # FIXME: To args when we'll have different files - # TODO: Use global variable to find world file in robossembler_db - world_config_file = PathJoinSubstitution( - [FindPackageShare("rbs_simulation"), "worlds", "asm2.sdf"] - ) - # Gazebo nodes - - gazebo_server = IncludeLaunchDescription( - PythonLaunchDescriptionSource( - [os.path.join(get_package_share_directory('ros_gz_sim'), - 'launch', 'gz_sim.launch.py')]), - launch_arguments={ - 'gz_args': [' -r ',world_config_file, " -s"], - "debugger": debugger, - }.items(), - condition=UnlessCondition(gazebo_gui)) - - gazebo = IncludeLaunchDescription( - PythonLaunchDescriptionSource( - [os.path.join(get_package_share_directory('ros_gz_sim'), - 'launch', 'gz_sim.launch.py')]), - launch_arguments={ - 'gz_args': [' -r ',world_config_file], - "debugger": debugger, - }.items(), - condition=IfCondition(gazebo_gui)) - - # Spawn robot - gazebo_spawn_robot = Node( - package='ros_gz_sim', - executable='create', - arguments=[ - '-name', rbs_robot_type, - '-x', '0.0', - '-z', '0.0', - '-y', '0.0', - '-topic', '/robot_description'], - output='screen', - condition=IfCondition(sim_gazebo)) - - # Bridge - rgbd_bridge_out = Node( - package='ros_gz_bridge', - executable='parameter_bridge', - arguments=[ - '/outer_rgbd_camera/image@sensor_msgs/msg/Image@gz.msgs.Image', - '/outer_rgbd_camera/camera_info@sensor_msgs/msg/CameraInfo@gz.msgs.CameraInfo', - '/outer_rgbd_camera/depth_image@sensor_msgs/msg/Image@gz.msgs.Image', - '/outer_rgbd_camera/points@sensor_msgs/msg/PointCloud2@gz.msgs.PointCloudPacked' - ], - output='screen', - condition=IfCondition(sim_gazebo) and IfCondition(vision_bridge)) - - rgbd_bridge_in = Node( - package='ros_gz_bridge', - executable='parameter_bridge', - arguments=[ - '/inner_rgbd_camera/image@sensor_msgs/msg/Image@gz.msgs.Image', - '/inner_rgbd_camera/camera_info@sensor_msgs/msg/CameraInfo@gz.msgs.CameraInfo', - '/inner_rgbd_camera/depth_image@sensor_msgs/msg/Image@gz.msgs.Image', - '/inner_rgbd_camera/points@sensor_msgs/msg/PointCloud2@gz.msgs.PointCloudPacked' - ], - output='screen', - condition=IfCondition(sim_gazebo) and IfCondition(vision_bridge)) - - clock_bridge = Node( - package='ros_gz_bridge', - executable='parameter_bridge', - arguments=['/clock@rosgraph_msgs/msg/Clock[ignition.msgs.Clock'], - output='screen', - condition=IfCondition(sim_gazebo)) - - nodes_to_start = [ - gazebo, - gazebo_server, - gazebo_spawn_robot, - rgbd_bridge_out, - rgbd_bridge_in, - clock_bridge, - ] - return LaunchDescription(declared_arguments + nodes_to_start) diff --git a/rbs_simulation/launch/simulation_gazebo.launch.py b/rbs_simulation/launch/simulation_gazebo.launch.py deleted file mode 100644 index 997d075..0000000 --- a/rbs_simulation/launch/simulation_gazebo.launch.py +++ /dev/null @@ -1,93 +0,0 @@ -import os -from launch_ros.actions import Node -from launch import LaunchDescription -from launch.actions import DeclareLaunchArgument, IncludeLaunchDescription -from launch_ros.substitutions import FindPackageShare -from launch.substitutions import Command, FindExecutable, LaunchConfiguration, PathJoinSubstitution -from launch.conditions import IfCondition, UnlessCondition -from launch.launch_description_sources import PythonLaunchDescriptionSource -from ament_index_python.packages import get_package_share_directory - - -def generate_launch_description(): - declared_arguments = [] - declared_arguments.append( - DeclareLaunchArgument("sim_gazebo", - default_value="false", - description="Gazebo Simulation") - ) - declared_arguments.append( - DeclareLaunchArgument("gazebo_gui", - default_value="false", - description="Launch gazebo_gui?") - ) - declared_arguments.append( - DeclareLaunchArgument("debugger", - default_value="false", - description="launch Gazebo with debugger?") - ) - declared_arguments.append( - DeclareLaunchArgument("rgbd_camera", - default_value="true", - description="Camera are used?") - ) - - sim_gazebo = LaunchConfiguration("sim_gazebo") - gazebo_gui = LaunchConfiguration("gazebo_gui") - debugger = LaunchConfiguration("debugger") - rgbd_camera = LaunchConfiguration("rgbd_camera") - gazebo_world_filename = LaunchConfiguration("gazebo_world_filename") - - world_config_file = PathJoinSubstitution( - [FindPackageShare("rbs_simulation"), "worlds", gazebo_world_filename] - ) - gazebo_server = IncludeLaunchDescription( - PythonLaunchDescriptionSource( - [os.path.join(get_package_share_directory('ros_gz_sim'), - 'launch', 'gz_sim.launch.py')]), - launch_arguments={ - 'gz_args': [' -s ', '-r ', world_config_file], - "debugger": debugger, - }.items(), - condition=UnlessCondition(gazebo_gui)) - - gazebo = IncludeLaunchDescription( - PythonLaunchDescriptionSource( - [os.path.join(get_package_share_directory('ros_gz_sim'), - 'launch', 'gz_sim.launch.py')]), - launch_arguments={ - 'gz_args': [' -r ', world_config_file], - "debugger": debugger, - }.items(), - condition=IfCondition(gazebo_gui)) - - rgbd_sensor_bridge = Node( - package="ros_gz_bridge", - executable="parameter_bridge", - arguments=[ - '/rgbd_camera/image@sensor_msgs/msg/Image@gz.msgs.Image', - '/rgbd_camera/camera_info@sensor_msgs/msg/CameraInfo@gz.msgs.CameraInfo', - '/rgbd_camera/depth_image@sensor_msgs/msg/Image@gz.msgs.Image', - '/rgbd_camera/points@sensor_msgs/msg/PointCloud2@gz.msgs.PointCloudPacked' - ], - output='screen', - condition=IfCondition(rgbd_camera) - ) - - - clock_bridge = Node( - package='ros_gz_bridge', - executable='parameter_bridge', - arguments=[ - '/clock@rosgraph_msgs/msg/Clock[ignition.msgs.Clock' - ], - output='screen', - condition=IfCondition(sim_gazebo)) - - nodes_to_start = [ - gazebo, - gazebo_server, - clock_bridge, - rgbd_sensor_bridge, - ] - return LaunchDescription(declared_arguments + nodes_to_start) diff --git a/rbs_simulation/launch/simulation_spawn.launch.py b/rbs_simulation/launch/simulation_spawn.launch.py deleted file mode 100644 index f8f56d0..0000000 --- a/rbs_simulation/launch/simulation_spawn.launch.py +++ /dev/null @@ -1,76 +0,0 @@ -from launch_ros.actions import Node -from launch import LaunchDescription -from launch.actions import DeclareLaunchArgument, OpaqueFunction -from launch.substitutions import LaunchConfiguration -from launch.conditions import IfCondition - -def launch_setup(context, *args, **kwargs): - sim_gazebo = LaunchConfiguration("sim_gazebo") - rbs_robot_name= LaunchConfiguration("rbs_robot_name") - namespace = LaunchConfiguration("namespace") - x_pos = LaunchConfiguration("x_pos") - y_pos = LaunchConfiguration("y_pos") - z_pos = LaunchConfiguration("z_pos") - # Convert LaunchConfiguration to string values - namespace = namespace.perform(context) - # Spawn robot - # TODO: add full pose support include rotation - gazebo_spawn_robot = Node( - package='ros_gz_sim', - executable='create', - arguments=[ - '-name', rbs_robot_name, - '-x', x_pos.perform(context), - '-y', y_pos.perform(context), - '-z', z_pos.perform(context), - '-topic', namespace + '/robot_description'], - output='screen', - condition=IfCondition(sim_gazebo)) - - nodes_to_start = [ - gazebo_spawn_robot, - ] - - return nodes_to_start - - -def generate_launch_description(): - declared_arguments = [] - declared_arguments.append( - DeclareLaunchArgument("sim_gazebo", - default_value="false", - description="Gazebo Simulation") - ) - declared_arguments.append( - DeclareLaunchArgument("rbs_robot_type", - description="Type of robot by name", - choices=["rbs_arm" ,"ur3", "ur3e", "ur5", "ur5e", "ur10", "ur10e", "ur16e"], - default_value="rbs_arm",) - ) - declared_arguments.append( - DeclareLaunchArgument("gazebo_gui", - default_value="true", - description="Launch gazebo_gui?") - ) - declared_arguments.append( - DeclareLaunchArgument("namespace", - default_value="", - description="namespace for spawn a robot") - ) - declared_arguments.append( - DeclareLaunchArgument("x_pos", - default_value="0.0", - description="robot's position along X") - ) - declared_arguments.append( - DeclareLaunchArgument("y_pos", - default_value="0.0", - description="robot's position along Y") - ) - declared_arguments.append( - DeclareLaunchArgument("z_pos", - default_value="0.0", - description="robot's position along Z") - ) - - return LaunchDescription(declared_arguments + [OpaqueFunction(function=launch_setup)]) diff --git a/rbs_simulation/models/CMakeLists.txt b/rbs_simulation/models/CMakeLists.txt deleted file mode 100644 index 86bf0f6..0000000 --- a/rbs_simulation/models/CMakeLists.txt +++ /dev/null @@ -1,21 +0,0 @@ -macro(list_subdirectories retval curdir return_relative) - file(GLOB sub-dir RELATIVE ${curdir} *) - set(list_of_dirs "") - foreach(dir ${sub-dir}) - if(IS_DIRECTORY ${curdir}/${dir}) - if (${return_relative}) - set(list_of_dirs ${list_of_dirs} ${dir}) - else() - set(list_of_dirs ${list_of_dirs} ${curdir}/${dir}) - endif() - endif() - endforeach() - set(${retval} ${list_of_dirs}) -endmacro() - -list_subdirectories(SUBDIR ${CMAKE_CURRENT_LIST_DIR} TRUE) - -install( - DIRECTORY ${SUBDIR} - DESTINATION share/${PROJECT_NAME} -) \ No newline at end of file diff --git a/rbs_simulation/models/box1/frames.json b/rbs_simulation/models/box1/frames.json deleted file mode 100644 index 492eb98..0000000 --- a/rbs_simulation/models/box1/frames.json +++ /dev/null @@ -1,40 +0,0 @@ -{ - "label": "box1", - "type": "component", - "include": [], - "features": { - "grasp-poses": { - "Gripper_for_Part__Feature057": { - "placement": { - "position": { - "x": 0.0, - "y": 0.0, - "z": 0.149 - }, - "orientation": { - "x": 0.0, - "y": 1.0, - "z": 0.0, - "w": 0.0 - } - }, - "distance": 0.015 - } - }, - "placements": { - "placement": { - "position": { - "x": 0.0, - "y": 0.0, - "z": 0.0 - }, - "orientation": { - "x": 0.0, - "y": 0.0, - "z": 0.0, - "w": 0.0 - } - } - } - } -} \ No newline at end of file diff --git a/rbs_simulation/models/box1/model.config b/rbs_simulation/models/box1/model.config deleted file mode 100644 index 41f885c..0000000 --- a/rbs_simulation/models/box1/model.config +++ /dev/null @@ -1,14 +0,0 @@ - - - box1 - model.sdf - - - Splinter1984 - rom.andrianov1984@gmail.com - - - - A box1. - - diff --git a/rbs_simulation/models/box1/model.sdf b/rbs_simulation/models/box1/model.sdf deleted file mode 100644 index 1c61d3c..0000000 --- a/rbs_simulation/models/box1/model.sdf +++ /dev/null @@ -1,58 +0,0 @@ - - - - 0 0 0.015 0 0 0 - - - - 0.00004167 - 0.0 - 0.0 - 0.00004167 - 0.0 - 0.00004167 - - 0.1 - - - - - - 0.05 0.05 0.05 - - - - - - - - - - - - 0.3 - - - - - 0.2 - 0.2 - - - - - - - - 0.05 0.05 0.05 - - - - - - - diff --git a/rbs_simulation/models/box12/frames.json b/rbs_simulation/models/box12/frames.json deleted file mode 100644 index e994e61..0000000 --- a/rbs_simulation/models/box12/frames.json +++ /dev/null @@ -1,40 +0,0 @@ -{ - "label": "box12", - "type": "assembly", - "include": ["box1", "box2"], - "features": { - "grasp-poses": { - "Gripper_for_Part__Feature059": { - "placement": { - "position": { - "x": 0.0, - "y": 0.0, - "z": 0.129 - }, - "orientation": { - "x": 0.0, - "y": 1.0, - "z": 0.0, - "w": 0.0 - } - }, - "distance": 0.015 - } - }, - "placements": { - "placement": { - "position": { - "x": 0.0, - "y": 0.0, - "z": 0.0 - }, - "orientation": { - "x": 0.0, - "y": 0.0, - "z": 0.0, - "w": 0.0 - } - } - } - } -} \ No newline at end of file diff --git a/rbs_simulation/models/box12/model.config b/rbs_simulation/models/box12/model.config deleted file mode 100644 index aa5db29..0000000 --- a/rbs_simulation/models/box12/model.config +++ /dev/null @@ -1,14 +0,0 @@ - - - box12 - model.sdf - - - Splinter1984 - rom.andrianov1984@gmail.com - - - - A box12. - - diff --git a/rbs_simulation/models/box12/model.sdf b/rbs_simulation/models/box12/model.sdf deleted file mode 100644 index 80ffad1..0000000 --- a/rbs_simulation/models/box12/model.sdf +++ /dev/null @@ -1,19 +0,0 @@ - - - - 0 0 0.015 0 0 0 - - 0 0 0 0 0 0 - 0 - - - 0 0 0.03 0 0 0 - 0 - - - box1 - box2 - 0.0 0.0 0.06 0.0 0.0 0.0 - - - diff --git a/rbs_simulation/models/box2/frames.json b/rbs_simulation/models/box2/frames.json deleted file mode 100644 index 7a1c5dd..0000000 --- a/rbs_simulation/models/box2/frames.json +++ /dev/null @@ -1,40 +0,0 @@ -{ - "label": "box2", - "type": "component", - "include": [], - "features": { - "grasp-poses": { - "Gripper_for_Part__Feature058": { - "placement": { - "position": { - "x": 0.0, - "y": 0.0, - "z": 0.129 - }, - "orientation": { - "x": 0.0, - "y": 1.0, - "z": 0.0, - "w": 0.0 - } - }, - "distance": 0.015 - } - }, - "placements": { - "placement": { - "position": { - "x": 0.0, - "y": 0.0, - "z": 0.0 - }, - "orientation": { - "x": 0.0, - "y": 0.0, - "z": 0.0, - "w": 0.0 - } - } - } - } -} \ No newline at end of file diff --git a/rbs_simulation/models/box2/model.config b/rbs_simulation/models/box2/model.config deleted file mode 100644 index 691fbfa..0000000 --- a/rbs_simulation/models/box2/model.config +++ /dev/null @@ -1,14 +0,0 @@ - - - box2 - model.sdf - - - Splinter1984 - rom.andrianov1984@gmail.com - - - - A box2. - - diff --git a/rbs_simulation/models/box2/model.sdf b/rbs_simulation/models/box2/model.sdf deleted file mode 100644 index 6e3fab2..0000000 --- a/rbs_simulation/models/box2/model.sdf +++ /dev/null @@ -1,29 +0,0 @@ - - - - 0 0 0.015 0 0 0 - - 0 - - - - 0.03 0.03 0.03 - - - - - - - 0.03 0.03 0.03 - - - - 0.1 0.75 0 5 - 0.9 0.7 0 1 - 0.4 0.4 0.4 64 - 0.2 0 0.2 2 - - - - - diff --git a/rbs_simulation/models/fork/meshes/collision/fork.stl b/rbs_simulation/models/fork/meshes/collision/fork.stl deleted file mode 100644 index e6d850c..0000000 Binary files a/rbs_simulation/models/fork/meshes/collision/fork.stl and /dev/null differ diff --git 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147 103 147 131 174 132 175 103 147 132 175 108 145 109 146 133 176 103 147 103 147 133 176 134 177 103 147 134 177 102 157 102 157 134 177 135 178 102 157 135 178 115 155 136 179 137 180 138 181 137 180 139 182 140 183 139 184 114 154 111 150 139 184 111 150 140 185 140 185 111 150 110 149 140 185 110 149 141 186 141 186 110 149 123 166 141 186 123 166 142 187 142 187 123 166 122 165 142 187 122 165 143 188 143 188 122 165 121 164 143 188 121 164 144 189 144 189 121 164 118 160 144 189 118 160 145 190 145 190 118 160 117 159 145 190 117 159 146 191 146 191 117 159 126 169 146 191 126 169 147 192 147 192 126 169 125 168 147 192 125 168 148 193 148 193 125 168 124 167 148 193 124 167 149 194 149 194 124 167 120 163 149 194 120 163 150 195 150 195 120 163 119 162 150 195 119 162 151 196 151 196 119 162 129 172 151 196 129 172 152 197 152 197 129 172 128 171 152 197 128 171 153 198 137 180 140 183 138 181 138 181 140 183 141 199 138 181 141 199 154 200 154 200 141 199 142 201 154 200 142 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0 0 1 1 2 2 2 2 3 3 4 4 4 4 3 3 5 5 4 4 5 5 6 6 6 6 5 5 7 7 6 6 7 7 8 8 8 8 7 7 9 9 8 8 9 9 10 10 2 2 4 4 0 0 0 0 4 4 6 6 0 0 6 6 11 11 11 11 6 6 8 8 11 11 8 8 12 12 12 12 8 8 10 10 12 12 10 10 13 13 5 14 14 15 15 16 5 14 15 16 7 17 7 17 15 16 16 18 7 17 16 18 9 19 16 18 17 20 9 19 9 19 17 20 18 21 9 19 18 21 10 22 10 22 18 21 19 23 10 22 19 23 13 24 13 24 19 23 20 25 13 24 20 25 21 26 20 25 22 27 21 26 21 26 22 27 23 28 21 26 23 28 24 29 23 28 25 30 24 29 24 29 25 30 26 31 24 29 26 31 27 32 26 31 28 33 27 32 27 32 28 33 29 34 27 32 29 34 30 35 29 34 28 33 31 36 31 36 28 33 32 37 28 33 26 31 32 37 32 37 26 31 25 30 32 37 25 30 33 38 25 30 23 28 33 38 33 38 23 28 22 27 33 38 22 27 34 39 22 27 20 25 34 39 34 39 20 25 19 23 34 39 19 23 35 40 19 23 18 21 35 40 35 40 18 21 17 20 35 40 17 20 36 41 14 15 37 42 15 16 15 16 37 42 36 41 15 16 36 41 16 18 16 18 36 41 17 20 38 43 39 44 40 45 41 46 42 47 43 48 38 43 40 45 44 49 44 49 40 45 45 50 44 49 45 50 46 51 46 51 45 50 47 52 46 51 47 52 48 53 48 53 49 54 46 51 46 51 49 54 50 55 46 51 50 55 44 49 44 49 50 55 41 46 44 49 41 46 38 43 38 43 41 46 43 48 38 43 43 48 39 44 40 56 51 57 52 58 40 56 52 58 45 59 45 59 52 58 53 60 45 59 53 60 47 61 47 61 53 60 54 62 47 61 54 62 48 63 48 63 54 62 55 64 48 63 55 64 56 65 56 65 55 64 57 66 56 65 57 66 58 67 58 67 57 66 59 68 58 67 59 68 60 69 61 70 59 68 57 66 61 70 57 66 62 71 62 71 57 66 55 64 62 71 55 64 63 72 63 73 55 64 54 62 63 73 54 62 64 74 64 74 54 62 53 60 64 74 53 60 65 75 65 76 53 60 52 58 65 76 52 58 66 77 66 77 52 58 51 57 66 77 51 57 67 78 83 127 102 128 81 129 81 129 102 128 103 130 81 129 103 130 79 131 104 132 105 133 106 119 106 119 105 133 107 119 106 119 107 119 108 119 108 119 107 119 109 119 108 119 109 119 110 134 111 135 112 136 113 137 113 137 112 136 114 138 113 137 114 138 104 132 104 132 114 138 115 139 104 132 115 139 105 133 103 130 116 140 79 131 79 131 116 140 117 141 79 131 117 141 77 142 77 142 117 141 118 143 77 142 118 143 75 144 75 144 118 143 119 145 75 144 119 145 73 146 109 119 120 147 110 134 110 134 120 147 121 148 110 134 121 148 122 149 122 149 121 148 123 150 122 149 123 150 85 151 85 151 123 150 124 152 85 151 124 152 83 127 83 127 124 152 125 153 83 127 125 153 102 128 119 145 126 154 73 146 73 146 126 154 127 155 73 146 127 155 71 156 71 156 127 155 128 157 71 156 128 157 68 158 68 158 128 157 129 159 68 158 129 159 111 135 111 135 129 159 130 119 111 135 130 119 112 136 129 160 131 161 132 162 129 160 132 162 130 163 130 163 132 162 133 164 130 163 133 164 112 165 112 165 133 164 134 166 112 165 134 166 114 167 114 167 134 166 135 168 114 167 135 168 115 169 115 169 135 168 136 170 115 169 136 170 105 171 105 171 136 170 137 172 105 171 137 172 107 173 107 173 137 172 138 174 107 173 138 174 109 175 109 175 138 174 139 176 109 175 139 176 120 177 120 177 139 176 140 178 120 177 140 178 121 179 121 179 140 178 141 180 121 179 141 180 123 181 123 181 141 180 142 182 123 181 142 182 124 183 143 184 144 185 145 186 145 186 144 185 146 187 145 186 146 187 147 187 147 187 146 187 148 187 147 187 148 187 149 188 149 188 148 187 150 189 149 188 150 189 151 190 151 190 150 189 152 191 151 190 152 191 153 187 153 187 152 191 154 187 153 187 154 187 155 187 155 187 154 187 156 187 155 187 156 187 157 187 158 192 159 193 160 194 158 192 160 194 161 195 161 195 160 194 162 196 161 195 162 196 163 197 163 197 162 196 164 198 163 197 164 198 165 198 165 198 164 198 166 199 165 198 166 199 167 200 167 200 166 199 168 201 167 200 168 201 169 202 169 202 168 201 170 203 169 202 170 203 171 204 171 204 170 203 172 205 171 204 172 205 173 206 173 206 172 205 174 207 173 206 174 207 175 208 175 208 174 207 176 209 175 208 176 209 177 210 177 210 176 209 178 211 177 210 178 211 179 212 179 212 178 211 180 213 180 213 178 211 181 214 180 213 181 214 182 215 183 216 184 217 185 218 185 218 184 217 186 219 185 218 186 219 187 220 187 220 186 219 188 119 187 220 188 119 189 119 189 119 188 119 190 119 189 119 190 119 191 221 191 221 190 119 192 222 191 221 192 222 193 223 193 223 192 222 194 224 193 223 194 224 195 225 195 225 194 224 182 226 195 225 182 226 181 119 196 227 171 228 197 229 197 229 171 228 173 230 197 229 173 230 198 231 199 232 163 233 200 234 200 234 163 233 165 235 200 234 165 235 201 236 201 236 165 235 167 237 201 236 167 237 196 227 196 227 167 237 169 238 196 227 169 238 171 228 202 239 203 240 204 241 204 241 203 240 205 242 204 241 205 242 206 243 206 243 205 242 158 244 206 243 158 244 199 232 199 232 158 244 161 245 199 232 161 245 163 233 207 246 208 247 209 248 209 248 208 247 210 249 209 248 210 249 211 250 211 250 210 249 212 251 211 250 212 251 213 252 173 230 175 253 198 231 198 231 175 253 177 254 198 231 177 254 214 255 214 255 177 254 179 256 214 255 179 256 215 257 215 257 179 256 180 258 215 257 180 258 207 246 207 246 180 258 216 259 207 246 216 259 208 247 212 251 217 260 213 252 213 252 217 260 218 261 213 252 218 261 219 262 219 262 218 261 220 263 219 262 220 263 202 239 202 239 220 263 221 264 202 239 221 264 203 240 364 463 365 464 366 465 367 466 368 467 369 468 370 469 371 470 372 471 372 471 371 470 367 466 367 466 369 468 372 471 372 471 369 468 373 472 372 471 373 472 374 473 374 473 373 472 375 474 374 473 375 474 376 475 375 474 377 476 376 475 376 475 377 476 378 477 376 475 378 477 379 478 379 478 378 477 380 479 379 478 380 479 381 480 382 481 383 482 384 483 384 483 383 482 385 484 384 483 385 484 386 485 386 485 385 484 387 486 386 485 387 486 388 487 388 487 387 486 381 480 388 487 381 480 389 488 389 488 381 480 380 479 390 489 391 490 392 491 392 491 391 490 393 492 392 491 393 492 394 493 391 490 395 494 393 492 393 492 395 494 396 495 393 492 396 495 397 496 398 497 370 469 399 498 399 498 370 469 372 471 399 498 372 471 400 499 400 499 372 471 374 473 400 499 374 473 401 500 401 500 374 473 376 475 401 500 376 475 402 501 402 501 376 475 379 478 402 501 379 478 403 502 403 502 379 478 381 480 403 502 381 480 404 503 404 503 381 480 387 486 404 503 387 486 405 504 405 504 387 486 385 484 405 504 385 484 406 505 406 505 385 484 383 482 406 505 383 482 407 506 397 496 408 507 393 492 393 492 408 507 409 508 393 492 409 508 394 493 394 493 409 508 410 509 394 493 410 509 411 510 412 511 398 497 413 512 413 512 398 497 399 498 413 512 399 498 414 513 414 513 399 498 400 514 414 513 400 514 415 515 415 515 400 514 401 516 415 515 401 516 416 517 416 517 401 516 402 518 416 517 402 518 417 519 417 519 402 518 403 520 417 519 403 520 418 521 418 521 403 520 404 522 418 521 404 522 419 523 419 523 404 522 405 524 419 523 405 524 420 525 420 525 405 524 406 526 420 525 406 526 421 527 421 527 406 526 407 528 421 527 407 528 366 465 382 481 390 489 383 482 383 482 390 489 392 491 383 482 392 491 407 506 407 506 392 491 394 493 407 528 394 493 366 465 366 465 394 493 411 510 366 465 411 510 364 463 422 529 418 521 423 530 423 530 418 521 419 523 423 530 419 523 424 531 424 531 419 523 420 525 424 531 420 525 425 532 425 532 420 525 421 527 425 532 421 527 426 533 426 533 421 527 366 465 426 533 366 465 427 534 427 534 366 465 365 464 427 534 365 464 428 535 428 535 365 464 429 536 428 535 429 536 430 537 430 537 429 536 431 538 430 537 431 538 432 539 432 539 431 538 433 540 432 539 433 540 434 541 434 541 433 540 435 542 434 541 435 542 436 543 435 542 437 544 436 543 436 543 437 544 438 545 436 543 438 545 439 546 439 546 438 545 440 547 439 546 440 547 441 548 441 548 440 547 442 549 441 548 442 549 443 550 443 550 442 549 444 551 443 550 444 551 445 552 445 552 444 551 446 553 445 552 446 553 447 554 447 554 446 553 412 511 447 554 412 511 448 555 448 555 412 511 413 512 448 555 413 512 449 556 449 556 413 512 414 513 449 556 414 513 450 557 450 557 414 513 415 515 450 557 415 515 451 558 451 558 415 515 416 517 451 558 416 517 422 529 422 529 416 517 417 519 422 529 417 519 418 521 368 467 471 595 472 596 472 596 471 595 473 597 471 595 474 598 473 597 473 597 474 598 475 599 473 597 475 599 476 600 475 599 477 601 476 600 476 600 477 601 478 602 476 600 478 602 479 603 478 602 480 604 479 603 479 603 480 604 481 605 479 603 481 605 482 606 481 605 483 607 482 606 482 606 483 607 484 608 482 606 484 608 485 609 484 608 486 610 485 609 485 609 486 610 487 611 485 609 487 611 488 612 487 611 489 613 488 612 488 612 489 613 490 614 488 612 490 614 491 615 397 496 492 616 493 617 493 617 492 616 491 615 493 617 491 615 494 618 494 618 491 615 490 614 495 619 496 620 497 621 495 619 497 621 498 622 498 622 497 621 499 623 498 622 499 623 500 624 500 624 499 623 501 625 500 624 501 625 502 626 502 626 501 625 503 627 502 626 503 627 504 628 505 629 506 630 507 631 505 629 507 631 508 632 508 632 507 631 509 633 508 632 509 633 510 634 510 634 509 633 511 635 510 634 511 635 512 636 512 636 511 635 513 637 512 636 513 637 514 638 513 637 515 639 514 638 514 638 515 639 516 640 517 641 518 642 519 643 519 643 518 642 520 644 519 643 520 644 495 619 495 619 520 644 496 620 516 640 515 639 521 645 516 640 521 645 522 646 522 646 521 645 523 647 522 646 523 647 524 648 524 648 523 647 525 649 524 648 525 649 526 650 526 650 525 649 527 651 526 650 527 651 528 652 528 652 527 651 529 653 528 652 529 653 530 654 530 654 529 653 531 655 530 654 531 655 532 656 532 656 531 655 533 657 532 656 533 657 534 658 534 658 533 657 535 659 534 658 535 659 536 660 536 660 535 659 537 661 536 660 537 661 538 662 538 662 537 661 539 663 538 662 539 663 540 664 540 664 539 663 541 665 540 664 541 665 542 666 542 666 541 665 543 667 542 666 543 667 544 668 544 668 543 667 545 669 544 668 545 669 546 670 546 670 545 669 547 671 546 670 547 671 548 672 548 672 547 671 549 672 548 672 549 672 550 673 550 673 549 672 551 674 550 673 551 674 552 675 552 675 551 674 553 676 552 675 553 676 554 677 554 677 553 676 555 678 554 677 555 678 556 679 556 679 555 678 557 680 556 679 557 680 558 681 558 681 557 680 559 682 558 681 559 682 560 683 560 683 559 682 561 684 560 683 561 684 562 685 561 684 563 686 562 685 562 685 563 686 518 642 562 685 518 642 517 641 564 687 565 688 566 689 564 687 566 689 567 690 567 690 566 689 568 691 567 690 568 691 569 692 569 692 568 691 570 693 569 692 570 693 571 694 571 694 570 693 572 695 571 694 572 695 573 696 573 696 572 695 574 697 573 696 574 697 575 698 575 698 574 697 576 699 575 698 576 699 577 700 577 700 576 699 578 701 577 700 578 701 579 702 579 702 578 701 580 703 579 702 580 703 581 704 581 704 580 703 582 705 581 704 582 705 583 706 583 706 582 705 584 707 583 706 584 707 585 708 585 708 584 707 586 709 585 708 586 709 587 710 568 711 566 187 588 712 588 712 566 187 565 187 588 712 565 187 589 187 588 712 590 713 568 711 568 711 590 713 591 714 568 711 591 714 570 715 570 715 591 714 592 716 570 715 592 716 572 717 572 717 592 716 593 718 572 717 593 718 574 719 574 719 593 718 594 720 574 719 594 720 576 721 576 721 594 720 595 722 576 721 595 722 578 723 578 723 595 722 596 187 578 723 596 187 580 187 580 187 596 187 597 187 580 187 597 187 582 187 582 187 597 187 598 724 582 187 598 724 584 725 584 725 598 724 599 726 584 725 599 726 586 727 586 727 599 726 600 728 586 727 600 728 601 729 601 729 600 728 602 730 601 729 602 730 603 187 604 731 573 732 605 733 605 733 573 732 575 734 605 733 575 734 606 735 606 735 575 734 577 736 606 735 577 736 607 737 577 736 579 738 607 737 607 737 579 738 581 739 607 737 581 739 608 119 608 119 581 739 583 740 608 119 583 740 609 741 609 741 583 740 585 742 609 741 585 742 610 743 611 744 567 745 612 746 612 746 567 745 569 747 612 746 569 747 604 731 604 731 569 747 571 748 604 731 571 748 573 732 613 749 614 750 615 119 615 119 614 750 616 751 615 119 616 751 617 752 617 752 616 751 618 753 617 752 618 753 611 744 611 744 618 753 564 754 611 744 564 754 567 745 619 755 620 756 621 757 621 757 620 756 622 758 621 757 622 758 623 759 623 759 622 758 624 760 623 759 624 760 613 749 613 749 624 760 625 761 613 749 625 761 614 750 585 742 587 762 610 743 610 743 587 762 626 763 610 743 626 763 627 764 627 764 626 763 628 765 627 764 628 765 619 755 619 755 628 765 629 766 619 755 629 766 620 756 655 816 656 817 657 818 657 818 656 817 658 119 657 818 658 119 659 119 659 119 658 119 660 119 659 119 660 119 661 119 661 119 660 119 662 119 661 119 662 119 663 819 663 819 662 119 664 820 663 819 664 820 665 821 665 821 664 820 666 822 665 821 666 822 667 823 667 823 666 822 668 824 667 823 668 824 669 825 669 825 668 824 670 826 669 825 670 826 671 119 671 119 670 826 672 119 671 119 672 119 673 119 673 119 672 119 674 119 673 119 674 119 675 119 675 119 674 119 676 827 675 119 676 827 677 828 677 828 676 827 678 829 677 828 678 829 679 830 679 830 678 829 680 831 679 830 680 831 681 832 681 832 680 831 682 833 681 832 682 833 683 834 684 835 668 836 666 837 684 835 666 837 685 838 685 838 666 837 664 839 685 838 664 839 686 839 686 839 664 839 662 840 686 839 662 840 687 841 687 841 662 840 660 842 687 841 660 842 688 843 688 843 660 842 658 844 688 843 658 844 689 845 689 845 658 844 656 846 689 845 656 846 690 847 690 847 656 846 655 848 690 847 655 848 691 849 655 848 692 850 691 849 691 849 692 850 693 851 691 849 693 851 694 852 694 852 693 851 695 853 694 852 695 853 696 854 696 854 695 853 697 855 696 854 697 855 698 856 698 856 697 855 699 857 698 856 699 857 700 858 701 859 690 860 702 861 702 861 690 860 691 862 702 861 691 862 703 863 703 863 691 862 694 864 703 863 694 864 704 865 705 866 686 867 706 868 706 868 686 867 687 869 706 868 687 869 707 870 707 870 687 869 688 871 707 870 688 871 701 859 701 859 688 871 689 872 701 859 689 872 690 860 708 873 709 874 710 187 710 187 709 874 684 875 710 187 684 875 705 866 705 866 684 875 685 876 705 866 685 876 686 867 711 877 712 878 713 879 713 879 712 878 714 880 713 879 714 880 715 881 715 881 714 880 716 882 715 881 716 882 708 873 708 873 716 882 717 883 708 873 717 883 709 874 694 864 696 884 704 865 704 865 696 884 698 885 704 865 698 885 718 886 718 886 698 885 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48 53 49 54 46 51 46 51 49 54 50 55 46 51 50 55 44 49 44 49 50 55 41 46 44 49 41 46 38 43 38 43 41 46 43 48 38 43 43 48 39 44 40 56 51 57 52 58 40 56 52 58 45 59 45 59 52 58 53 60 45 59 53 60 47 61 47 61 53 60 54 62 47 61 54 62 48 63 48 63 54 62 55 64 48 63 55 64 56 65 56 65 55 64 57 66 56 65 57 66 58 67 58 67 57 66 59 68 58 67 59 68 60 69 61 70 59 68 57 66 61 70 57 66 62 71 62 71 57 66 55 64 62 71 55 64 63 72 63 73 55 64 54 62 63 73 54 62 64 74 64 74 54 62 53 60 64 74 53 60 65 75 65 76 53 60 52 58 65 76 52 58 66 77 66 77 52 58 51 57 66 77 51 57 67 78 83 123 102 115 81 124 81 124 102 115 103 125 81 124 103 125 79 126 104 127 105 128 106 129 106 129 105 128 107 130 106 129 107 130 108 131 108 131 107 130 109 132 108 131 109 132 110 133 111 134 112 115 113 135 113 135 112 115 114 136 113 135 114 136 104 127 104 127 114 136 115 137 104 127 115 137 105 128 103 125 116 138 79 126 79 126 116 138 117 139 79 126 117 139 77 140 77 140 117 139 118 141 77 140 118 141 75 142 75 142 118 141 119 143 75 142 119 143 73 115 109 132 120 144 110 133 110 133 120 144 121 145 110 133 121 145 122 115 122 115 121 145 123 146 122 115 123 146 85 147 85 147 123 146 124 148 85 147 124 148 83 123 83 123 124 148 125 149 83 123 125 149 102 115 119 143 126 115 73 115 73 115 126 115 127 115 73 115 127 115 71 115 71 115 127 115 128 150 71 115 128 150 68 151 68 151 128 150 129 152 68 151 129 152 111 134 111 134 129 152 130 153 111 134 130 153 112 115 129 154 131 155 132 156 129 154 132 156 130 157 130 157 132 156 133 158 130 157 133 158 112 159 112 159 133 158 134 160 112 159 134 160 114 161 114 161 134 160 135 162 114 161 135 162 115 163 115 163 135 162 136 164 115 163 136 164 105 165 105 165 136 164 137 166 105 165 137 166 107 167 107 167 137 166 138 168 107 167 138 168 109 169 109 169 138 168 139 170 109 169 139 170 120 171 120 171 139 170 140 172 120 171 140 172 121 173 121 173 140 172 141 174 121 173 141 174 123 175 123 175 141 174 142 176 123 175 142 176 124 177 143 178 144 178 145 178 145 178 144 178 146 178 145 178 146 178 147 178 147 178 146 178 148 179 147 178 148 179 149 180 149 180 148 179 150 181 149 180 150 181 151 178 151 178 150 181 152 182 151 178 152 182 153 183 153 183 152 182 154 184 153 183 154 184 155 185 155 185 154 184 156 186 155 185 156 186 157 187 158 188 159 189 160 190 158 188 160 190 161 191 161 191 160 190 162 192 161 191 162 192 163 193 163 193 162 192 164 194 163 193 164 194 165 195 165 195 164 194 166 196 165 195 166 196 167 197 167 197 166 196 168 198 167 197 168 198 169 199 169 199 168 198 170 200 169 199 170 200 171 201 171 201 170 200 172 202 171 201 172 202 173 203 173 203 172 202 174 204 173 203 174 204 175 205 175 205 174 204 176 206 175 205 176 206 177 207 177 207 176 206 178 208 177 207 178 208 179 209 179 209 178 208 180 210 180 210 178 208 181 211 180 210 181 211 182 212 183 115 184 115 185 115 185 115 184 115 186 115 185 115 186 115 187 213 187 213 186 115 188 214 187 213 188 214 189 215 189 215 188 214 190 216 189 215 190 216 191 217 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202 234 202 234 220 254 221 255 202 234 221 255 203 178 364 457 365 458 366 459 367 460 368 461 369 462 370 463 371 464 372 465 372 465 371 464 367 460 367 460 369 462 372 465 372 465 369 462 373 466 372 465 373 466 374 467 374 467 373 466 375 468 374 467 375 468 376 469 375 468 377 470 376 469 376 469 377 470 378 471 376 469 378 471 379 472 379 472 378 471 380 473 379 472 380 473 381 474 382 475 383 476 384 477 384 477 383 476 385 478 384 477 385 478 386 479 386 479 385 478 387 480 386 479 387 480 388 481 388 481 387 480 381 474 388 481 381 474 389 482 389 482 381 474 380 473 390 483 391 484 392 485 392 485 391 484 393 486 392 485 393 486 394 487 391 484 395 488 393 486 393 486 395 488 396 489 393 486 396 489 397 490 398 491 370 463 399 492 399 492 370 463 372 465 399 492 372 465 400 493 400 493 372 465 374 467 400 493 374 467 401 494 401 494 374 467 376 469 401 494 376 469 402 495 402 495 376 469 379 472 402 495 379 472 403 496 403 496 379 472 381 474 403 496 381 474 404 497 404 497 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425 526 420 519 421 521 425 526 421 521 426 527 426 527 421 521 366 459 426 527 366 459 427 528 427 528 366 459 365 458 427 528 365 458 428 529 428 529 365 458 429 530 428 529 429 530 430 531 430 531 429 530 431 532 430 531 431 532 432 533 432 533 431 532 433 534 432 533 433 534 434 535 434 535 433 534 435 536 434 535 435 536 436 537 435 536 437 538 436 537 436 537 437 538 438 539 436 537 438 539 439 540 439 540 438 539 440 541 439 540 440 541 441 542 441 542 440 541 442 543 441 542 442 543 443 544 443 544 442 543 444 545 443 544 444 545 445 546 445 546 444 545 446 547 445 546 446 547 447 548 447 548 446 547 412 505 447 548 412 505 448 549 448 549 412 505 413 506 448 549 413 506 449 550 449 550 413 506 414 507 449 550 414 507 450 551 450 551 414 507 415 509 450 551 415 509 451 552 451 552 415 509 416 511 451 552 416 511 422 523 422 523 416 511 417 513 422 523 417 513 418 515 368 461 471 589 472 590 472 590 471 589 473 591 471 589 474 592 473 591 473 591 474 592 475 593 473 591 475 593 476 594 475 593 477 595 476 594 476 594 477 595 478 596 476 594 478 596 479 597 478 596 480 598 479 597 479 597 480 598 481 599 479 597 481 599 482 600 481 599 483 601 482 600 482 600 483 601 484 602 482 600 484 602 485 603 484 602 486 604 485 603 485 603 486 604 487 605 485 603 487 605 488 606 487 605 489 607 488 606 488 606 489 607 490 608 488 606 490 608 491 609 397 490 492 610 493 611 493 611 492 610 491 609 493 611 491 609 494 612 494 612 491 609 490 608 495 613 496 614 497 615 495 613 497 615 498 616 498 616 497 615 499 617 498 616 499 617 500 618 500 618 499 617 501 619 500 618 501 619 502 620 502 620 501 619 503 621 502 620 503 621 504 622 505 623 506 624 507 625 505 623 507 625 508 626 508 626 507 625 509 627 508 626 509 627 510 628 510 628 509 627 511 629 510 628 511 629 512 630 512 630 511 629 513 631 512 630 513 631 514 632 513 631 515 633 514 632 514 632 515 633 516 634 517 635 518 636 519 637 519 637 518 636 520 638 519 637 520 638 495 613 495 613 520 638 496 614 516 634 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587 748 626 749 610 730 626 749 627 750 627 750 626 749 628 751 627 750 628 751 619 741 619 741 628 751 629 752 619 741 629 752 620 742 655 115 656 798 657 799 657 799 656 798 658 800 657 799 658 800 659 115 659 115 658 800 660 115 659 115 660 115 661 115 661 115 660 115 662 801 661 115 662 801 663 802 663 802 662 801 664 803 663 802 664 803 665 804 665 804 664 803 666 805 665 804 666 805 667 806 667 806 666 805 668 807 667 806 668 807 669 808 669 808 668 807 670 809 669 808 670 809 671 115 671 115 670 809 672 115 671 115 672 115 673 810 673 810 672 115 674 811 673 810 674 811 675 812 675 812 674 811 676 813 675 812 676 813 677 814 677 814 676 813 678 815 677 814 678 815 679 816 679 816 678 815 680 817 679 816 680 817 681 818 681 818 680 817 682 819 681 818 682 819 683 820 684 821 668 822 666 823 684 821 666 823 685 824 685 824 666 823 664 825 685 824 664 825 686 825 686 825 664 825 662 826 686 825 662 826 687 827 687 827 662 826 660 828 687 827 660 828 688 829 688 829 660 828 658 830 688 829 658 830 689 831 689 831 658 830 656 832 689 831 656 832 690 833 690 833 656 832 655 834 690 833 655 834 691 835 655 834 692 836 691 835 691 835 692 836 693 837 691 835 693 837 694 838 694 838 693 837 695 839 694 838 695 839 696 840 696 840 695 839 697 841 696 840 697 841 698 842 698 842 697 841 699 843 698 842 699 843 700 844 701 845 690 846 702 847 702 847 690 846 691 848 702 847 691 848 703 849 703 849 691 848 694 178 703 849 694 178 704 850 705 851 686 852 706 853 706 853 686 852 687 854 706 853 687 854 707 855 707 855 687 854 688 856 707 855 688 856 701 845 701 845 688 856 689 178 701 845 689 178 690 846 708 857 709 858 710 859 710 859 709 858 684 860 710 859 684 860 705 851 705 851 684 860 685 861 705 851 685 861 686 852 711 862 712 863 713 864 713 864 712 863 714 865 713 864 714 865 715 866 715 866 714 865 716 867 715 866 716 867 708 857 708 857 716 867 717 868 708 857 717 868 709 858 694 178 696 869 704 850 704 850 696 869 698 870 704 850 698 870 718 871 718 871 698 870 700 872 718 871 700 872 719 873 700 872 720 874 719 873 719 873 720 874 721 875 719 873 721 875 722 178 722 178 721 875 723 876 722 178 723 876 724 877 724 877 723 876 725 878 724 877 725 878 711 862 711 862 725 878 726 879 711 862 726 879 712 863 752 923 753 924 181 925 181 925 753 924 754 926 181 925 754 926 195 927 195 927 754 926 755 928 195 927 755 928 193 929 193 929 755 928 756 930 193 929 756 930 191 931 191 931 756 930 757 932 191 931 757 932 189 933 189 933 757 932 758 934 189 933 758 934 187 935 187 935 758 934 759 936 187 935 759 936 185 937 760 938 681 939 683 940 760 938 683 940 759 936 759 936 683 940 183 941 759 936 183 941 185 937 681 939 760 938 761 942 681 939 761 942 679 943 679 943 761 942 762 944 679 943 762 944 677 945 763 946 764 947 765 948 765 948 764 947 655 949 765 948 655 949 657 950 766 951 767 952 768 953 768 953 767 952 769 954 768 953 769 954 770 955 770 955 769 954 771 956 770 955 771 956 772 957 772 957 771 956 773 958 772 957 773 958 774 959 774 959 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597 1003 799 1002 800 1004 597 1003 597 1003 800 1004 801 1005 597 1003 801 1005 598 1006 801 1005 802 1007 598 1006 598 1006 802 1007 803 1008 598 1006 803 1008 599 1009 803 1008 804 1010 599 1009 599 1009 804 1010 805 1011 599 1009 805 1011 600 1012 805 1011 806 1013 600 1012 600 1012 806 1013 784 977 600 1012 784 977 602 979 807 1014 808 1015 589 1016 589 1016 808 1015 785 981 589 1016 785 981 588 980 808 1015 807 1014 809 1017 809 1017 807 1014 810 1018 809 1017 810 1018 811 1019 811 1019 810 1018 812 1020 811 1019 812 1020 813 1021 813 1021 812 1020 814 1022 813 1021 814 1022 815 1023 815 1023 814 1022 816 1024 815 1023 816 1024 817 1025 817 1025 816 1024 818 1026 503 1027 819 1028 504 1029 504 1029 819 1028 820 1030 496 178 520 178 821 178 503 178 501 178 819 178 819 178 501 178 499 178 819 178 499 178 821 178 821 178 499 178 497 178 821 178 497 178 496 178 502 1031 504 115 820 1032 519 1033 495 1034 822 1035 822 1035 495 1034 498 115 822 1035 498 115 820 1032 820 1032 498 115 500 1036 820 1032 500 1036 502 1031 133 1037 132 1038 777 1039 777 1039 132 1038 131 115 777 1039 131 115 143 115 141 1040 140 1041 823 1042 810 1043 807 1044 140 1041 603 1045 157 1046 824 1047 825 1048 826 1049 827 1050 137 115 818 1051 138 115 138 115 818 1051 816 1052 138 115 816 1052 139 1053 139 1053 816 1052 814 1054 139 1053 814 1054 140 1041 140 1041 814 1054 812 1055 140 1041 812 1055 810 1043 137 115 136 1056 818 1051 818 1051 136 1056 135 1057 818 1051 135 1057 777 1039 777 1039 135 1057 134 1058 777 1039 134 1058 133 1037 589 1059 828 1060 807 1044 807 1044 828 1060 829 1061 807 1044 829 1061 140 1041 140 1041 829 1061 830 1062 140 1041 830 1062 823 1042 141 1040 823 1042 142 1063 142 1063 823 1042 831 1064 142 1063 831 1064 825 1048 825 1048 831 1064 832 1065 825 1048 832 1065 826 1049 824 1047 833 115 603 1045 603 1045 833 115 825 1048 603 1045 825 1048 834 1066 834 1066 825 1048 827 1050 514 632 516 634 760 1067 515 633 513 631 784 1068 784 1068 513 631 835 1069 514 632 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95 94

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3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 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-1.5708 0 - - - - 0 0 0 3.14159 -0 0 - - - 0 0 0 0 -0 0 - false - false - - - 0 0 10 0 -0 0 - true - 1 - -0.5 0.1 -0.9 - 0.8 0.8 0.8 1 - 0.2 0.2 0.2 1 - - 1000 - 0.01 - 0.90000000000000002 - 0.001 - - - 0 - 0 - 0 - - - - diff --git a/rbs_skill_interfaces/CMakeLists.txt b/rbs_skill_interfaces/CMakeLists.txt index 1dc670a..4eb9943 100644 --- a/rbs_skill_interfaces/CMakeLists.txt +++ b/rbs_skill_interfaces/CMakeLists.txt @@ -20,12 +20,15 @@ rosidl_generate_interfaces(${PROJECT_NAME} "action/MoveitSendPose.action" "action/MoveitSendJointStates.action" "action/GripperCommand.action" + "action/MoveitSendPoseWithConstraints.action" + "action/TwistControlWithCondition.action" "action/RbsBt.action" "msg/ObjectInfo.msg" "msg/PropertyValuePair.msg" "msg/ActionFeedbackStatusConstants.msg" "msg/ActionResultStatusConstants.msg" "msg/BoundBox.msg" + "msg/ArucoMarkers.msg" "srv/DetectObject.srv" "srv/BtInit.srv" "srv/AssembleState.srv" diff --git a/rbs_skill_interfaces/action/MoveitSendPose.action b/rbs_skill_interfaces/action/MoveitSendPose.action index 8c76779..3278f82 100644 --- a/rbs_skill_interfaces/action/MoveitSendPose.action +++ b/rbs_skill_interfaces/action/MoveitSendPose.action @@ -1,17 +1,12 @@ -##Description: Moves robot arm to a specified pose relative to the frame in header.frame_id of target_pose -#goal definition - -#Used to indicate which hardcoded motion constraint to use -#e.g 0 no constraint, 1 keep the same end effector orientation -int32 constraint_mode -#similar to geometry_msgs/PoseStamped but using euler instead of quaternion -#at target_pose->header.frame_id define the tf frame -# which the pose will be calculated relative from geometry_msgs/Pose target_pose string robot_name float32 end_effector_velocity float32 end_effector_acceleration -float32 duration #if this action cannot be completed within this time period it should be considered failed. +float32 duration +string planner_id +string pipeline_id +float32 allowed_planning_time +bool try_plan_untill_success --- #result definition bool success diff --git a/rbs_skill_interfaces/action/MoveitSendPoseWithConstraints.action b/rbs_skill_interfaces/action/MoveitSendPoseWithConstraints.action new file mode 100644 index 0000000..c3ddede --- /dev/null +++ b/rbs_skill_interfaces/action/MoveitSendPoseWithConstraints.action @@ -0,0 +1,15 @@ +int32 constraint_mode +geometry_msgs/Pose target_pose +moveit_msgs/OrientationConstraint orientation_constraint +string robot_name +float32 end_effector_velocity +float32 end_effector_acceleration +float32 duration +--- +bool success +uint64 millis_passed +string status +--- +bool success +uint64 millis_passed +string status diff --git a/rbs_skill_interfaces/action/TwistControlWithCondition.action b/rbs_skill_interfaces/action/TwistControlWithCondition.action new file mode 100644 index 0000000..71d4026 --- /dev/null +++ b/rbs_skill_interfaces/action/TwistControlWithCondition.action @@ -0,0 +1,8 @@ +geometry_msgs/Twist twist_cmd +string robot_name +--- +bool success +bool condition_status +--- +bool success +bool condition_status diff --git a/rbs_skill_interfaces/msg/ArucoMarkers.msg b/rbs_skill_interfaces/msg/ArucoMarkers.msg new file mode 100644 index 0000000..184003d --- /dev/null +++ b/rbs_skill_interfaces/msg/ArucoMarkers.msg @@ -0,0 +1,5 @@ + +std_msgs/Header header + +int64[] marker_ids +geometry_msgs/Pose[] poses diff --git a/rbs_skill_interfaces/package.nix b/rbs_skill_interfaces/package.nix new file mode 100644 index 0000000..ba78a1b --- /dev/null +++ b/rbs_skill_interfaces/package.nix @@ -0,0 +1,23 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 + +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license + +{ lib, buildRosPackage, ament-cmake, ament-cmake-gtest, ament-lint-auto, ament-lint-common, geometry-msgs, moveit-msgs, rosidl-default-generators, rosidl-default-runtime, shape-msgs, std-msgs, test-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-skill-interfaces"; + version = "0.0.0"; + + src = ./.; + + buildType = "ament_cmake"; + buildInputs = [ ament-cmake rosidl-default-generators ]; + checkInputs = [ ament-cmake-gtest ament-lint-auto ament-lint-common test-msgs ]; + propagatedBuildInputs = [ geometry-msgs moveit-msgs rosidl-default-runtime shape-msgs std-msgs ]; + nativeBuildInputs = [ ament-cmake rosidl-default-generators ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/rbs_skill_interfaces/srv/GetPickPlacePoses.srv b/rbs_skill_interfaces/srv/GetPickPlacePoses.srv index 52d3384..8d2b056 100644 --- a/rbs_skill_interfaces/srv/GetPickPlacePoses.srv +++ b/rbs_skill_interfaces/srv/GetPickPlacePoses.srv @@ -4,4 +4,5 @@ geometry_msgs/Vector3 grasp_direction geometry_msgs/Vector3 place_direction --- geometry_msgs/Pose[] grasp -geometry_msgs/Pose[] place \ No newline at end of file +geometry_msgs/Pose[] place +bool ok diff --git a/rbs_skill_servers/CMakeLists.txt b/rbs_skill_servers/CMakeLists.txt index d89010e..3bf91bb 100644 --- a/rbs_skill_servers/CMakeLists.txt +++ b/rbs_skill_servers/CMakeLists.txt @@ -100,6 +100,18 @@ add_ros2_component(move_to_pose_moveit_cartesian "rbs_skill_actions::MoveitMtpCart" mtp_moveit_cart) +add_ros2_component(move_to_pose_orientation_constraint + src/mtp_moveit_constraints.cpp + "rbs_skill_actions::MoveitMtpOrientationConstraint" + mtp_moveit_orientation_constraint +) + +add_ros2_component(twist_command_with_condition + ./src/twist_cmd_with_condition.cpp + "rbs_skill_actions::TwistCmdWithCondition" + twist_cmd_with_condition +) + # Install directories and targets install(DIRECTORY include/ DESTINATION include) install(DIRECTORY launch config DESTINATION share/${PROJECT_NAME}) @@ -113,6 +125,8 @@ install( move_to_pose_cartesian move_to_pose_moveit_cartesian move_to_pose_moveit + move_to_pose_orientation_constraint + twist_command_with_condition ARCHIVE DESTINATION lib LIBRARY DESTINATION lib RUNTIME DESTINATION lib/${PROJECT_NAME}) diff --git a/rbs_skill_servers/include/rbs_skill_servers/base_skill.hpp b/rbs_skill_servers/include/rbs_skill_servers/base_skill.hpp index b6842ee..ad51995 100644 --- a/rbs_skill_servers/include/rbs_skill_servers/base_skill.hpp +++ b/rbs_skill_servers/include/rbs_skill_servers/base_skill.hpp @@ -68,6 +68,8 @@ protected: goal->robot_name.c_str()); (void)uuid; + std::lock_guard lock(m_goal_mutex); + m_current_goal = goal; m_current_result = std::make_shared(); @@ -93,6 +95,7 @@ protected: void execute(const std::shared_ptr> goal_handle) { + std::lock_guard lock(m_goal_mutex); m_current_goal_handle = goal_handle; @@ -112,7 +115,7 @@ protected: if (m_controllers_map.count(requiredActionController()) && m_controllers_map[requiredActionController()] == "inactive") { switchController(requiredActionController()); - } else if (m_controllers_map.count(requiredActionController()) == 0) { + } else if (!m_controllers_map.count(requiredActionController())) { loadConfigureSwitchExecuteController({requiredActionController()}); } else if (!checkParameters()) { getRequirementParametersAndExecute(requiredActionController()); @@ -122,6 +125,7 @@ protected: } void updateControllersMap() { + using namespace std::chrono_literals; RCLCPP_INFO(this->get_logger(), "Called list_controllers service to check " @@ -139,6 +143,8 @@ protected: return; } + std::lock_guard lock(m_controllers_map_mutex); + auto response = list_controllers_future.get(); m_controllers_map.clear(); @@ -451,6 +457,11 @@ private: std::vector m_required_controllers{}; std::vector m_missing_controllers{}; std::unordered_map m_controllers_map; + + std::mutex m_goal_mutex; + std::mutex m_controllers_map_mutex; + std::mutex m_controllers_mutex; + }; } // namespace rbs_skill_actions diff --git a/rbs_skill_servers/launch/skills.launch.py b/rbs_skill_servers/launch/skills.launch.py index abd654f..e2ee73a 100644 --- a/rbs_skill_servers/launch/skills.launch.py +++ b/rbs_skill_servers/launch/skills.launch.py @@ -9,8 +9,12 @@ from rbs_launch_utils.launch_common import load_yaml, load_yaml_abs def launch_setup(context, *args, **kwargs): robot_description_content = LaunchConfiguration("robot_description") - robot_description_semantic_content = LaunchConfiguration("robot_description_semantic") - robot_description_kinematics_filepath = LaunchConfiguration("robot_description_kinematics") + robot_description_semantic_content = LaunchConfiguration( + "robot_description_semantic" + ) + robot_description_kinematics_filepath = LaunchConfiguration( + "robot_description_kinematics" + ) use_sim_time = LaunchConfiguration("use_sim_time") use_moveit = LaunchConfiguration("use_moveit") ee_link_name = LaunchConfiguration("ee_link_name").perform(context) @@ -23,13 +27,16 @@ def launch_setup(context, *args, **kwargs): } namespace = LaunchConfiguration("namespace") - kinematics_yaml = load_yaml_abs(robot_description_kinematics_filepath.perform(context)) - robot_description_kinematics = {"robot_description_kinematics": kinematics_yaml} + # kinematics_yaml = load_yaml_abs( + # robot_description_kinematics_filepath.perform(context) + # ) + # robot_description_kinematics = {"robot_description_kinematics": kinematics_yaml} skills_container = ComposableNodeContainer( name="skills", namespace=namespace, package="rclcpp_components", + # prefix=['kitty -e gdb -ex run --args'], # prefix=['gdbserver localhost:1234'], executable="component_container_mt", composable_node_descriptions=[ @@ -79,8 +86,10 @@ def launch_setup(context, *args, **kwargs): parameters=[ robot_description, robot_description_semantic, - robot_description_kinematics, + # robot_description_kinematics, {"use_sim_time": use_sim_time}, + {"base_link": base_link_name}, + {"ee_link": ee_link_name}, ], condition=IfCondition(use_moveit), ), @@ -91,11 +100,38 @@ def launch_setup(context, *args, **kwargs): parameters=[ robot_description, robot_description_semantic, - robot_description_kinematics, + # robot_description_kinematics, {"use_sim_time": use_sim_time}, ], condition=IfCondition(use_moveit), ), + ComposableNode( + package="rbs_skill_servers", + plugin="rbs_skill_actions::MoveitMtpOrientationConstraint", + name="mtp_moveit_orientation_constraint", + parameters=[ + robot_description, + robot_description_semantic, + {"use_sim_time": use_sim_time}, + {"base_link": base_link_name}, + {"ee_link": ee_link_name}, + ], + condition=IfCondition(use_moveit), + ), + ComposableNode( + package="rbs_skill_servers", + plugin="rbs_skill_actions::TwistCmdWithCondition", + name="twist_cmd_with_condition", + parameters=[ + {"use_sim_time": use_sim_time}, + {"condition_topic" : "/gz_ros2_vacuum_gripper_plugin/contact_info"}, + # {"robot_name": namespace}, + {"base_link": base_link_name}, + # {"ee_link": ee_link_name}, + # robot_description, + ], + ), + ], ) @@ -130,15 +166,9 @@ def generate_launch_description(): declared_arguments.append( DeclareLaunchArgument("with_gripper_condition", default_value="") ) - declared_arguments.append( - DeclareLaunchArgument("namespace", default_value="") - ) - declared_arguments.append( - DeclareLaunchArgument("ee_link_name", default_value="") - ) - declared_arguments.append( - DeclareLaunchArgument("base_link_name", default_value="") - ) + declared_arguments.append(DeclareLaunchArgument("namespace", default_value="")) + declared_arguments.append(DeclareLaunchArgument("ee_link_name", default_value="")) + declared_arguments.append(DeclareLaunchArgument("base_link_name", default_value="")) return LaunchDescription( declared_arguments + [OpaqueFunction(function=launch_setup)] ) diff --git a/rbs_skill_servers/package.nix b/rbs_skill_servers/package.nix new file mode 100644 index 0000000..fad702a --- /dev/null +++ b/rbs_skill_servers/package.nix @@ -0,0 +1,49 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license +{ + lib, + buildRosPackage, + action-msgs, + ament-cmake, + ament-lint-auto, + ament-lint-common, + cartesian-compliance-controller, + cartesian-controller-base, + cartesian-controller-handles, + cartesian-controller-utilities, + cartesian-force-controller, + cartesian-motion-controller, + cartesian-twist-controller, + geometric-shapes, + geometry-msgs, + gz-ros2-control, + moveit-core, + moveit-msgs, + moveit-ros-planning, + moveit-ros-planning-interface, + rbs-skill-interfaces, + rbs-utils, + rclcpp, + rclcpp-action, + rclcpp-components, + tf2-eigen, + tf2-ros, +}: +buildRosPackage rec { + pname = "ros-jazzy-rbs-skill-servers"; + version = "0.0.0"; + + src = ./.; + + buildType = "ament_cmake"; + buildInputs = [ament-cmake]; + checkInputs = [ament-lint-auto ament-lint-common]; + propagatedBuildInputs = [action-msgs cartesian-compliance-controller cartesian-controller-base cartesian-controller-handles cartesian-controller-utilities cartesian-force-controller cartesian-motion-controller cartesian-twist-controller geometric-shapes geometry-msgs gz-ros2-control moveit-core moveit-msgs moveit-ros-planning moveit-ros-planning-interface rbs-skill-interfaces rbs-utils rclcpp rclcpp-action rclcpp-components tf2-eigen tf2-ros]; + nativeBuildInputs = [ament-cmake]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [asl20]; + }; +} diff --git a/rbs_skill_servers/package.xml b/rbs_skill_servers/package.xml index f4d0036..08a50c7 100644 --- a/rbs_skill_servers/package.xml +++ b/rbs_skill_servers/package.xml @@ -8,11 +8,21 @@ Apache-2.0 ament_cmake - ign_ros2_control + + cartesian_compliance_controller + cartesian_controller_base + cartesian_controller_handles + cartesian_controller_utilities + cartesian_force_controller + cartesian_motion_controller + cartesian_twist_controller + controller_manager_msgs + rclcpp moveit_core moveit_ros_planning moveit_ros_planning_interface + moveit_msgs tf2_ros diff --git a/rbs_skill_servers/src/mtjs_jtc.cpp b/rbs_skill_servers/src/mtjs_jtc.cpp index f36ee49..9498495 100644 --- a/rbs_skill_servers/src/mtjs_jtc.cpp +++ b/rbs_skill_servers/src/mtjs_jtc.cpp @@ -83,6 +83,7 @@ protected: &wrapped_result) { if (wrapped_result.code == rclcpp_action::ResultCode::SUCCEEDED) { RCLCPP_INFO(this->get_logger(), "Goal succeeded"); + m_current_result->success = true; m_current_goal_handle->succeed(m_current_result); } else { RCLCPP_ERROR(this->get_logger(), "Goal failed"); diff --git a/rbs_skill_servers/src/mtp_cart.cpp b/rbs_skill_servers/src/mtp_cart.cpp index c5010eb..d469cf3 100644 --- a/rbs_skill_servers/src/mtp_cart.cpp +++ b/rbs_skill_servers/src/mtp_cart.cpp @@ -72,7 +72,7 @@ private: m_current_pose_subscriber; geometry_msgs::msg::PoseStamped::SharedPtr m_current_pose; std::string m_base_link; - double m_threshold_distance = 0.02; + double m_threshold_distance = 0.01; std::vector m_trajectory; size_t m_current_step; @@ -92,7 +92,14 @@ private: RCLCPP_INFO(this->get_logger(), "Goal successfully completed"); m_trajectory_timer->cancel(); } else { - publish_pose(m_trajectory.back()); + if (distance > m_threshold_distance) { + publish_pose(m_trajectory.back()); + } else { + m_current_result->success = true; + m_current_goal_handle->succeed(m_current_result); + RCLCPP_INFO(this->get_logger(), "Goal successfully completed"); + m_trajectory_timer->cancel(); + } } } } @@ -139,7 +146,7 @@ private: normalize_orientation(end_pose.orientation); double distance = (end_position - start_position).norm(); - int num_steps = static_cast(distance / 0.01); + int num_steps = static_cast(distance / 0.001); for (int i = 0; i <= num_steps; ++i) { double t = static_cast(i) / num_steps; diff --git a/rbs_skill_servers/src/mtp_jtc.cpp b/rbs_skill_servers/src/mtp_jtc.cpp index 7c4f76a..e66ce23 100644 --- a/rbs_skill_servers/src/mtp_jtc.cpp +++ b/rbs_skill_servers/src/mtp_jtc.cpp @@ -2,6 +2,8 @@ #include "control_msgs/action/follow_joint_trajectory.hpp" #include "kdl/chainiksolverpos_lma.hpp" #include "rbs_skill_servers/base_skill.hpp" +#include +#include #include #include #include @@ -13,6 +15,7 @@ #include #include #include +#include #include #include #include @@ -81,17 +84,28 @@ protected: trajectory_goal.trajectory.joint_names = m_joint_names; - const int max_wait_iterations = 100; - int wait_count = 0; - while (m_current_joint_positions.empty() && - wait_count++ < max_wait_iterations) { - std::this_thread::sleep_for(std::chrono::milliseconds(10)); - } - if (m_current_joint_positions.empty()) { + std::unique_lock lg(m_joint_positon_mutex); + m_current_joint_positions.clear(); + if (!m_joint_positon_cv.wait_for( + lg, std::chrono::milliseconds(1000), + [this]() { return !m_current_joint_positions.empty(); })) { RCLCPP_ERROR(this->get_logger(), "Joint positions were not received in time"); return; } + lg.unlock(); + + // const int max_wait_iterations = 100; + // int wait_count = 0; + // while (m_current_joint_positions.empty() && + // wait_count++ < max_wait_iterations) { + // std::this_thread::sleep_for(std::chrono::milliseconds(10)); + // } + // if (m_current_joint_positions.empty()) { + // RCLCPP_ERROR(this->get_logger(), + // "Joint positions were not received in time"); + // return; + // } std::vector target_joint_values; solveIK(target_joint_values); @@ -127,6 +141,8 @@ private: } // RCLCPP_WARN(this->get_logger(), "Called joint positions"); + std::unique_lock lg(m_joint_positon_mutex); + if (m_joint_mame_to_index.empty()) { m_joint_mame_to_index.reserve(m_joint_names.size()); for (size_t j = 0; j < m_joint_names.size(); ++j) { @@ -149,6 +165,9 @@ private: m_current_joint_positions[j] = msg->position[index_it->second]; } } + lg.unlock(); + + m_joint_positon_cv.notify_one(); } std::vector @@ -233,6 +252,8 @@ private: std::string m_base_link; std::string m_ee_link; std::string m_robot_description; + std::mutex m_joint_positon_mutex; + std::condition_variable m_joint_positon_cv; }; } // namespace rbs_skill_actions diff --git a/rbs_skill_servers/src/mtp_jtc_cart.cpp b/rbs_skill_servers/src/mtp_jtc_cart.cpp index c2b17d5..b1af615 100644 --- a/rbs_skill_servers/src/mtp_jtc_cart.cpp +++ b/rbs_skill_servers/src/mtp_jtc_cart.cpp @@ -75,9 +75,11 @@ public: auto base_link = this->get_parameter("base_link").as_string(); auto robot_ee_link = this->get_parameter("ee_link").as_string(); if (base_link.empty() or robot_ee_link.empty()) { - RCLCPP_ERROR(this->get_logger(), - "Describe robot end-effector link and base link to continue"); - throw std::runtime_error("Describe robot end-effector link and base link to continue"); + RCLCPP_ERROR( + this->get_logger(), + "Describe robot end-effector link and base link to continue"); + throw std::runtime_error( + "Describe robot end-effector link and base link to continue"); } if (!kdl_tree.getChain(base_link, robot_ee_link, m_kdl_chain)) { @@ -135,6 +137,7 @@ protected: &wrapped_result) { if (wrapped_result.code == rclcpp_action::ResultCode::SUCCEEDED) { RCLCPP_INFO(this->get_logger(), "Goal succeeded"); + m_current_result->success = true; m_current_goal_handle->succeed(m_current_result); } else { RCLCPP_ERROR(this->get_logger(), "Goal failed"); diff --git a/rbs_skill_servers/src/mtp_moveit.cpp b/rbs_skill_servers/src/mtp_moveit.cpp index 7b07c9e..6e7c772 100644 --- a/rbs_skill_servers/src/mtp_moveit.cpp +++ b/rbs_skill_servers/src/mtp_moveit.cpp @@ -1,6 +1,9 @@ -#include "moveit/move_group_interface/move_group_interface.h" +#include "geometry_msgs/msg/pose_stamped.hpp" #include "rbs_skill_interfaces/action/moveit_send_pose.hpp" #include "rbs_skill_servers/base_skill.hpp" +#include +#include +#include namespace rbs_skill_actions { @@ -9,52 +12,105 @@ using MoveitSendPose = rbs_skill_interfaces::action::MoveitSendPose; class MoveitMtp : public SkillBase { public: explicit MoveitMtp(const rclcpp::NodeOptions &options = rclcpp::NodeOptions()) - : SkillBase("mtp_moveit", options) {} + : SkillBase("mtp_moveit", options) { + this->declare_parameter("base_link", ""); + this->declare_parameter("ee_link", ""); + } private: + std::shared_ptr move_group_; + std::string requiredActionController() override { return "joint_trajectory_controller"; } void executeAction() override { RCLCPP_INFO(this->get_logger(), "Executing action goal"); + move_group_ = + std::make_shared( + this->shared_from_this(), m_current_goal->robot_name); - moveit::planning_interface::MoveGroupInterface move_group_interface( - this->shared_from_this(), m_current_goal->robot_name); - move_group_interface.startStateMonitor(); + move_group_->startStateMonitor(); - move_group_interface.setPoseTarget(m_current_goal->target_pose); - move_group_interface.setMaxVelocityScalingFactor( + geometry_msgs::msg::PoseStamped pose_stamped; + pose_stamped.pose = m_current_goal->target_pose; + pose_stamped.header.frame_id = this->get_parameter("base_link").as_string(); + pose_stamped.header.stamp = this->get_clock()->now(); + + // TODO(solid-sinusoid): add chomp planner + // // move_group_->setPlannerId("BiTRRT"); + // // move_group_->setPlannerId("chomp"); + // move_group_->setPlanningPipelineId("chomp"); + // RCLCPP_INFO(this->get_logger(), "Planning pipeline_id [%s]", move_group_->getPlanningPipelineId().c_str()); + // + // move_group_->setPoseReferenceFrame(this->get_parameter("base_link").as_string()); + // + // moveit::core::RobotState start_state(*move_group_->getCurrentState()); + // auto current_pose = move_group_->getCurrentPose(this->get_parameter("ee_link").as_string()); + // auto joint_model_group = move_group_->getRobotModel()->getJointModelGroup(m_current_goal->robot_name); + // + // auto transform_to_base = start_state.getFrameTransform(this->get_parameter("base_link").as_string()); + // + // // Eigen::Isometry3d pose_eigen; + // auto pose = pose_stamped.pose; + // Eigen::Vector3d position(pose.position.x, pose.position.y, pose.position.z); + // + // Eigen::Quaterniond orientation(pose.orientation.w, pose.orientation.x, pose.orientation.y, pose.orientation.z); + // + // Eigen::Isometry3d pose_eigen = Eigen::Isometry3d::Identity(); + // pose_eigen.translate(position); + // pose_eigen.rotate(orientation); + // + // Eigen::Isometry3d pose_in_base = transform_to_base * pose_eigen; + // + // bool found_ik = start_state.setFromIK(joint_model_group, pose_in_base); + // std::vector target_state{}; + // if (found_ik) { + // start_state.copyJointGroupPositions(joint_model_group, target_state); + // move_group_->setJointValueTarget(target_state); + // } else{ + // RCLCPP_ERROR(this->get_logger(), "IK solution not found"); + // } + // + + move_group_->setPlanningTime(m_current_goal->allowed_planning_time); + move_group_->setPoseTarget(pose_stamped); + move_group_->setMaxVelocityScalingFactor( m_current_goal->end_effector_velocity); - move_group_interface.setMaxAccelerationScalingFactor( + move_group_->setMaxAccelerationScalingFactor( m_current_goal->end_effector_acceleration); moveit::planning_interface::MoveGroupInterface::Plan plan; - moveit::core::MoveItErrorCode plan_err_code = - move_group_interface.plan(plan); - if (plan_err_code == moveit::core::MoveItErrorCode::INVALID_MOTION_PLAN) { - move_group_interface.plan(plan); + moveit::core::MoveItErrorCode plan_err_code = move_group_->plan(plan); + if (m_current_goal->try_plan_untill_success) { + RCLCPP_INFO(this->get_logger(), "Plan will be trying untill seccess"); + while (plan_err_code != moveit::core::MoveItErrorCode::SUCCESS) { + RCLCPP_WARN(this->get_logger(), "Failed to plan, trying untill seccess"); + plan_err_code = move_group_->plan(plan); + } } if (plan_err_code == moveit::core::MoveItErrorCode::SUCCESS) { RCLCPP_INFO(this->get_logger(), "Planning success"); - // move_group_interface.execute(plan); - moveit::core::MoveItErrorCode move_err_code = - move_group_interface.execute(plan); + moveit::core::MoveItErrorCode move_err_code = move_group_->execute(plan); if (move_err_code == moveit::core::MoveItErrorCode::SUCCESS) { m_current_result->success = true; m_current_goal_handle->succeed(m_current_result); RCLCPP_INFO(this->get_logger(), "Successfully executed action goal"); - } else if (move_err_code == moveit::core::MoveItErrorCode::FAILURE) { - RCLCPP_ERROR(this->get_logger(), "Failure in move:"); + } else { + RCLCPP_ERROR_STREAM( + this->get_logger(), + "Failed to move because:" + << moveit::core::errorCodeToString(move_err_code)); } - } else { RCLCPP_WARN_STREAM(this->get_logger(), - "Failed to generate plan because " - << error_code_to_string(plan_err_code)); + "Failed to generate plan because: " + << moveit::core::errorCodeToString(plan_err_code)); + m_current_result->success = false; m_current_goal_handle->abort(m_current_result); } if (m_current_goal_handle->is_canceling()) { + m_current_result->success = false; m_current_goal_handle->canceled(m_current_result); RCLCPP_ERROR(this->get_logger(), "Action goal canceled"); return; diff --git a/rbs_skill_servers/src/mtp_moveit_cart.cpp b/rbs_skill_servers/src/mtp_moveit_cart.cpp index 535bdc3..6f92450 100644 --- a/rbs_skill_servers/src/mtp_moveit_cart.cpp +++ b/rbs_skill_servers/src/mtp_moveit_cart.cpp @@ -11,10 +11,12 @@ using MoveitSendPose = rbs_skill_interfaces::action::MoveitSendPose; class MoveitMtpCart : public SkillBase { public: - explicit MoveitMtpCart(const rclcpp::NodeOptions &options = rclcpp::NodeOptions()) + explicit MoveitMtpCart( + const rclcpp::NodeOptions &options = rclcpp::NodeOptions()) : SkillBase("mtp_moveit_cart", options) {} private: + std::shared_ptr move_group_; std::string requiredActionController() override { return "joint_trajectory_controller"; } @@ -22,15 +24,15 @@ private: void executeAction() override { RCLCPP_INFO(this->get_logger(), "Executing action goal"); - moveit::planning_interface::MoveGroupInterface move_group_interface( - this->shared_from_this(), m_current_goal->robot_name); - move_group_interface.startStateMonitor(); + move_group_ = + std::make_shared( + this->shared_from_this(), m_current_goal->robot_name); + move_group_->startStateMonitor(); - moveit::core::RobotState start_state( - *move_group_interface.getCurrentState()); + moveit::core::RobotState start_state(*move_group_->getCurrentState()); std::vector waypoints; - auto current_pose = move_group_interface.getCurrentPose(); + auto current_pose = move_group_->getCurrentPose(); geometry_msgs::msg::Pose target_pose = m_current_goal->target_pose; waypoints.push_back(target_pose); @@ -39,49 +41,53 @@ private: target_pose.position.z); moveit_msgs::msg::RobotTrajectory trajectory; - const double jump_threshold = 0.0; const double eef_step = 0.001; - double fraction = move_group_interface.computeCartesianPath( - waypoints, eef_step, jump_threshold, trajectory); + double fraction = + move_group_->computeCartesianPath(waypoints, eef_step, trajectory); robot_trajectory::RobotTrajectory rt( - move_group_interface.getCurrentState()->getRobotModel(), + move_group_->getCurrentState()->getRobotModel(), m_current_goal->robot_name); - rt.setRobotTrajectoryMsg(*move_group_interface.getCurrentState(), trajectory); + rt.setRobotTrajectoryMsg(*move_group_->getCurrentState(), trajectory); trajectory_processing::TimeOptimalTrajectoryGeneration tp; bool su = tp.computeTimeStamps(rt); if (!su) { - RCLCPP_ERROR(this->get_logger(), "Failed to compute timestamp of trajectory"); + RCLCPP_ERROR(this->get_logger(), + "Failed to compute timestamp of trajectory"); m_current_goal_handle->abort(m_current_result); } rt.getRobotTrajectoryMsg(trajectory); moveit::planning_interface::MoveGroupInterface::Plan plan; - plan.trajectory_ = trajectory; + plan.trajectory = trajectory; if (fraction > 0) { RCLCPP_INFO(this->get_logger(), "Planning success"); - moveit::core::MoveItErrorCode execute_err_code = - move_group_interface.execute(plan); - if (execute_err_code == moveit::core::MoveItErrorCode::SUCCESS) { + moveit::core::MoveItErrorCode move_err_code = move_group_->execute(plan); + if (move_err_code == moveit::core::MoveItErrorCode::SUCCESS) { m_current_result->success = true; m_current_goal_handle->succeed(m_current_result); RCLCPP_INFO(this->get_logger(), "Successfully executed action goal"); - } else if (execute_err_code == moveit::core::MoveItErrorCode::FAILURE) { - RCLCPP_ERROR(this->get_logger(), "Failure in move:"); + } else { + RCLCPP_ERROR_STREAM( + this->get_logger(), + "Failed to move because:" + << moveit::core::errorCodeToString(move_err_code)); } // move_group_interface.move(); } else { RCLCPP_WARN(this->get_logger(), "Failed to generate plan"); + m_current_result->success = false; m_current_goal_handle->abort(m_current_result); } if (m_current_goal_handle->is_canceling()) { + m_current_result->success = false; m_current_goal_handle->canceled(m_current_result); RCLCPP_ERROR(this->get_logger(), "Action goal canceled"); return; diff --git a/rbs_skill_servers/src/mtp_moveit_constraints.cpp b/rbs_skill_servers/src/mtp_moveit_constraints.cpp new file mode 100644 index 0000000..e6b19fe --- /dev/null +++ b/rbs_skill_servers/src/mtp_moveit_constraints.cpp @@ -0,0 +1,103 @@ +#include "geometry_msgs/msg/pose_stamped.hpp" +#include "moveit_msgs/msg/constraints.hpp" +#include "moveit_msgs/msg/orientation_constraint.hpp" +#include "rbs_skill_interfaces/action/moveit_send_pose.hpp" +#include "rbs_skill_interfaces/action/moveit_send_pose_with_constraints.hpp" +#include "rbs_skill_servers/base_skill.hpp" +#include +#include +#include +#include + + +namespace rbs_skill_actions { + +using MoveitSendPoseOrientationConstraint = rbs_skill_interfaces::action::MoveitSendPoseWithConstraints; + +class MoveitMtpOrientationConstraint : public SkillBase { +public: + explicit MoveitMtpOrientationConstraint(const rclcpp::NodeOptions &options = rclcpp::NodeOptions()) + : SkillBase("mtp_moveit_orientation_constraint", options) { + this->declare_parameter("base_link", ""); + this->declare_parameter("ee_link", ""); + } + +private: + std::shared_ptr move_group_; + + std::string requiredActionController() override { + return "joint_trajectory_controller"; + } + + void executeAction() override { + RCLCPP_INFO(this->get_logger(), "Executing action goal"); + move_group_ = + std::make_shared( + this->shared_from_this(), m_current_goal->robot_name); + + move_group_->startStateMonitor(); + + geometry_msgs::msg::PoseStamped pose_stamped; + pose_stamped.pose = m_current_goal->target_pose; + pose_stamped.header.frame_id = this->get_parameter("base_link").as_string(); + pose_stamped.header.stamp = this->get_clock()->now(); + + moveit_msgs::msg::OrientationConstraint orientation_constraint; + orientation_constraint.weight = m_current_goal->orientation_constraint.weight; + orientation_constraint.absolute_x_axis_tolerance = m_current_goal->orientation_constraint.absolute_x_axis_tolerance; + orientation_constraint.absolute_y_axis_tolerance = m_current_goal->orientation_constraint.absolute_y_axis_tolerance; + orientation_constraint.absolute_z_axis_tolerance = m_current_goal->orientation_constraint.absolute_z_axis_tolerance; + orientation_constraint.orientation = pose_stamped.pose.orientation; + orientation_constraint.header = pose_stamped.header; + orientation_constraint.link_name = this->get_parameter("ee_link").as_string(); + + moveit_msgs::msg::Constraints constraints; + constraints.orientation_constraints.emplace_back(orientation_constraint); + + move_group_->setPoseTarget(pose_stamped); + move_group_->setPathConstraints(constraints); + move_group_->setMaxVelocityScalingFactor( + m_current_goal->end_effector_velocity); + move_group_->setMaxAccelerationScalingFactor( + m_current_goal->end_effector_acceleration); + move_group_->setPlanningTime(10.0); + + moveit::planning_interface::MoveGroupInterface::Plan plan; + moveit::core::MoveItErrorCode plan_err_code = move_group_->plan(plan); + if (plan_err_code == moveit::core::MoveItErrorCode::INVALID_MOTION_PLAN) { + move_group_->plan(plan); + } + if (plan_err_code == moveit::core::MoveItErrorCode::SUCCESS) { + RCLCPP_INFO(this->get_logger(), "Planning success"); + moveit::core::MoveItErrorCode move_err_code = move_group_->execute(plan); + if (move_err_code == moveit::core::MoveItErrorCode::SUCCESS) { + m_current_result->success = true; + m_current_goal_handle->succeed(m_current_result); + RCLCPP_INFO(this->get_logger(), "Successfully executed action goal"); + } else { + RCLCPP_ERROR_STREAM( + this->get_logger(), + "Failed to move because:" + << moveit::core::errorCodeToString(move_err_code)); + } + } else { + RCLCPP_WARN_STREAM(this->get_logger(), + "Failed to generate plan because: " + << moveit::core::errorCodeToString(plan_err_code)); + m_current_result->success = false; + m_current_goal_handle->abort(m_current_result); + } + + if (m_current_goal_handle->is_canceling()) { + m_current_result->success = false; + m_current_goal_handle->canceled(m_current_result); + RCLCPP_ERROR(this->get_logger(), "Action goal canceled"); + return; + } + } +}; // class MoveToPoseActionServer + +} // namespace rbs_skill_actions + +#include "rclcpp_components/register_node_macro.hpp" +RCLCPP_COMPONENTS_REGISTER_NODE(rbs_skill_actions::MoveitMtpOrientationConstraint); diff --git a/rbs_skill_servers/src/mtp_moveit_cpp.cpp b/rbs_skill_servers/src/mtp_moveit_cpp.cpp new file mode 100644 index 0000000..f9180a5 --- /dev/null +++ b/rbs_skill_servers/src/mtp_moveit_cpp.cpp @@ -0,0 +1,89 @@ +#include "geometry_msgs/msg/pose_stamped.hpp" +#include "rbs_skill_interfaces/action/moveit_send_pose.hpp" +#include "rbs_skill_servers/base_skill.hpp" +#include +#include +#include +#include + +namespace rbs_skill_actions { + +using MoveitSendPose = rbs_skill_interfaces::action::MoveitSendPose; + +class MoveitMtp : public SkillBase { +public: + explicit MoveitMtp(const rclcpp::NodeOptions &options = rclcpp::NodeOptions()) + : SkillBase("mtp_moveit", options) { + this->declare_parameter("base_link", ""); + this->declare_parameter("ee_link", ""); + } + +private: + std::shared_ptr move_group_; + + std::string requiredActionController() override { + return "joint_trajectory_controller"; + } + + void executeAction() override { + RCLCPP_INFO(this->get_logger(), "Executing action goal"); + move_group_ = + std::make_shared( + this->shared_from_this(), m_current_goal->robot_name); + + move_group_->startStateMonitor(); + + geometry_msgs::msg::PoseStamped pose_stamped; + pose_stamped.pose = m_current_goal->target_pose; + pose_stamped.header.frame_id = this->get_parameter("base_link").as_string(); + pose_stamped.header.stamp = this->get_clock()->now(); + + move_group_->setPlanningTime(m_current_goal->alowed_planning_time); + move_group_->setPoseTarget(pose_stamped); + move_group_->setMaxVelocityScalingFactor( + m_current_goal->end_effector_velocity); + move_group_->setMaxAccelerationScalingFactor( + m_current_goal->end_effector_acceleration); + moveit::planning_interface::MoveGroupInterface::Plan plan; + moveit::core::MoveItErrorCode plan_err_code = move_group_->plan(plan); + if (m_current_goal->try_plan_untill_success) { + RCLCPP_INFO(this->get_logger(), "Plan will be trying untill seccess"); + while (plan_err_code != moveit::core::MoveItErrorCode::SUCCESS) { + RCLCPP_WARN(this->get_logger(), "Failed to plan, trying untill seccess"); + plan_err_code = move_group_->plan(plan); + } + } + if (plan_err_code == moveit::core::MoveItErrorCode::SUCCESS) { + RCLCPP_INFO(this->get_logger(), "Planning success"); + moveit::core::MoveItErrorCode move_err_code = move_group_->execute(plan); + if (move_err_code == moveit::core::MoveItErrorCode::SUCCESS) { + m_current_result->success = true; + m_current_goal_handle->succeed(m_current_result); + RCLCPP_INFO(this->get_logger(), "Successfully executed action goal"); + } else { + RCLCPP_ERROR_STREAM( + this->get_logger(), + "Failed to move because:" + << moveit::core::errorCodeToString(move_err_code)); + } + } else { + RCLCPP_WARN_STREAM(this->get_logger(), + "Failed to generate plan because: " + << moveit::core::errorCodeToString(plan_err_code)); + m_current_result->success = false; + m_current_goal_handle->abort(m_current_result); + } + + if (m_current_goal_handle->is_canceling()) { + m_current_result->success = false; + m_current_goal_handle->canceled(m_current_result); + RCLCPP_ERROR(this->get_logger(), "Action goal canceled"); + return; + } + } +}; // class MoveToPoseActionServer + +} // namespace rbs_skill_actions + +#include "rclcpp_components/register_node_macro.hpp" +RCLCPP_COMPONENTS_REGISTER_NODE(rbs_skill_actions::MoveitMtp); diff --git a/rbs_skill_servers/src/twist_cmd_with_condition.cpp b/rbs_skill_servers/src/twist_cmd_with_condition.cpp new file mode 100644 index 0000000..705de44 --- /dev/null +++ b/rbs_skill_servers/src/twist_cmd_with_condition.cpp @@ -0,0 +1,139 @@ +#include "geometry_msgs/msg/twist_stamped.hpp" +#include "rbs_skill_interfaces/action/twist_control_with_condition.hpp" +#include "rbs_skill_servers/base_skill.hpp" +#include "std_msgs/msg/bool.hpp" +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace rbs_skill_actions { + +using TwistCmd = rbs_skill_interfaces::action::TwistControlWithCondition; +using ServerGoalHandle = rclcpp_action::ServerGoalHandle; + +class TwistCmdWithCondition : public SkillBase { +public: + explicit TwistCmdWithCondition( + const rclcpp::NodeOptions &options = rclcpp::NodeOptions()) + : SkillBase("twist_cmd", options), + m_last_msg(std::make_shared()) { + + this->declare_parameter("condition_topic", ""); + this->declare_parameter("base_link", ""); + + auto cbg = + this->create_callback_group(rclcpp::CallbackGroupType::Reentrant); + + rclcpp::SubscriptionOptions sopt; + sopt.callback_group = cbg; + + rclcpp::PublisherOptions popt; + popt.callback_group = cbg; + + m_condition_sub = this->create_subscription( + this->get_parameter("condition_topic").as_string(), 10, + std::bind(&TwistCmdWithCondition::conditionCallback, this, + std::placeholders::_1), + sopt); + + m_command_pub = this->create_publisher( + "/cartesian_twist_controller/twist_cmd", 10, popt); + + m_command_timer = this->create_timer( + std::chrono::milliseconds(100), + std::bind(&TwistCmdWithCondition::publishCmd, this), cbg); + } + +protected: + std::string requiredActionController() override { + return "cartesian_twist_controller"; + } + + std::vector requiredParameters() override { return {"joints"}; } + + void executeAction() override { + RCLCPP_INFO(this->get_logger(), "Starting executing action goal"); + + m_twist_cmd.header.frame_id = this->get_parameter("base_link").as_string(); + m_twist_cmd.header.stamp = this->get_clock()->now(); + m_twist_cmd.twist = m_current_goal->twist_cmd; + + RCLCPP_INFO( + this->get_logger(), "Incoming command twist [%f, %f, %f, %f, %f, %f]", + m_current_goal->twist_cmd.linear.x, m_current_goal->twist_cmd.linear.y, + m_current_goal->twist_cmd.linear.z, m_current_goal->twist_cmd.angular.x, + m_current_goal->twist_cmd.angular.y, + m_current_goal->twist_cmd.angular.z); + + std::unique_lock lg(m_condition_mutex); + + if (!m_condition_cv.wait_for(lg, std::chrono::seconds(30), + [this]() { return m_last_msg->data; })) { + if (m_current_goal_handle) { + m_current_result->success = false; + m_current_goal_handle->abort(m_current_result); + RCLCPP_WARN(this->get_logger(), + "Condition was not met in time, action aborted."); + } + return; + } + if (m_last_msg->data && m_current_goal_handle) { + m_current_result->success = true; + m_current_goal_handle->succeed(m_current_result); + RCLCPP_INFO(this->get_logger(), "Condition is true, stopping action."); + } + lg.unlock(); + } + +private: + rclcpp::Subscription::SharedPtr m_condition_sub; + rclcpp::Publisher::SharedPtr m_command_pub; + rclcpp::TimerBase::SharedPtr m_command_timer; + geometry_msgs::msg::TwistStamped m_twist_cmd; + std_msgs::msg::Bool::SharedPtr m_last_msg; + std::mutex m_condition_mutex; + std::condition_variable m_condition_cv; + bool cond_rising_edge = false; + bool cond_falling_edge = false; + + void publishCmd() { + if (cond_falling_edge) { + m_command_pub->publish(m_twist_cmd); + } else { + m_twist_cmd.twist.linear.x = 0.0; + m_twist_cmd.twist.linear.y = 0.0; + m_twist_cmd.twist.linear.z = 0.0; + m_twist_cmd.twist.angular.x = 0.0; + m_twist_cmd.twist.angular.y = 0.0; + m_twist_cmd.twist.angular.z = 0.0; + m_command_pub->publish(m_twist_cmd); + } + } + + void conditionCallback(const std_msgs::msg::Bool &msg) { + std::lock_guard lg(m_condition_mutex); + + cond_rising_edge = (!m_last_msg->data && msg.data); + cond_falling_edge = (m_last_msg->data && !msg.data); + if (!m_last_msg->data && !msg.data) { + cond_falling_edge = true; + } + if (cond_falling_edge or cond_rising_edge) { + *m_last_msg = msg; + m_condition_cv.notify_one(); + } + } +}; + +} // namespace rbs_skill_actions + +#include "rclcpp_components/register_node_macro.hpp" +RCLCPP_COMPONENTS_REGISTER_NODE(rbs_skill_actions::TwistCmdWithCondition); diff --git a/rbs_task_planner/package.nix b/rbs_task_planner/package.nix new file mode 100644 index 0000000..2860195 --- /dev/null +++ b/rbs_task_planner/package.nix @@ -0,0 +1,23 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 + +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license + +{ lib, buildRosPackage, ament-cmake, ament-cmake-gtest, ament-index-cpp, ament-lint-auto, ament-lint-common, plansys2-bringup, plansys2-bt-actions, plansys2-domain-expert, plansys2-executor, plansys2-msgs, plansys2-pddl-parser, plansys2-planner, plansys2-problem-expert, plansys2-terminal, popf, test-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-task-planner"; + version = "0.0.1"; + + src = ./.; + + buildType = "ament_cmake"; + buildInputs = [ ament-cmake ]; + checkInputs = [ ament-cmake-gtest ament-lint-auto ament-lint-common test-msgs ]; + propagatedBuildInputs = [ ament-index-cpp plansys2-bringup plansys2-bt-actions plansys2-domain-expert plansys2-executor plansys2-msgs plansys2-pddl-parser plansys2-planner plansys2-problem-expert plansys2-terminal popf ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "ROS2 task planner for manipulator"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/rbs_tests/CMakeLists.txt b/rbs_tests/CMakeLists.txt new file mode 100644 index 0000000..731cf0b --- /dev/null +++ b/rbs_tests/CMakeLists.txt @@ -0,0 +1,12 @@ +cmake_minimum_required(VERSION 3.10) +project(rbs_tests) + +find_package(ament_cmake REQUIRED) + +if(BUILD_TESTING) + find_package(rbs_utils REQUIRED) + find_package(launch_testing_ament_cmake) + add_launch_test(integration_tests/integration_tests.py) +endif() + +ament_package() diff --git a/rbs_tests/README.md b/rbs_tests/README.md new file mode 100644 index 0000000..33a7ad2 --- /dev/null +++ b/rbs_tests/README.md @@ -0,0 +1,4 @@ +### Run tests manually +```bash +colcon test --packages-select rbs_tests && colcon test-result --test-result-base build/rbs_tests/ --verbose +``` diff --git a/rbs_tests/integration_tests/integration_tests.py b/rbs_tests/integration_tests/integration_tests.py new file mode 100755 index 0000000..0e0dc72 --- /dev/null +++ b/rbs_tests/integration_tests/integration_tests.py @@ -0,0 +1,61 @@ +#!/usr/bin/env python3 +# import os +import unittest +from unittest.mock import patch, MagicMock + +# import rclpy +# from rclpy.executors import SingleThreadedExecutor +from rbs_utils.recording_demo import recording_demo, CommandType + +import launch +import launch_ros +import launch_testing +import launch_testing.actions +# import launch_testing.asserts +import pytest + +@pytest.mark.rostest +def generate_test_description(): + test_node = launch_ros.actions.Node( + package="rbs_bt_executor", + executable="rbs_interface.py", + output="screen" + # parameters = [{"bt_path": skills_cfg_file},{"mode": mode},{"use_sim_time": True}] + ) + + return launch.LaunchDescription([ + test_node, + launch_testing.actions.ReadyToTest(), + ]), { 'test_node': test_node } + +class TestRecordingDemo(unittest.TestCase): + + def setUp(self): + # Предполагается, что ROS 2 окружение запущено + pass + + def test_run_command_returns_bool(self): + with patch("rbs_utils.recording_demo.RbsActionClient") as MockClient: + mock_client_instance = MockClient.return_value + mock_client_instance.res_ok = True + mock_client_instance.send_goal = MagicMock() + + result = recording_demo(CommandType.RUN) + self.assertTrue(result) + mock_client_instance.send_goal.assert_called_with( + sid=unittest.mock.ANY, action="RecordingDemo", command="rdConfigure") + + def test_stop_and_cancel_triggers_stop(self): + with patch("rbs_utils.recording_demo.RbsActionClient") as MockClient: + mock_client_instance = MockClient.return_value + mock_client_instance.res_ok = True + mock_client_instance.send_goal = MagicMock() + + result = recording_demo(CommandType.STOP_AND_CANCEL) + self.assertTrue(result) + mock_client_instance.send_goal.assert_called_with( + sid=unittest.mock.ANY, action="RecordingDemo", command="rdStop") + + def test_invalid_command_returns_false(self): + result = recording_demo("nonexistent_command") + self.assertFalse(result) diff --git a/rbs_tests/package.xml b/rbs_tests/package.xml new file mode 100644 index 0000000..1ff18b4 --- /dev/null +++ b/rbs_tests/package.xml @@ -0,0 +1,16 @@ + + + + rbs_tests + 0.0.1 + Integration tests for the Robossembler-ROS2 + shalenikol + Apache-2.0 + + launch + launch_ros + rbs_utils + + launch_testing_ament_cmake + + diff --git a/rbs_utils/rbs_utils/CMakeLists.txt b/rbs_utils/rbs_utils/CMakeLists.txt index 92f9442..092778e 100644 --- a/rbs_utils/rbs_utils/CMakeLists.txt +++ b/rbs_utils/rbs_utils/CMakeLists.txt @@ -16,7 +16,6 @@ find_package(geometry_msgs REQUIRED) find_package(sensor_msgs REQUIRED) find_package(rosidl_default_generators REQUIRED) find_package(rbs_utils_interfaces REQUIRED) -find_package(dynmsg REQUIRED) find_package(rclpy REQUIRED) find_package(rosbag2_cpp REQUIRED) find_package(nlohmann_json REQUIRED) @@ -30,32 +29,29 @@ set(deps geometry_msgs sensor_msgs rbs_utils_interfaces - dynmsg rosbag2_cpp ) -add_library(${PROJECT_NAME} SHARED src/rbs_utils.cpp) - ament_python_install_package(${PROJECT_NAME}) install(PROGRAMS scripts/assembly_config_service.py scripts/recording_demo_via_rosbag.py + scripts/example_recording_demo.py + rbs_utils/recording_demo.py DESTINATION lib/${PROJECT_NAME} ) -install( - DIRECTORY include/ - DESTINATION include -) +# install( +# DIRECTORY include/ +# DESTINATION include +# ) install( - DIRECTORY launch + DIRECTORY launch config DESTINATION share/${PROJECT_NAME} ) -ament_target_dependencies(${PROJECT_NAME} PUBLIC ${deps}) - # target_include_directories(asm_folder_process # PUBLIC # "$" @@ -64,19 +60,6 @@ ament_target_dependencies(${PROJECT_NAME} PUBLIC ${deps}) add_executable(bagfile_recorder src/bagfile_recorder.cpp) ament_target_dependencies(bagfile_recorder ${deps}) -target_include_directories(${PROJECT_NAME} - PUBLIC - "$" - "$") - -install( - TARGETS ${PROJECT_NAME} - EXPORT export_${PROJECT_NAME} - LIBRARY DESTINATION lib - ARCHIVE DESTINATION lib - RUNTIME DESTINATION bin -) - install( TARGETS bagfile_recorder DESTINATION lib/${PROJECT_NAME} @@ -96,8 +79,4 @@ if(BUILD_TESTING) ament_lint_auto_find_test_dependencies() endif() -ament_export_targets(export_${PROJECT_NAME} HAS_LIBRARY_TARGET) -ament_export_dependencies( - ${deps} -) ament_package() diff --git a/rbs_utils/rbs_utils/config/recording_demo_skill.json b/rbs_utils/rbs_utils/config/recording_demo_skill.json new file mode 100644 index 0000000..47a4a10 --- /dev/null +++ b/rbs_utils/rbs_utils/config/recording_demo_skill.json @@ -0,0 +1,37 @@ +{ + "skills": [ + { + "sid": "RecordingDemo_cfg", + "SkillPackage": { "name": "Robossembler", "version": "1.0", "format": "1" }, + "Module": { "name": "RecordingDemo", "description": "Recording a demo via RosBag", "node_name": "lc_record_demo" }, + "Launch": { "package": "rbs_utils", "executable": "recording_demo_via_rosbag.py" }, + "BTAction": [ + { + "name": "rdConfigure", "type_action": "ACTION", "type": "run", + "param": [] + }, + { "name": "rdStop", "type_action": "ACTION", "type": "stop", + "param": [ + { + "type": "formBuilder", + "dependency": { + "output": { + "do": "stop_and_cancel" + } + } + } + ] + } + ], + "Settings": { + "output": { + "params": [ + { "name": "output_path", "value": "rbs_bag", "description": "!!! Путь, куда запишется rosbag" }, + { "name": "compressed", "value": "True", "default": "False" }, + { "name": "serialization", "value": "mcap", "default": "cdr" } + ] + } + } + } + ] +} diff --git a/rbs_utils/rbs_utils/include/rbs_utils/rbs_utils.hpp b/rbs_utils/rbs_utils/include/rbs_utils/rbs_utils.hpp deleted file mode 100644 index a8e0fc2..0000000 --- a/rbs_utils/rbs_utils/include/rbs_utils/rbs_utils.hpp +++ /dev/null @@ -1,102 +0,0 @@ -#include "dynmsg/message_reading.hpp" -#include "dynmsg/msg_parser.hpp" -#include "dynmsg/typesupport.hpp" -#include "dynmsg/yaml_utils.hpp" -#include "geometry_msgs/msg/pose.hpp" -#include "geometry_msgs/msg/pose_array.hpp" -#include "rclcpp/rclcpp.hpp" -#include "rclcpp_lifecycle/lifecycle_node.hpp" -#include "tf2_geometry_msgs/tf2_geometry_msgs.hpp" -#include "tf2_msgs/msg/tf_message.hpp" -#include "tf2_ros/buffer.h" -#include "tf2_ros/static_transform_broadcaster.h" -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include - -const std::string env_dir = std::getenv("RBS_ASSEMBLY_DIR"); - -namespace rbs_utils { - -struct EnvModel { - std::string model_name; - std::string mesh_path; - std::vector model_inertia; - std::vector model_pose; - double mass; -}; - -class AssemblyConfigLoader { -public: - template - explicit AssemblyConfigLoader(const std::string &t_assembly_dir, - const NodePtr &t_node) - : AssemblyConfigLoader(t_assembly_dir, - t_node->get_node_logging_interface(), - t_node->get_node_clock_interface()) {} - - explicit AssemblyConfigLoader( - const std::string &t_assembly_dir, - const rclcpp::node_interfaces::NodeLoggingInterface::SharedPtr - &t_logger_node_interface, - const rclcpp::node_interfaces::NodeClockInterface::SharedPtr - &t_clock_node_interface); - - tf2_msgs::msg::TFMessage getAllPossibleTfData(); - tf2_msgs::msg::TFMessage getTfData(const std::string &model_name); - tf2_msgs::msg::TFMessage getGraspTfData(const std::string &model_name); - - std::vector getUniqueSceneModelNames(); - - void printWorkspace(); - geometry_msgs::msg::PoseArray getWorkspaceInspectorTrajectory(); - geometry_msgs::msg::Pose - transformTrajectory(const geometry_msgs::msg::Pose &pose); - void saveRbsConfig(); - tf2_msgs::msg::TFMessage getAdditionalPoses(); - -private: - std::vector m_env_files; - std::vector m_env_paths; - std::string m_assembly_dir; - std::unique_ptr m_tf_buffer; - rbs_utils_interfaces::msg::AssemblyConfig m_assembly_config; - rclcpp::Logger m_logger; - rclcpp::Clock::SharedPtr m_clock; - void parseRbsDb(const std::string &filepath); - - geometry_msgs::msg::PoseArray getWorkspace(); - geometry_msgs::msg::Transform - createTransform(const geometry_msgs::msg::Pose &pose); -}; - -class StaticFramePublisher : public rclcpp::Node { -public: - explicit StaticFramePublisher(const tf2_msgs::msg::TFMessage &tfs) - : Node("rbs_static_tf") { - m_tf_static_broadcaster = - std::make_shared(this); - - this->make_transforms(tfs); - } - -private: - void make_transforms(const tf2_msgs::msg::TFMessage &tfs) { - for (const auto &transform : tfs.transforms) { - m_tf_static_broadcaster->sendTransform(transform); - } - } - - std::shared_ptr m_tf_static_broadcaster; -}; -} // namespace rbs_utils diff --git a/rbs_utils/rbs_utils/launch/image_compressed_to_raw.launch.py b/rbs_utils/rbs_utils/launch/image_compressed_to_raw.launch.py new file mode 100644 index 0000000..a0ed023 --- /dev/null +++ b/rbs_utils/rbs_utils/launch/image_compressed_to_raw.launch.py @@ -0,0 +1,75 @@ +""" + https://github.com/clearpathrobotics/clearpath_robot + +# Software License Agreement (BSD) +# +# @author Roni Kreinin +# @copyright (c) 2023, Clearpath Robotics, Inc., All rights reserved. +# +# Redistribution and use in source and binary forms, with or without +# modification, are permitted provided that the following conditions are met: +# * Redistributions of source code must retain the above copyright notice, +# this list of conditions and the following disclaimer. +# * Redistributions in binary form must reproduce the above copyright notice, +# this list of conditions and the following disclaimer in the documentation +# and/or other materials provided with the distribution. +# * Neither the name of Clearpath Robotics nor the names of its contributors +# may be used to endorse or promote products derived from this software +# without specific prior written permission. +# +# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE +# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR +# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF +# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS +# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN +# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) +# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE +# POSSIBILITY OF SUCH DAMAGE. +""" +from launch import LaunchDescription +from launch.actions import DeclareLaunchArgument +from launch.substitutions import LaunchConfiguration +from launch_ros.actions import Node + + +def generate_launch_description(): + namespace = LaunchConfiguration('namespace') + in_compressed = LaunchConfiguration('in_compressed') + out_raw = LaunchConfiguration('out_raw') + + arg_namespace = DeclareLaunchArgument( + 'namespace', + default_value='' + ) + + arg_in_compressed = DeclareLaunchArgument( + 'in_compressed', + default_value='compressed' + ) + + arg_out_raw = DeclareLaunchArgument( + 'out_raw', + default_value='image' + ) + + compressed_transport_node = Node( + name='image_compressed_to_raw', + namespace=namespace, + package='image_transport', + executable='republish', + remappings=[ + ('in/compressed', in_compressed), + ('out', out_raw), + ], + arguments=['compressed', 'raw'], + ) + + ld = LaunchDescription() + ld.add_action(arg_namespace) + ld.add_action(arg_in_compressed) + ld.add_action(arg_out_raw) + ld.add_action(compressed_transport_node) + return ld diff --git a/rbs_utils/rbs_utils/launch/image_raw_to_compressed.launch.py b/rbs_utils/rbs_utils/launch/image_raw_to_compressed.launch.py new file mode 100644 index 0000000..2e99fbb --- /dev/null +++ b/rbs_utils/rbs_utils/launch/image_raw_to_compressed.launch.py @@ -0,0 +1,76 @@ +""" + https://github.com/clearpathrobotics/clearpath_robot + +# Software License Agreement (BSD) +# +# @author Roni Kreinin +# @copyright (c) 2023, Clearpath Robotics, Inc., All rights reserved. +# +# Redistribution and use in source and binary forms, with or without +# modification, are permitted provided that the following conditions are met: +# * Redistributions of source code must retain the above copyright notice, +# this list of conditions and the following disclaimer. +# * Redistributions in binary form must reproduce the above copyright notice, +# this list of conditions and the following disclaimer in the documentation +# and/or other materials provided with the distribution. +# * Neither the name of Clearpath Robotics nor the names of its contributors +# may be used to endorse or promote products derived from this software +# without specific prior written permission. +# +# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE +# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR +# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF +# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS +# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN +# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) +# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE +# POSSIBILITY OF SUCH DAMAGE. +""" + +from launch import LaunchDescription +from launch.actions import DeclareLaunchArgument +from launch.substitutions import LaunchConfiguration +from launch_ros.actions import Node + + +def generate_launch_description(): + namespace = LaunchConfiguration('namespace') + in_raw = LaunchConfiguration('in_raw') + out_compressed = LaunchConfiguration('out_compressed') + + arg_namespace = DeclareLaunchArgument( + 'namespace', + default_value='' + ) + + arg_in_raw = DeclareLaunchArgument( + 'in_raw', + default_value='image' + ) + + arg_out_compressed = DeclareLaunchArgument( + 'out_compressed', + default_value='compressed' + ) + + compressed_transport_node = Node( + name='image_raw_to_compressed', + namespace=namespace, + package='image_transport', + executable='republish', + remappings=[ + ('in', in_raw), + ('out/compressed', out_compressed), + ], + arguments=['raw', 'compressed'], + ) + + ld = LaunchDescription() + ld.add_action(arg_namespace) + ld.add_action(arg_in_raw) + ld.add_action(arg_out_compressed) + ld.add_action(compressed_transport_node) + return ld diff --git a/rbs_utils/rbs_utils/package.nix b/rbs_utils/rbs_utils/package.nix new file mode 100644 index 0000000..6ce88e1 --- /dev/null +++ b/rbs_utils/rbs_utils/package.nix @@ -0,0 +1,23 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 + +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license + +{ lib, buildRosPackage, ament-cmake, ament-lint-auto, ament-lint-common, geometry-msgs, nlohmann_json, rbs-utils-interfaces, rclcpp, rclcpp-lifecycle, rclpy, rosbag2-cpp, rosidl-default-generators, rviz-visual-tools, sensor-msgs, std-msgs, tf2-eigen, tf2-ros }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-utils"; + version = "0.0.0"; + + src = ./.; + + buildType = "ament_cmake"; + buildInputs = [ ament-cmake ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ geometry-msgs nlohmann_json rbs-utils-interfaces rclcpp rclcpp-lifecycle rclpy rosbag2-cpp rosidl-default-generators rviz-visual-tools sensor-msgs std-msgs tf2-eigen tf2-ros ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/rbs_utils/rbs_utils/package.xml b/rbs_utils/rbs_utils/package.xml index 4aa08d4..315054e 100644 --- a/rbs_utils/rbs_utils/package.xml +++ b/rbs_utils/rbs_utils/package.xml @@ -8,6 +8,7 @@ Apache-2.0 ament_cmake + ament_cmake_python rclpy rclcpp @@ -19,10 +20,11 @@ rosidl_default_generators std_msgs rbs_utils_interfaces - dynmsg sensor_msgs nlohmann-json-dev rosbag2_cpp + image_transport + controller_manager_msgs ament_lint_auto ament_lint_common diff --git a/rbs_utils/rbs_utils/rbs_utils/launch.py b/rbs_utils/rbs_utils/rbs_utils/launch.py new file mode 100644 index 0000000..7960199 --- /dev/null +++ b/rbs_utils/rbs_utils/rbs_utils/launch.py @@ -0,0 +1,28 @@ +import yaml +from launch.substitutions import LaunchConfiguration + +def param_constructor(loader, node, local_vars): + value = loader.construct_scalar(node) + return LaunchConfiguration(value).perform( + local_vars.get("context", "Launch context if not defined") + ) + +def variable_constructor(loader, node, local_vars): + value = loader.construct_scalar(node) + return local_vars.get(value, f"Variable '{value}' not found") + +def load_xacro_args(yaml_file, local_vars): + # Get valut from ros2 argument + yaml.add_constructor( + "!param", lambda loader, node: param_constructor(loader, node, local_vars) + ) + + # Get value from local variable in this code + # The local variable should be initialized before the loader was called + yaml.add_constructor( + "!variable", + lambda loader, node: variable_constructor(loader, node, local_vars), + ) + + with open(yaml_file, "r") as file: + return yaml.load(file, Loader=yaml.FullLoader) diff --git a/rbs_utils/rbs_utils/rbs_utils/recording_demo.py b/rbs_utils/rbs_utils/rbs_utils/recording_demo.py new file mode 100755 index 0000000..6c7c449 --- /dev/null +++ b/rbs_utils/rbs_utils/rbs_utils/recording_demo.py @@ -0,0 +1,176 @@ +#!/usr/bin/env python3 +""" +recording_demo_service_node +ROS 2 program for recording a demo via RosBag + +@shalenikol release 0.1 +""" + +import os +import json +from enum import Enum + +import rclpy +from rclpy.node import Node +from rclpy.action.client import ActionClient +from rbs_skill_interfaces.action import RbsBt +from ament_index_python.packages import get_package_share_directory +from rbs_utils_interfaces.msg import RecorderCommands +from rbs_utils_interfaces.srv import Recorder + + +class CommandType(str, Enum): + RUN = "run" + SAVE_AND_NEXT = "save_and_next" + CANCEL_AND_NEXT = "cancel_and_next" + STOP_AND_SAVE = "stop_and_save" + STOP_AND_CANCEL = "stop_and_cancel" + + +# list of all values +COMMAND_TYPES = [cmd.value for cmd in CommandType] + +SERVER_NAME = "rbs_interface_a" +FILE_TEMPLATE_SKILL = "recording_demo_skill.json" +FILE_SKILL = "skill.json" +KEY_SIDPATH = "@path@" # prefix for filepath + + +class RbsActionClient(Node): + def __init__(self): + self.res_ok = False + self.is_record_run = False + super().__init__("rbs_action_client") + self._action_client = ActionClient(self, RbsBt, SERVER_NAME) + self._recorder_service = self.create_service(Recorder, "recorder", self.recorder) + + def recorder(self, request: Recorder.Request, response: Recorder.Response) -> Recorder.Response: + # response.ok = recording_demo(request.command.command) + response.ok = False + if request.command.command == RecorderCommands.RUN and not self.is_record_run: + response.ok = recording_demo(CommandType.RUN) + self.is_record_run = response.ok + + elif request.command.command == RecorderCommands.SAVE_AND_NEXT and self.is_record_run: + response.ok = recording_demo(CommandType.SAVE_AND_NEXT) + + elif request.command.command == RecorderCommands.CANCEL_AND_NEXT and self.is_record_run: + response.ok = recording_demo(CommandType.CANCEL_AND_NEXT) + self.is_record_run = response.ok + + elif request.command.command == RecorderCommands.STOP_AND_SAVE and self.is_record_run: + response.ok = recording_demo(CommandType.STOP_AND_SAVE) + if response.ok: + self.is_record_run = False + + elif request.command.command == RecorderCommands.STOP_AND_CANCEL and self.is_record_run: + response.ok = recording_demo(CommandType.STOP_AND_CANCEL) + if response.ok: + self.is_record_run = False + + return response + + def send_goal(self, sid: str, action: str, command: str): + self.res_ok = False + self.get_logger().info("Waiting for action server...") + self._action_client.wait_for_server() + + goal_msg = RbsBt.Goal() + goal_msg.sid = sid + goal_msg.action = action + goal_msg.command = command + + self.get_logger().info( + f"Sending goal: sid={sid}, action={action}, command={command}" + ) + send_goal_future = self._action_client.send_goal_async( + goal_msg, feedback_callback=self.feedback_callback + ) + + rclpy.spin_until_future_complete(self, send_goal_future) + goal_handle = send_goal_future.result() + + if not goal_handle.accepted: + self.get_logger().warn("Goal rejected") + return + + self.get_logger().info("Goal accepted, waiting for result...") + get_result_future = goal_handle.get_result_async() + rclpy.spin_until_future_complete(self, get_result_future) + result = get_result_future.result().result + + self.res_ok = result.ok + + if self.res_ok: + self.get_logger().info("Result: SUCCESS") + else: + self.get_logger().error("Result: FAILURE") + + def feedback_callback(self, feedback_msg): + feedback = feedback_msg.feedback + self.get_logger().info(f"Received feedback: {feedback}") + + +def get_config_path() -> str: + return os.path.join(get_package_share_directory("rbs_utils"), "config") + + +def get_config_file() -> str: + return os.path.join(get_config_path(), FILE_TEMPLATE_SKILL) + + +def recording_demo(command: CommandType = CommandType.RUN) -> bool: + if command not in COMMAND_TYPES: + return False + + # read template of skill description ("RecordingDemo") + with open(get_config_file(), "r") as f: + cfg = json.load(f) + + file_skill = os.path.join(get_config_path(), FILE_SKILL) + sid = KEY_SIDPATH + file_skill + rec_demo = cfg["skills"][0] + rec_demo["sid"] = sid + if not command == CommandType.RUN: + for act in rec_demo["BTAction"]: + if act["name"] == "rdStop": + act["param"] = [ + {"type": "formBuilder", "dependency": {"output": {"do": command}}} + ] + + # write params of skill description + with open(file_skill, "w") as f: + json.dump(cfg, f, indent=2, ensure_ascii=False) + + ret = False + action_client = RbsActionClient() + + if command == CommandType.RUN: + action_client.send_goal(sid=sid, action="RecordingDemo", command="rdConfigure") + elif command in [CommandType.SAVE_AND_NEXT, CommandType.CANCEL_AND_NEXT]: + action_client.send_goal(sid=sid, action="RecordingDemo", command="rdStop") + if action_client.res_ok: + action_client.send_goal( + sid=sid, action="RecordingDemo", command="rdConfigure" + ) + else: # command in [CommandType.STOP_AND_CANCEL, CommandType.STOP_AND_SAVE]: + action_client.send_goal(sid=sid, action="RecordingDemo", command="rdStop") + + ret = action_client.res_ok + return ret + + +def main(): + rclpy.init() + + executor = rclpy.executors.SingleThreadedExecutor() + lc_node = RbsActionClient() + executor.add_node(lc_node) + try: + executor.spin() + except (KeyboardInterrupt, rclpy.executors.ExternalShutdownException): + lc_node.destroy_node() + + +if __name__ == "__main__": + main() diff --git a/rbs_utils/rbs_utils/scripts/assembly_config_service.py b/rbs_utils/rbs_utils/scripts/assembly_config_service.py index ce92375..03a65d2 100755 --- a/rbs_utils/rbs_utils/scripts/assembly_config_service.py +++ b/rbs_utils/rbs_utils/scripts/assembly_config_service.py @@ -36,7 +36,7 @@ class AssemblyConfigService(Node): self.tf2_listner = Tf2Listener(self) for relative_part in self.assembly_config.relative_part: tf2_broadcaster.broadcast_tf( - relative_part.relative_at, + relative_part.relative_to, relative_part.name, translation=( relative_part.pose.position.x, @@ -53,7 +53,7 @@ class AssemblyConfigService(Node): for grasp_poses in self.assembly_config.grasp_poses: tf2_broadcaster.broadcast_tf( - grasp_poses.relative_at, + grasp_poses.relative_to, grasp_poses.name, translation=( grasp_poses.pose.position.x, @@ -70,7 +70,7 @@ class AssemblyConfigService(Node): for place_poses in self.assembly_config.place_poses: tf2_broadcaster.broadcast_tf( - place_poses.relative_at, + place_poses.relative_to, place_poses.name, translation=( place_poses.pose.position.x, @@ -333,7 +333,7 @@ def parse_assembly_config(yaml_file): pose = Pose(position=Point(**position), orientation=Quaternion(**orientation)) relative_part.append( RelativeNamedPose( - name=part["name"], relative_at=part["relative_at"], pose=pose + name=part["name"], relative_to=part["relative_to"], pose=pose ) ) @@ -348,7 +348,7 @@ def parse_assembly_config(yaml_file): ) grasp_pose.append( RelativeNamedPose( - name=pose["name"], relative_at=pose["relative_at"], pose=pose_obj + name=pose["name"], relative_to=pose["relative_to"], pose=pose_obj ) ) @@ -374,7 +374,7 @@ def parse_assembly_config(yaml_file): ) place_poses.append( RelativeNamedPose( - name=pose["name"], relative_at=pose["relative_at"], pose=pose_obj + name=pose["name"], relative_to=pose["relative_to"], pose=pose_obj ) ) diff --git a/rbs_utils/rbs_utils/scripts/example_recording_demo.py b/rbs_utils/rbs_utils/scripts/example_recording_demo.py new file mode 100644 index 0000000..1e8e2d0 --- /dev/null +++ b/rbs_utils/rbs_utils/scripts/example_recording_demo.py @@ -0,0 +1,19 @@ +#!/usr/bin/env python3 +""" + Example of using demo recording to rosbag + ```bash + ros2 run rbs_utils example_recording_demo.py + + @shalenikol release 0.1 +""" +from rbs_utils.recording_demo import recording_demo, CommandType + +if __name__ == '__main__': + res = recording_demo() # default: CommandType.RUN + print(f"{res=}") + res = recording_demo(CommandType.SAVE_AND_NEXT) + print(f"{res=}") + res = recording_demo(CommandType.CANCEL_AND_NEXT) + print(f"{res=}") + res = recording_demo(CommandType.STOP_AND_SAVE) + print(f"{res=}") diff --git a/rbs_utils/rbs_utils/scripts/recording_demo_via_rosbag.py b/rbs_utils/rbs_utils/scripts/recording_demo_via_rosbag.py index 03f07ca..812a5e3 100755 --- a/rbs_utils/rbs_utils/scripts/recording_demo_via_rosbag.py +++ b/rbs_utils/rbs_utils/scripts/recording_demo_via_rosbag.py @@ -4,7 +4,7 @@ ROS 2 program for recording a demo via RosBag @shalenikol release 0.3 - !!! In "Humble" writer.close() not worked !!! Waiting "Jazzy" + @shalenikol release 0.4 In "Jazzy" writer.close() """ import os import shutil @@ -16,19 +16,26 @@ from rclpy.lifecycle import Node from rclpy.lifecycle import State from rclpy.lifecycle import TransitionCallbackReturn -import rosbag2_py +import rosbag2_py # 0.26.7 (jazzy) from ros2topic.api import get_topic_names_and_types from rclpy.serialization import serialize_message -from sensor_msgs.msg import Image, JointState +from sensor_msgs.msg import JointState, Image, CompressedImage + +from rbs_utils.recording_demo import CommandType + +#'get_type_description': 'type_description_interfaces/srv/GetTypeDescription' NODE_NAME_DEFAULT = "lc_record_demo" PARAM_SKILL_CFG = "lc_record_demo_cfg" OUTPUT_PATH_DEFAULT = "rbs_bag" +RECORD_PATH = "episode" WRITER_ID = "sqlite3" -TOPIC_TYPES = ["sensor_msgs/msg/JointState", "sensor_msgs/msg/Image"] -TOPIC_CLASSES = [JointState, Image] +TOPIC_FILTERS = { + "sensor_msgs/msg/JointState": JointState, + "sensor_msgs/msg/Image": Image, +} class RecordingDemo(Node): """ lifecycle node """ @@ -38,6 +45,8 @@ class RecordingDemo(Node): self.topics = [] self._sub = [] self.output_path = OUTPUT_PATH_DEFAULT + self.compressed = "False" # default: not compressed image + self.serialization = "cdr" # default serialization format # for other nodes kwargs["allow_undeclared_parameters"] = True @@ -48,46 +57,73 @@ class RecordingDemo(Node): self.skill_cfg = json.loads(str_cfg) sets = self.skill_cfg["Settings"]["output"]["params"] for s in sets: - if s["name"] == "output_path": - self.output_path = s["value"] + nam = s["name"] + val = s["value"] + if nam == "output_path": + self.output_path = val + elif nam == "compressed": + self.compressed = val + elif nam == "serialization": + self.serialization = val + + if self.compressed == "True": + del TOPIC_FILTERS["sensor_msgs/msg/Image"] + TOPIC_FILTERS["sensor_msgs/msg/CompressedImage"] = CompressedImage def get_list_topics(self) -> list: topic_names_and_types = get_topic_names_and_types(node=self, include_hidden_topics=False) topic_list = [] - for (topic_name, topic_types) in topic_names_and_types: - if topic_types[0] in TOPIC_TYPES: - i = TOPIC_TYPES.index(topic_types[0]) - topic_list.append({"name": topic_name, "type": topic_types[0], "class": TOPIC_CLASSES[i]}) + for topic_name, topic_types in topic_names_and_types: + topic_type = topic_types[0] + if topic_type in TOPIC_FILTERS: + topic_list.append({ + "name": topic_name, + "type": topic_type, + "class": TOPIC_FILTERS[topic_type], + }) return topic_list - def check_output_folder(self, path: str) -> None: + def init_output_folder(self, path: str) -> str: # check for output folder existence - if os.path.isdir(path): + if not os.path.isdir(path): + os.makedirs(path) + rec_folder = os.path.join(path, RECORD_PATH) + + if os.path.isdir(rec_folder): + shutil.rmtree(rec_folder) + return rec_folder + + def save_episode(self) -> None: + if os.path.isdir(self.rec_folder): x = 1 - while os.path.isdir(path + str(x)): + while os.path.isdir(self.rec_folder + str(x)): x += 1 - shutil.move(path, path + str(x)) + shutil.move(self.rec_folder, self.rec_folder + str(x)) def on_configure(self, state: State) -> TransitionCallbackReturn: - self.check_output_folder(self.output_path) + self.rec_folder = self.init_output_folder(self.output_path) self.writer = rosbag2_py.SequentialWriter() - storage_options = rosbag2_py._storage.StorageOptions(uri=self.output_path, storage_id=WRITER_ID) - converter_options = rosbag2_py._storage.ConverterOptions("", "") + storage_options = rosbag2_py.StorageOptions(uri=self.rec_folder, storage_id=WRITER_ID) + converter_options = rosbag2_py.ConverterOptions("", "") self.writer.open(storage_options, converter_options) - + self.topics = self.get_list_topics() for id, topic in enumerate(self.topics): - topic_info = rosbag2_py._storage.TopicMetadata( + # for type_hash + pub_infos = self.get_publishers_info_by_topic(topic["name"]) + topic_info = rosbag2_py.TopicMetadata( + id, name=topic["name"], type=topic["type"], - serialization_format="cdr") + serialization_format=self.serialization, + type_description_hash=str(pub_infos[0].topic_type_hash)) self.writer.create_topic(topic_info) - self.get_logger().info(f"on_configure: {id}) {topic}") + self.get_logger().info(f"Topics: {id+1}) {topic}") - # self.get_logger().info("on_configure() is called.") + self.get_logger().info("on_configure() is called.") return TransitionCallbackReturn.SUCCESS def on_activate(self, state: State) -> TransitionCallbackReturn: @@ -117,10 +153,24 @@ class RecordingDemo(Node): self.destroy_subscription(sub) self._sub.clear() - # self.writer.close() # / del self.writer + self.writer.close() + + do_param = CommandType.STOP_AND_SAVE # default + + json_param = self.get_parameter(PARAM_SKILL_CFG).get_parameter_value().string_value + self.skill_cfg = json.loads(json_param) + for comm in self.skill_cfg["BTAction"]: + if comm["name"] == "rdStop": + for par in comm["param"]: + if par["type"] == "formBuilder": + do_param = par["dependency"]["output"]["do"] + + if do_param in [CommandType.STOP_AND_SAVE, CommandType.SAVE_AND_NEXT]: + self.save_episode() + elif do_param == CommandType.STOP_AND_CANCEL: + shutil.rmtree(self.rec_folder) self.get_logger().info("on_cleanup() is called") - self.timer = self.create_timer(0.01, self.timer_callback) return TransitionCallbackReturn.SUCCESS def on_shutdown(self, state: State) -> TransitionCallbackReturn: @@ -137,14 +187,6 @@ class RecordingDemo(Node): serialize_message(msg), self.get_clock().now().nanoseconds) - def timer_callback(self): - self.get_logger().info("Restarting node..") - self.destroy_node() - rclpy.shutdown() - rclpy.init() - lc_node = RecordingDemo() - rclpy.spin(lc_node) - def main(): rclpy.init() diff --git a/rbs_utils/rbs_utils/src/bagfile_recorder.cpp b/rbs_utils/rbs_utils/src/bagfile_recorder.cpp index 94b9739..19b35d3 100644 --- a/rbs_utils/rbs_utils/src/bagfile_recorder.cpp +++ b/rbs_utils/rbs_utils/src/bagfile_recorder.cpp @@ -69,9 +69,7 @@ protected: topics_ = get_list_topics(); for (const auto &topic_name : topics_) { - writer_->create_topic({topic_name, "sensor_msgs/msg/Image", "cdr", ""}); - RCLCPP_INFO(this->get_logger(), "Configuring topic: %s", - topic_name.c_str()); + writer_->create_topic({0u, topic_name, "sensor_msgs/msg/Image", "", {}, ""}); } return CallbackReturn::SUCCESS; } diff --git a/rbs_utils/rbs_utils/src/rbs_utils.cpp b/rbs_utils/rbs_utils/src/rbs_utils.cpp deleted file mode 100644 index 5d84828..0000000 --- a/rbs_utils/rbs_utils/src/rbs_utils.cpp +++ /dev/null @@ -1,297 +0,0 @@ -#include "rbs_utils/rbs_utils.hpp" -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include - -namespace rbs_utils { -AssemblyConfigLoader::AssemblyConfigLoader( - const std::string &t_assembly_dir, - const rclcpp::node_interfaces::NodeLoggingInterface::SharedPtr - &t_logging_interface, - const rclcpp::node_interfaces::NodeClockInterface::SharedPtr - &t_clock_interface) - : m_assembly_dir(t_assembly_dir), - m_logger(t_logging_interface->get_logger()), - m_clock(t_clock_interface->get_clock()) { - if (!m_assembly_dir.empty()) { - std::vector filenames = {"rbs_db"}; - for (auto &filename : filenames) { - std::string filepath = - env_dir + "/" + m_assembly_dir + "/" + filename + ".yaml"; - - m_env_files.push_back(filepath); - parseRbsDb(filepath); - } - } else { - RCLCPP_ERROR(m_logger, "Assembly dir is not set"); - } -} - -void AssemblyConfigLoader::parseRbsDb(const std::string &filepath) { - try { - YAML::Node asm_config = YAML::LoadFile(filepath); - std::string asm_config_string = dynmsg::yaml_to_string(asm_config); - - RosMessage_Cpp rosmsg; - InterfaceTypeName interface{"rbs_utils_interfaces", "AssemblyConfig"}; - rosmsg.type_info = dynmsg::cpp::get_type_info(interface); - - void *ros_msg = reinterpret_cast(&m_assembly_config); - dynmsg::cpp::yaml_and_typeinfo_to_rosmsg(rosmsg.type_info, - asm_config_string, ros_msg); - - } catch (const std::exception &e) { - RCLCPP_ERROR(m_logger, "Exception reading file %s: %s", filepath.c_str(), - e.what()); - } -} - -[[deprecated("Not Implemented")]] void AssemblyConfigLoader::saveRbsConfig() {} - -std::vector AssemblyConfigLoader::getUniqueSceneModelNames() { - std::vector model_names; - if (m_assembly_config.relative_part.size() != 0) { - for (auto &t : m_assembly_config.relative_part) { - model_names.push_back(t.name); - } - } else { - return model_names; - } - // Sort and remove duplicates - std::sort(model_names.begin(), model_names.end()); - model_names.erase(std::unique(model_names.begin(), model_names.end()), - model_names.end()); - - return model_names; -} - -tf2_msgs::msg::TFMessage AssemblyConfigLoader::getAllPossibleTfData() { - tf2_msgs::msg::TFMessage tp; - // Get absolute parts - for (auto &abs_poses : m_assembly_config.absolute_part) { - geometry_msgs::msg::TransformStamped tmp; - tmp.transform = createTransform(abs_poses.pose); - tmp.child_frame_id = abs_poses.name; - tmp.header.frame_id = "world"; - tmp.header.stamp = m_clock->now(); - tp.transforms.push_back(tmp); - } - // Get relative parts - for (const auto &relative_part : m_assembly_config.relative_part) { - geometry_msgs::msg::TransformStamped tmp; - tmp.transform = createTransform(relative_part.pose); - tmp.child_frame_id = relative_part.name; - tmp.header.frame_id = relative_part.relative_at; - tmp.header.stamp = m_clock->now(); - tp.transforms.push_back(tmp); - RCLCPP_INFO(m_logger, "Model name [%s]", relative_part.name.c_str()); - } - // Get grasp poses - for (const auto &grasp_pose : m_assembly_config.grasp_poses) { - geometry_msgs::msg::TransformStamped tmp; - tmp.transform = createTransform(grasp_pose.pose); - tmp.child_frame_id = grasp_pose.name; - tmp.header.frame_id = grasp_pose.relative_at; - tmp.header.stamp = m_clock->now(); - tp.transforms.push_back(tmp); - } - - return tp; -} - -tf2_msgs::msg::TFMessage -AssemblyConfigLoader::getGraspTfData(const std::string &model_name) { - tf2_msgs::msg::TFMessage tp; - - bool found_grasp_pose = false; - if (!m_assembly_config.relative_part.empty()) { - for (auto &abs_poses : m_assembly_config.absolute_part) { - geometry_msgs::msg::TransformStamped tmp; - tmp.transform = createTransform(abs_poses.pose); - tmp.child_frame_id = abs_poses.name; - tmp.header.frame_id = "world"; - tmp.header.stamp = m_clock->now(); - tp.transforms.push_back(tmp); - } - } else { - RCLCPP_ERROR(m_logger, "Relative parts is empty size: %zu", - m_assembly_config.relative_part.size()); - } - - for (const auto &grasp_pose : m_assembly_config.grasp_poses) { - if (grasp_pose.relative_at == model_name) { - geometry_msgs::msg::TransformStamped tmp; - tmp.transform = createTransform(grasp_pose.pose); - tmp.child_frame_id = grasp_pose.name; - tmp.header.frame_id = grasp_pose.relative_at; - tmp.header.stamp = m_clock->now(); - tp.transforms.push_back(tmp); - found_grasp_pose = true; - } - } - - if (!found_grasp_pose) { - RCLCPP_ERROR(m_logger, "Grasp pose not found for model %s", - model_name.c_str()); - } - - return tp; - -} - -tf2_msgs::msg::TFMessage -AssemblyConfigLoader::getTfData(const std::string &model_name) { - tf2_msgs::msg::TFMessage tp; - - if (!m_assembly_config.absolute_part.empty()) { - for (auto &abs_part : m_assembly_config.absolute_part) { - geometry_msgs::msg::TransformStamped abs_transrorm_stamped; - abs_transrorm_stamped.transform = createTransform(abs_part.pose); - abs_transrorm_stamped.child_frame_id = abs_part.name; - abs_transrorm_stamped.header.frame_id = "world"; - abs_transrorm_stamped.header.stamp = m_clock->now(); - tp.transforms.push_back(abs_transrorm_stamped); - } - } else { - RCLCPP_ERROR(m_logger, "Absolute parts is empty size: %zu", - m_assembly_config.absolute_part.size()); - } - - bool found_model = false; - bool found_grasp_pose = false; - if (!m_assembly_config.relative_part.empty()) { - for (auto &abs_poses : m_assembly_config.absolute_part) { - geometry_msgs::msg::TransformStamped tmp; - tmp.transform = createTransform(abs_poses.pose); - tmp.child_frame_id = abs_poses.name; - tmp.header.frame_id = "world"; - tmp.header.stamp = m_clock->now(); - tp.transforms.push_back(tmp); - } - - for (const auto &relative_part : m_assembly_config.relative_part) { - // Find our model data - if (relative_part.name == model_name) { - geometry_msgs::msg::TransformStamped tmp; - tmp.transform = createTransform(relative_part.pose); - tmp.child_frame_id = relative_part.name; - tmp.header.frame_id = relative_part.relative_at; - tmp.header.stamp = m_clock->now(); - tp.transforms.push_back(tmp); - found_model = true; - } - RCLCPP_INFO(m_logger, "Model name [%s]", - relative_part.relative_at.c_str()); - } - } else { - RCLCPP_ERROR(m_logger, "Relative parts is empty size: %zu", - m_assembly_config.relative_part.size()); - } - - for (const auto &grasp_pose : m_assembly_config.grasp_poses) { - if (grasp_pose.relative_at == model_name) { - geometry_msgs::msg::TransformStamped tmp; - tmp.transform = createTransform(grasp_pose.pose); - tmp.child_frame_id = grasp_pose.name; - tmp.header.frame_id = grasp_pose.relative_at; - tmp.header.stamp = m_clock->now(); - tp.transforms.push_back(tmp); - found_grasp_pose = true; - } - } - - if (!found_model) { - RCLCPP_ERROR(m_logger, "Model %s not found in config", model_name.c_str()); - } - if (!found_grasp_pose) { - RCLCPP_ERROR(m_logger, "Grasp pose not found for model %s", - model_name.c_str()); - } - - return tp; -} - -geometry_msgs::msg::Transform -AssemblyConfigLoader::createTransform(const geometry_msgs::msg::Pose &pose) { - geometry_msgs::msg::Transform transform; - transform.translation.x = pose.position.x; - transform.translation.y = pose.position.y; - transform.translation.z = pose.position.z; - transform.rotation.x = pose.orientation.x; - transform.rotation.y = pose.orientation.y; - transform.rotation.z = pose.orientation.z; - transform.rotation.w = pose.orientation.w; - return transform; -} - -geometry_msgs::msg::PoseArray AssemblyConfigLoader::getWorkspace() { - geometry_msgs::msg::PoseArray pose_array; - pose_array.header.frame_id = "world"; - - if (m_assembly_config.workspace.empty()) { - RCLCPP_WARN(m_logger, "Workspace is empty, check your robossembler_db"); - return pose_array; - } - - pose_array.poses.reserve(m_assembly_config.workspace.size()); - - const double default_rotation_value = 0.0; - const double default_rotation_w = 1.0; - - for (const auto &point : m_assembly_config.workspace) { - geometry_msgs::msg::Pose pose; - pose.position.x = point.x; - pose.position.y = point.y; - pose.position.z = point.z; - pose.orientation.x = default_rotation_value; - pose.orientation.y = default_rotation_value; - pose.orientation.z = default_rotation_value; - pose.orientation.w = default_rotation_w; - pose_array.poses.push_back(pose); - } - - return pose_array; -} - -geometry_msgs::msg::PoseArray -AssemblyConfigLoader::getWorkspaceInspectorTrajectory() { - geometry_msgs::msg::PoseArray pose_array; - pose_array.header.frame_id = "world"; - - auto workspace_poses = getWorkspace(); - - for (const auto &pose : workspace_poses.poses) { - pose_array.poses.push_back(transformTrajectory(pose)); - } - - return pose_array; -} - -geometry_msgs::msg::Pose AssemblyConfigLoader::transformTrajectory( - const geometry_msgs::msg::Pose &pose) { - Eigen::Isometry3d pose_eigen; - tf2::fromMsg(pose, pose_eigen); - - Eigen::AngleAxisd rotation(M_PI, Eigen::Vector3d::UnitY()); - pose_eigen.rotate(rotation); - pose_eigen.translation().z() += 0.35; - return tf2::toMsg(pose_eigen); -} - -} // namespace rbs_utils diff --git a/rbs_utils/rbs_utils_interfaces/CMakeLists.txt b/rbs_utils/rbs_utils_interfaces/CMakeLists.txt index 2c90a56..8f4e748 100644 --- a/rbs_utils/rbs_utils_interfaces/CMakeLists.txt +++ b/rbs_utils/rbs_utils_interfaces/CMakeLists.txt @@ -15,15 +15,18 @@ rosidl_generate_interfaces(${PROJECT_NAME} "msg/AssemblyConfig.msg" "msg/NamedPose.msg" "msg/RelativeNamedPose.msg" + "msg/RecorderCommands.msg" "srv/GetGraspPose.srv" "srv/GetPlacePose.srv" + "srv/GetRelativeNamedPose.srv" "srv/GetWorkspace.srv" + "srv/GetNamedPose.srv" + "srv/AddTasks.srv" + "srv/TaskFromQueue.srv" + "srv/Recorder.srv" DEPENDENCIES std_msgs geometry_msgs ) - - - if(BUILD_TESTING) find_package(ament_lint_auto REQUIRED) diff --git a/rbs_utils/rbs_utils_interfaces/msg/RecorderCommands.msg b/rbs_utils/rbs_utils_interfaces/msg/RecorderCommands.msg new file mode 100644 index 0000000..1a52562 --- /dev/null +++ b/rbs_utils/rbs_utils_interfaces/msg/RecorderCommands.msg @@ -0,0 +1,6 @@ +string RUN = "run" +string SAVE_AND_NEXT = "save_and_next" +string CANCEL_AND_NEXT = "cancel_and_next" +string STOP_AND_SAVE = "stop_and_save" +string STOP_AND_CANCEL = "stop_and_cancel" +string command diff --git a/rbs_utils/rbs_utils_interfaces/msg/RelativeNamedPose.msg b/rbs_utils/rbs_utils_interfaces/msg/RelativeNamedPose.msg index f83c1a3..0205231 100644 --- a/rbs_utils/rbs_utils_interfaces/msg/RelativeNamedPose.msg +++ b/rbs_utils/rbs_utils_interfaces/msg/RelativeNamedPose.msg @@ -1,3 +1,3 @@ string name -string relative_at +string relative_to "world" geometry_msgs/Pose pose diff --git a/rbs_utils/rbs_utils_interfaces/package.nix b/rbs_utils/rbs_utils_interfaces/package.nix new file mode 100644 index 0000000..9006cb6 --- /dev/null +++ b/rbs_utils/rbs_utils_interfaces/package.nix @@ -0,0 +1,22 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 + +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license + +{ lib, buildRosPackage, ament-cmake, geometry-msgs, rosidl-default-generators, rosidl-default-runtime }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-utils-interfaces"; + version = "0.0.0"; + + src = ./.; + + buildType = "ament_cmake"; + buildInputs = [ ament-cmake rosidl-default-generators ]; + propagatedBuildInputs = [ geometry-msgs rosidl-default-runtime ]; + nativeBuildInputs = [ ament-cmake rosidl-default-generators ]; + + meta = { + description = "Interfaces for read robossembler_db config"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/rbs_utils/rbs_utils_interfaces/srv/AddTasks.srv b/rbs_utils/rbs_utils_interfaces/srv/AddTasks.srv new file mode 100644 index 0000000..d4a8f28 --- /dev/null +++ b/rbs_utils/rbs_utils_interfaces/srv/AddTasks.srv @@ -0,0 +1,3 @@ +string tasks_csv +--- +bool ok \ No newline at end of file diff --git a/rbs_utils/rbs_utils_interfaces/srv/GetNamedPose.srv b/rbs_utils/rbs_utils_interfaces/srv/GetNamedPose.srv new file mode 100644 index 0000000..a5ce997 --- /dev/null +++ b/rbs_utils/rbs_utils_interfaces/srv/GetNamedPose.srv @@ -0,0 +1,4 @@ +string pose_name +--- +rbs_utils_interfaces/NamedPose named_pose +bool ok diff --git a/rbs_utils/rbs_utils_interfaces/srv/GetRelativeNamedPose.srv b/rbs_utils/rbs_utils_interfaces/srv/GetRelativeNamedPose.srv new file mode 100644 index 0000000..928d7df --- /dev/null +++ b/rbs_utils/rbs_utils_interfaces/srv/GetRelativeNamedPose.srv @@ -0,0 +1,5 @@ +string pose_name +string relative_to "world" +--- +rbs_utils_interfaces/RelativeNamedPose named_pose +bool ok diff --git a/rbs_utils/rbs_utils_interfaces/srv/Recorder.srv b/rbs_utils/rbs_utils_interfaces/srv/Recorder.srv new file mode 100644 index 0000000..c1563e5 --- /dev/null +++ b/rbs_utils/rbs_utils_interfaces/srv/Recorder.srv @@ -0,0 +1,3 @@ +rbs_utils_interfaces/RecorderCommands command +--- +bool ok diff --git a/rbs_utils/rbs_utils_interfaces/srv/TaskFromQueue.srv b/rbs_utils/rbs_utils_interfaces/srv/TaskFromQueue.srv new file mode 100644 index 0000000..f60e94f --- /dev/null +++ b/rbs_utils/rbs_utils_interfaces/srv/TaskFromQueue.srv @@ -0,0 +1,4 @@ +string mode +--- +bool ok +string task \ No newline at end of file diff --git a/rbss_aruco_pe/CMakeLists.txt b/rbss_aruco_pe/CMakeLists.txt new file mode 100644 index 0000000..baf23e3 --- /dev/null +++ b/rbss_aruco_pe/CMakeLists.txt @@ -0,0 +1,51 @@ +cmake_minimum_required(VERSION 3.8) +project(rbss_aruco_pe) + +# Default to C++17 +if(NOT CMAKE_CXX_STANDARD) + set(CMAKE_CXX_STANDARD 17) +endif() + +if(CMAKE_COMPILER_IS_GNUCXX OR CMAKE_CXX_COMPILER_ID MATCHES "Clang") + add_compile_options(-Wall -Wextra -Wpedantic) +endif() + +# Find dependencies +find_package(ament_cmake REQUIRED) +find_package(ament_cmake_python REQUIRED) +find_package(rclpy REQUIRED) +#find_package(open3d REQUIRED) +#find_package(numpy REQUIRED) +#find_package(cv2 REQUIRED) +#find_package(cv_bridge REQUIRED) +#find_package(tf_transformations REQUIRED) +find_package(rbs_skill_interfaces REQUIRED) + +# Install Python modules +ament_python_install_package(${PROJECT_NAME}) + +# Install Python executables +install(PROGRAMS + scripts/aruco_node_lc.py + DESTINATION lib/${PROJECT_NAME} +) + +# Install directories +install(DIRECTORY + launch config + DESTINATION share/${PROJECT_NAME} +) + +if(BUILD_TESTING) + find_package(ament_lint_auto REQUIRED) + # the following line skips the linter which checks for copyrights + # comment the line when a copyright and license is added to all source files + set(ament_cmake_copyright_FOUND TRUE) + # the following line skips cpplint (only works in a git repo) + # comment the line when this package is in a git repo and when + # a copyright and license is added to all source files + set(ament_cmake_cpplint_FOUND TRUE) + ament_lint_auto_find_test_dependencies() +endif() + +ament_package() \ No newline at end of file diff --git a/rbss_aruco_pe/config/aruco_parameters.yaml b/rbss_aruco_pe/config/aruco_parameters.yaml new file mode 100644 index 0000000..c49c494 --- /dev/null +++ b/rbss_aruco_pe/config/aruco_parameters.yaml @@ -0,0 +1,15 @@ +/aruco_node: + ros__parameters: + # Aruco detection parameters + marker_size: 0.04 # Size of the markers in meters + aruco_dictionary_id: DICT_6X6_50 # Aruco dictionary type + # Input topics + image_topic: /rgbd_camera/image/image # Input image topic + use_depth_input: false # Use depth image for 3D pose estimation + depth_image_topic: /camera/aligned_depth_to_color/image_raw # Input depth image topic + camera_info_topic: /rgbd_camera/image/camera_info # Input camera info topic with camera intrinsic parameters + camera_frame: camera_color_optical_frame # Camera link frame of reference + # Output topics + detected_markers_topic: /aruco/markers # Output topic with detected markers (aruco poses + ids) + markers_visualization_topic: /aruco/poses # Output topic with visualization of detected markers as pose array + output_image_topic: /aruco/image # Output topic with visualization of detected markers drawn on image diff --git a/rbss_aruco_pe/launch/rbss_aruco_pe.launch.py b/rbss_aruco_pe/launch/rbss_aruco_pe.launch.py new file mode 100644 index 0000000..43d3d29 --- /dev/null +++ b/rbss_aruco_pe/launch/rbss_aruco_pe.launch.py @@ -0,0 +1,171 @@ +def generate_launch_description(): + print("The skill must be launched via interface node") + return [] + +# # ROS2 imports +# from launch.substitutions import PathJoinSubstitution, LaunchConfiguration +# # from launch.actions import IncludeLaunchDescription +# # from launch.launch_description_sources import PythonLaunchDescriptionSource +# from launch import LaunchDescription +# from launch_ros.actions import Node +# from launch.actions import DeclareLaunchArgument +# # from launch_ros.substitutions import FindPackageShare +# # from launch.conditions import IfCondition, UnlessCondition + +# import os +# from ament_index_python.packages import get_package_share_directory +# import yaml + + +# def generate_launch_description(): + +# aruco_params_file = os.path.join( +# get_package_share_directory('rbss_aruco_pe'), +# 'config', +# 'aruco_parameters.yaml' +# ) + +# with open(aruco_params_file, 'r') as file: +# config = yaml.safe_load(file) + +# config = config["/aruco_node"]["ros__parameters"] + +# # declare configuration parameters +# marker_size_arg = DeclareLaunchArgument( +# name='marker_size', +# default_value=str(config['marker_size']), +# description='Size of the aruco marker in meters', +# ) + +# aruco_dictionary_id_arg = DeclareLaunchArgument( +# name='aruco_dictionary_id', +# default_value=config['aruco_dictionary_id'], +# description='ID of the aruco dictionary to use', +# ) + +# image_topic_arg = DeclareLaunchArgument( +# name='image_topic', +# default_value=config['image_topic'], +# description='Name of the image RGB topic to subscribe to', +# ) + +# use_depth_input_arg = DeclareLaunchArgument( +# name='use_depth_input', +# default_value=str(config['use_depth_input']), +# description='Use depth input for pose estimation', +# choices=['true', 'false', 'True', 'False'] +# ) + +# depth_image_topic_arg = DeclareLaunchArgument( +# name='depth_image_topic', +# default_value=config['depth_image_topic'], +# description='Name of the depth image topic to subscribe to', +# ) + +# camera_info_topic_arg = DeclareLaunchArgument( +# name='camera_info_topic', +# default_value=config['camera_info_topic'], +# description='Name of the camera info topic to subscribe to', +# ) + +# camera_frame_arg = DeclareLaunchArgument( +# name='camera_frame', +# default_value=config['camera_frame'], +# description='Name of the camera frame where the estimated pose will be', +# ) + +# detected_markers_topic_arg = DeclareLaunchArgument( +# name='detected_markers_topic', +# default_value=config['detected_markers_topic'], +# description='Name of the topic to publish the detected markers messages', +# ) + +# markers_visualization_topic_arg = DeclareLaunchArgument( +# name='markers_visualization_topic', +# default_value=config['markers_visualization_topic'], +# description='Name of the topic to publish the pose array for visualization of the markers', +# ) + +# output_image_topic_arg = DeclareLaunchArgument( +# name='output_image_topic', +# default_value=config['output_image_topic'], +# description='Name of the topic to publish the image with the detected markers', +# ) + +# aruco_node = Node( +# package='rbss_aruco_pe', +# executable='aruco_node.py', +# parameters=[{ +# "marker_size": LaunchConfiguration('marker_size'), +# "aruco_dictionary_id": LaunchConfiguration('aruco_dictionary_id'), +# "image_topic": LaunchConfiguration('image_topic'), +# "use_depth_input": LaunchConfiguration('use_depth_input'), +# "depth_image_topic": LaunchConfiguration('depth_image_topic'), +# "camera_info_topic": LaunchConfiguration('camera_info_topic'), +# "camera_frame": LaunchConfiguration('camera_frame'), +# "detected_markers_topic": LaunchConfiguration('detected_markers_topic'), +# "markers_visualization_topic": LaunchConfiguration('markers_visualization_topic'), +# "output_image_topic": LaunchConfiguration('output_image_topic'), +# }], +# output='screen', +# emulate_tty=True +# ) + +# # # launch realsense camera node +# # cam_feed_launch_file = PathJoinSubstitution( +# # [FindPackageShare("realsense2_camera"), "launch", "rs_launch.py"] +# # ) + +# # camera_feed_depth_node = IncludeLaunchDescription( +# # PythonLaunchDescriptionSource(cam_feed_launch_file), +# # launch_arguments={ +# # "pointcloud.enable": "true", +# # "enable_rgbd": "true", +# # "enable_sync": "true", +# # "align_depth.enable": "true", +# # "enable_color": "true", +# # "enable_depth": "true", +# # }.items(), +# # condition=IfCondition(LaunchConfiguration('use_depth_input')) +# # ) + +# # camera_feed_node = IncludeLaunchDescription( +# # PythonLaunchDescriptionSource(cam_feed_launch_file), +# # launch_arguments={ +# # "pointcloud.enable": "true", +# # "enable_color": "true", +# # }.items(), +# # condition=UnlessCondition(LaunchConfiguration('use_depth_input')) +# # ) + +# # rviz_file = PathJoinSubstitution([ +# # FindPackageShare('rbss_aruco_pe'), +# # 'rviz', +# # 'cam_detect.rviz' +# # ]) + +# # rviz2_node = Node( +# # package='rviz2', +# # executable='rviz2', +# # arguments=['-d', rviz_file] +# # ) + +# return LaunchDescription([ +# # Arguments +# marker_size_arg, +# aruco_dictionary_id_arg, +# image_topic_arg, +# use_depth_input_arg, +# depth_image_topic_arg, +# camera_info_topic_arg, +# camera_frame_arg, +# detected_markers_topic_arg, +# markers_visualization_topic_arg, +# output_image_topic_arg, + +# # Nodes +# aruco_node, +# # camera_feed_depth_node, +# # camera_feed_node, +# # rviz2_node +# ]) diff --git a/rbss_aruco_pe/package.xml b/rbss_aruco_pe/package.xml new file mode 100644 index 0000000..09c2a6f --- /dev/null +++ b/rbss_aruco_pe/package.xml @@ -0,0 +1,30 @@ + + + + rbss_aruco_pe + 0.0.1 + Aruco Marker Tracking and Pose Estimation wrapper for ROS2, using RGB cameras + shalenikol + Apache License 2.0 + + ament_cmake + ament_cmake_python + + rclpy + cv_bridge + std_msgs + sensor_msgs + geometry_msgs + lifecycle_msgs + rbs_skill_interfaces + + + tf_transformations + + ament_lint_auto + ament_lint_common + + + ament_cmake + + diff --git a/rbss_aruco_pe/rbs_bt_example.xml b/rbss_aruco_pe/rbs_bt_example.xml new file mode 100644 index 0000000..ff82aef --- /dev/null +++ b/rbss_aruco_pe/rbs_bt_example.xml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/rbss_aruco_pe/rbs_package.json b/rbss_aruco_pe/rbs_package.json new file mode 100644 index 0000000..489a323 --- /dev/null +++ b/rbss_aruco_pe/rbs_package.json @@ -0,0 +1,93 @@ +{ + "skills": [ + { + "sid": "ArucoPE-example", + "SkillPackage": { "name": "Robossembler", "version": "1.0", "format": "1" }, + "Module": { "name": "ArucoPE", "node_name": "aruco_pe", "description": "Aruco Marker Tracking and Pose Estimation wrapper for ROS2, using RGB cameras" }, + "Launch": { "package": "rbss_aruco_pe", "executable": "aruco_node_lc.py" }, + "BTAction": [ + { + "name": "arucoConfig", + "type": "run", + "param": [ + { + "type": "topic", + "dependency": { + "type": "topic", + "topicType": "sensor_msgs/msg/Image", + "topicOut": "/rgbd_camera/image/image" + } + }, + { + "type": "topic", + "dependency": { + "type": "topic", + "topicType": "sensor_msgs/msg/Image", + "topicOut": "/rgbd_camera/image/depth_image" + } + }, + { + "type": "topic", + "dependency": { + "type": "topic", + "topicType": "sensor_msgs/msg/CameraInfo", + "topicOut": "/rgbd_camera/image/camera_info" + } + } + ], + "typeAction": "ACTION" + }, + { "name": "isAruco", "type": "if", "typeAction": "CONDITION", + "param": [ + { + "type": "formBuilder", + "dependency": { + "output": { + "aruco_id": "25" + } + } + } + ] + }, + { "name": "arucoStop", "type": "stop", "param": [], "typeAction": "ACTION" } + ], + "topicsOut": [ + { + "name": "/aruco/markers", + "type": "rbs_skill_interfaces/msg/ArucoMarkers" + }, + { + "name": "/aruco/poses", + "type": "geometry_msgs/msg/PoseArray" + }, + { + "name": "/aruco/image", + "type": "sensor_msgs/msg/Image" + } + ], + "Settings": { + "output": { + "params": [ + { + "name": "is_image_mode", + "value": "True" + }, + { + "name": "aruco_dictionary_id", + "value": "DICT_6X6_50" + }, + { + "name": "marker_size", + "value": "0.04" + }, + { + "name": "camera_frame", + "value": "" + } + ] + }, + "type": "formBuilder" + } + } + ] +} diff --git a/rbss_aruco_pe/rbss_aruco_pe/__init__.py b/rbss_aruco_pe/rbss_aruco_pe/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/rbss_aruco_pe/rbss_aruco_pe/pose_estimation.py b/rbss_aruco_pe/rbss_aruco_pe/pose_estimation.py new file mode 100755 index 0000000..11e00e5 --- /dev/null +++ b/rbss_aruco_pe/rbss_aruco_pe/pose_estimation.py @@ -0,0 +1,264 @@ +#!/usr/bin/env python3 + +# Code taken from: +# https://github.com/AIRLab-POLIMI/ros2-aruco-pose-estimation + +# Code taken and readapted from: +# https://github.com/GSNCodes/ArUCo-Markers-Pose-Estimation-Generation-Python/tree/main + +# Python imports +import numpy as np +import cv2 +import tf_transformations + +# ROS2 imports +from rclpy.impl import rcutils_logger + +# ROS2 message imports +from geometry_msgs.msg import Pose, PoseArray +from rbs_skill_interfaces.msg import ArucoMarkers + +# utils import python code +from rbss_aruco_pe.utils import aruco_display + + +# def pose_estimation(rgb_frame: np.array, depth_frame: np.array, aruco_detector: cv2.aruco.ArucoDetector, marker_size: float, +# matrix_coefficients: np.array, distortion_coefficients: np.array, +# pose_array: PoseArray, markers: ArucoMarkers) -> list[np.array, PoseArray, ArucoMarkers]: +def pose_estimation(rgb_frame: np.array, depth_frame: np.array, aruco_dict, marker_size: float, + matrix_coefficients: np.array, distortion_coefficients: np.array, + pose_array: PoseArray, markers: ArucoMarkers) -> list[np.array, PoseArray, ArucoMarkers]: + ''' + rgb_frame - Frame from the RGB camera stream + depth_frame - Depth frame from the depth camera stream + matrix_coefficients - Intrinsic matrix of the calibrated camera + distortion_coefficients - Distortion coefficients associated with your camera + pose_array - PoseArray message to be published + markers - ArucoMarkers message to be published + + return:- + frame - The frame with the axis drawn on it + pose_array - PoseArray with computed poses of the markers + markers - ArucoMarkers message containing markers id number and pose + ''' + + # old code version + parameters = cv2.aruco.DetectorParameters_create() + corners, marker_ids, _ = cv2.aruco.detectMarkers(rgb_frame, aruco_dict, parameters=parameters) + + # new code version of cv2 (4.7.0) + # corners, marker_ids, rejected = aruco_detector.detectMarkers(image=rgb_frame) + + frame_processed = rgb_frame + logger = rcutils_logger.RcutilsLogger(name="aruco_node") + + # If markers are detected + if len(corners) > 0: + + logger.debug(f"Detected {len(corners)} markers.") + + for i, marker_id in enumerate(marker_ids): + # Estimate pose of each marker and return the values rvec and tvec + + # using deprecated function + # rvec, tvec, markerPoints = cv2.aruco.estimatePoseSingleMarkers(corners=corners[i], + # markerLength=marker_size, + # cameraMatrix=matrix_coefficients, + # distCoeffs=distortion_coefficients) + # tvec = tvec[0] + + # alternative code version using solvePnP + tvec, rvec, quat = my_estimatePoseSingleMarkers(corners=corners[i], marker_size=marker_size, + camera_matrix=matrix_coefficients, + distortion=distortion_coefficients) + + # show the detected markers bounding boxes + frame_processed = aruco_display(corners=corners, ids=marker_ids, + image=frame_processed) + + # draw frame axes + frame_processed = cv2.drawFrameAxes(image=frame_processed, cameraMatrix=matrix_coefficients, + distCoeffs=distortion_coefficients, rvec=rvec, tvec=tvec, + length=0.05, thickness=3) + + if (depth_frame is not None): + # get the centroid of the pointcloud + centroid = depth_to_pointcloud_centroid(depth_image=depth_frame, + intrinsic_matrix=matrix_coefficients, + corners=corners[i]) + + # log comparison between depthcloud centroid and tvec estimated positions + logger.info(f"depthcloud centroid = {centroid}") + logger.info(f"tvec = {tvec[0]} {tvec[1]} {tvec[2]}") + + # compute pose from the rvec and tvec arrays + if (depth_frame is not None): + # use computed centroid from depthcloud as estimated pose + pose = Pose() + pose.position.x = float(centroid[0]) + pose.position.y = float(centroid[1]) + pose.position.z = float(centroid[2]) + else: + # use tvec from aruco estimator as estimated pose + pose = Pose() + pose.position.x = float(tvec[0]) + pose.position.y = float(tvec[1]) + pose.position.z = float(tvec[2]) + + pose.orientation.x = quat[0] + pose.orientation.y = quat[1] + pose.orientation.z = quat[2] + pose.orientation.w = quat[3] + + # add the pose and marker id to the pose_array and markers messages + pose_array.poses.append(pose) + markers.poses.append(pose) + markers.marker_ids.append(marker_id[0]) + + return frame_processed, pose_array, markers + + +def my_estimatePoseSingleMarkers(corners, marker_size, camera_matrix, distortion) -> tuple[np.array, np.array, np.array]: + ''' + This will estimate the rvec and tvec for each of the marker corners detected by: + corners, ids, rejectedImgPoints = detector.detectMarkers(image) + + corners - is an array of detected corners for each detected marker in the image + marker_size - is the size of the detected markers in meters + mtx - is the camera intrinsic matrix + distortion - is the camera distortion matrix + RETURN list of rvecs, tvecs, and trash (so that it corresponds to the old estimatePoseSingleMarkers()) + ''' + marker_points = np.array([[-marker_size / 2.0, marker_size / 2.0, 0], + [marker_size / 2.0, marker_size / 2.0, 0], + [marker_size / 2.0, -marker_size / 2.0, 0], + [-marker_size / 2.0, -marker_size / 2.0, 0]], dtype=np.float32) + + # solvePnP returns the rotation and translation vectors + retval, rvec, tvec = cv2.solvePnP(objectPoints=marker_points, imagePoints=corners, + cameraMatrix=camera_matrix, distCoeffs=distortion, flags=cv2.SOLVEPNP_IPPE_SQUARE) + rvec = rvec.reshape(3, 1) + tvec = tvec.reshape(3, 1) + + rot, jacobian = cv2.Rodrigues(rvec) + rot_matrix = np.eye(4, dtype=np.float32) + rot_matrix[0:3, 0:3] = rot + + # convert rotation matrix to quaternion + quaternion = tf_transformations.quaternion_from_matrix(rot_matrix) + norm_quat = np.linalg.norm(quaternion) + quaternion = quaternion / norm_quat + + return tvec, rvec, quaternion + + +def depth_to_pointcloud_centroid(depth_image: np.array, intrinsic_matrix: np.array, + corners: np.array) -> np.array: + """ + This function takes a depth image and the corners of a quadrilateral as input, + and returns the centroid of the corresponding pointcloud. + + Args: + depth_image: A 2D numpy array representing the depth image. + corners: A list of 4 tuples, each representing the (x, y) coordinates of a corner. + + Returns: + A tuple (x, y, z) representing the centroid of the segmented pointcloud. + """ + + # Get image parameters + height, width = depth_image.shape + + + # Check if all corners are within image bounds + # corners has shape (1, 4, 2) + corners_indices = np.array([(int(x), int(y)) for x, y in corners[0]]) + + for x, y in corners_indices: + if x < 0 or x >= width or y < 0 or y >= height: + raise ValueError("One or more corners are outside the image bounds.") + + # bounding box of the polygon + x_min = int(min(corners_indices[:, 0])) + x_max = int(max(corners_indices[:, 0])) + y_min = int(min(corners_indices[:, 1])) + y_max = int(max(corners_indices[:, 1])) + + # create array of pixels inside the polygon defined by the corners + # search for pixels inside the squared bounding box of the polygon + points = [] + for x in range(x_min, x_max): + for y in range(y_min, y_max): + if is_pixel_in_polygon(pixel=(x, y), corners=corners_indices): + # add point to the list of points + points.append([x, y, depth_image[y, x]]) + + # Convert points to numpy array + points = np.array(points, dtype=np.uint16) + + # convert to open3d image + #depth_segmented = geometry.Image(points) + # create pinhole camera model + #pinhole_matrix = camera.PinholeCameraIntrinsic(width=width, height=height, + # intrinsic_matrix=intrinsic_matrix) + # Convert points to Open3D pointcloud + #pointcloud = geometry.PointCloud.create_from_depth_image(depth=depth_segmented, intrinsic=pinhole_matrix, + # depth_scale=1000.0) + + # apply formulas to pointcloud, where + # fx = intrinsic_matrix[0, 0], fy = intrinsic_matrix[1, 1] + # cx = intrinsic_matrix[0, 2], cy = intrinsic_matrix[1, 2], + # u = x, v = y, d = depth_image[y, x], depth_scale = 1000.0, + # z = d / depth_scale + # x = (u - cx) * z / fx + # y = (v - cy) * z / fy + + # create pointcloud + pointcloud = [] + for x, y, d in points: + z = d / 1000.0 + x = (x - intrinsic_matrix[0, 2]) * z / intrinsic_matrix[0, 0] + y = (y - intrinsic_matrix[1, 2]) * z / intrinsic_matrix[1, 1] + pointcloud.append([x, y, z]) + + # Calculate centroid from pointcloud + centroid = np.mean(np.array(pointcloud, dtype=np.uint16), axis=0) + + return centroid + + +def is_pixel_in_polygon(pixel: tuple, corners: np.array) -> bool: + """ + This function takes a pixel and a list of corners as input, and returns whether the pixel is inside the polygon + defined by the corners. This function uses the ray casting algorithm to determine if the pixel is inside the polygon. + This algorithm works by casting a ray from the pixel in the positive x-direction, and counting the number of times + the ray intersects with the edges of the polygon. If the number of intersections is odd, the pixel is inside the + polygon, otherwise it is outside. This algorithm works for both convex and concave polygons. + + Args: + pixel: A tuple (x, y) representing the pixel coordinates. + corners: A list of 4 tuples in a numpy array, each representing the (x, y) coordinates of a corner. + + Returns: + A boolean indicating whether the pixel is inside the polygon. + """ + + # Initialize counter for number of intersections + num_intersections = 0 + + # Iterate over each edge of the polygon + for i in range(len(corners)): + x1, y1 = corners[i] + x2, y2 = corners[(i + 1) % len(corners)] + + # Check if the pixel is on the same y-level as the edge + if (y1 <= pixel[1] < y2) or (y2 <= pixel[1] < y1): + # Calculate the x-coordinate of the intersection point + x_intersection = (x2 - x1) * (pixel[1] - y1) / (y2 - y1) + x1 + + # Check if the intersection point is to the right of the pixel + if x_intersection > pixel[0]: + num_intersections += 1 + + # Return whether the number of intersections is odd + return num_intersections % 2 == 1 diff --git a/rbss_aruco_pe/rbss_aruco_pe/utils.py b/rbss_aruco_pe/rbss_aruco_pe/utils.py new file mode 100755 index 0000000..281d940 --- /dev/null +++ b/rbss_aruco_pe/rbss_aruco_pe/utils.py @@ -0,0 +1,72 @@ +#!/usr/bin/env python3 + +import cv2 +from rclpy.impl import rcutils_logger + +ARUCO_DICT = { + "DICT_4X4_50": cv2.aruco.DICT_4X4_50, + "DICT_4X4_100": cv2.aruco.DICT_4X4_100, + "DICT_4X4_250": cv2.aruco.DICT_4X4_250, + "DICT_4X4_1000": cv2.aruco.DICT_4X4_1000, + "DICT_5X5_50": cv2.aruco.DICT_5X5_50, + "DICT_5X5_100": cv2.aruco.DICT_5X5_100, + "DICT_5X5_250": cv2.aruco.DICT_5X5_250, + "DICT_5X5_1000": cv2.aruco.DICT_5X5_1000, + "DICT_6X6_50": cv2.aruco.DICT_6X6_50, + "DICT_6X6_100": cv2.aruco.DICT_6X6_100, + "DICT_6X6_250": cv2.aruco.DICT_6X6_250, + "DICT_6X6_1000": cv2.aruco.DICT_6X6_1000, + "DICT_7X7_50": cv2.aruco.DICT_7X7_50, + "DICT_7X7_100": cv2.aruco.DICT_7X7_100, + "DICT_7X7_250": cv2.aruco.DICT_7X7_250, + "DICT_7X7_1000": cv2.aruco.DICT_7X7_1000, + "DICT_ARUCO_ORIGINAL": cv2.aruco.DICT_ARUCO_ORIGINAL, + "DICT_APRILTAG_16h5": cv2.aruco.DICT_APRILTAG_16h5, + "DICT_APRILTAG_25h9": cv2.aruco.DICT_APRILTAG_25h9, + "DICT_APRILTAG_36h10": cv2.aruco.DICT_APRILTAG_36h10, + "DICT_APRILTAG_36h11": cv2.aruco.DICT_APRILTAG_36h11 +} + + +def aruco_display(corners, ids, image): + ''' + This function draws the axes on the image for each of the detected markers, + given the rotation and translation vectors of the input camera image frame. + :param corners: corners of the detected marker regions + :param ids: ArUco marker IDs + :param image: input image frame + :return: RGB image with the axes drawn on it + ''' + if len(corners) > 0: + # flatten the ArUco IDs list + ids = ids.flatten() + # loop over the detected ArUCo corners + for (markerCorner, markerID) in zip(corners, ids): + # extract the marker corners (which are always returned in + # top-left, top-right, bottom-right, and bottom-left order) + corners = markerCorner.reshape((4, 2)) + (topLeft, topRight, bottomRight, bottomLeft) = corners + # convert each of the (x, y)-coordinate pairs to integers + topRight = (int(topRight[0]), int(topRight[1])) + bottomRight = (int(bottomRight[0]), int(bottomRight[1])) + bottomLeft = (int(bottomLeft[0]), int(bottomLeft[1])) + topLeft = (int(topLeft[0]), int(topLeft[1])) + + cv2.line(image, topLeft, topRight, (0, 255, 0), 2) + cv2.line(image, topRight, bottomRight, (0, 255, 0), 2) + cv2.line(image, bottomRight, bottomLeft, (0, 255, 0), 2) + cv2.line(image, bottomLeft, topLeft, (0, 255, 0), 2) + # compute and draw the center (x, y)-coordinates of the ArUco + # marker + cX = int((topLeft[0] + bottomRight[0]) / 2.0) + cY = int((topLeft[1] + bottomRight[1]) / 2.0) + cv2.circle(image, (cX, cY), 4, (0, 0, 255), -1) + # draw the ArUco marker ID on the image + cv2.putText(image, str(markerID), (topLeft[0], topLeft[1] - 10), cv2.FONT_HERSHEY_SIMPLEX, + 0.5, (0, 255, 0), 2) + + logger = rcutils_logger.RcutilsLogger(name="aruco_node") + logger.debug("[Inference] ArUco markers IDs: {}".format(ids)) + + return image + diff --git a/rbss_aruco_pe/scripts/aruco_node_lc.py b/rbss_aruco_pe/scripts/aruco_node_lc.py new file mode 100755 index 0000000..edb3229 --- /dev/null +++ b/rbss_aruco_pe/scripts/aruco_node_lc.py @@ -0,0 +1,379 @@ +#!/usr/bin/env python3 +""" +Code taken from: +https://github.com/AIRLab-POLIMI/ros2-aruco-pose-estimation +ROS2 wrapper code taken from: +https://github.com/JMU-ROBOTICS-VIVA/ros2_aruco/tree/main + +This node locates Aruco AR markers in images and publishes their ids and poses. + +Subscriptions: + /camera/image/image (sensor_msgs.msg.Image) + /camera/image/camera_info (sensor_msgs.msg.CameraInfo) + +Published Topics: + /aruco/poses (geometry_msgs.msg.PoseArray) + Pose of all detected markers (suitable for rviz visualization) + + /aruco/markers (aruco_interfaces.msg.ArucoMarkers) + Provides an array of all poses along with the corresponding + marker ids. + + /aruco/image (sensor_msgs.msg.Image) + Annotated image with marker locations and ids, with markers drawn on it + +Parameters: + marker_size - size of the markers in meters (default 0.04) + aruco_dictionary_id - dictionary that was used to generate markers (default DICT_6X6_50) + image_topic - image topic to subscribe to (default /camera/color/image_raw) + camera_info_topic - camera info topic to subscribe to (default /camera/camera_info) + camera_frame - camera optical frame to use (default "camera_depth_optical_frame") + detected_markers_topic - topic to publish detected markers (default /aruco/markers) + markers_visualization_topic - topic to publish markers visualization (default /aruco/poses) + output_image_topic - topic to publish annotated image (default /aruco/image) + +Version: 2025-04-16 +""" +# ROS2 imports +import rclpy +from rclpy.qos import qos_profile_sensor_data +from cv_bridge import CvBridge +import message_filters +from rclpy.lifecycle import Node +from rclpy.lifecycle import LifecycleState +from rclpy.lifecycle import TransitionCallbackReturn + +# Python imports +import numpy as np +import cv2 +import json + +# Local imports for custom defined functions +from rbss_aruco_pe.utils import ARUCO_DICT +from rbss_aruco_pe.pose_estimation import pose_estimation + +# ROS2 message imports +from sensor_msgs.msg import CameraInfo, Image +from geometry_msgs.msg import PoseArray +from rbs_skill_interfaces.msg import ArucoMarkers +from rbs_skill_interfaces.srv import RbsBt + +NODE_NAME_DEFAULT = "aruco_pe" +PARAM_SKILL_CFG = "aruco_pe_cfg" +CONDITION_SRV_NAME = "/condition" + +DEFAULT_ARUCO_DICTIONARY = "DICT_6X6_50" +DEFAULT_MARKER_SIZE = 0.04 +# Input topics +INP_IMAGE = "/camera/image/image" +INP_DEPTH_IMAGE = "/camera/image/depth_image" +INP_CAMERA_INFO = "/camera/image/camera_info" +CAMERA_FRAME = "camera_color_optical_frame" # Camera link frame of reference +# Output topics +OUT_DEFAULT_DETECTED_MARKERS = "/aruco/markers" +OUT_TT_DETECTED_MARKERS = "rbs_skill_interfaces/msg/ArucoMarkers" +OUT_DEFAULT_MARKERS_VISUALISATION = "/aruco/poses" +OUT_TT_MARKERS_VISUALISATION = "geometry_msgs/msg/PoseArray" +OUT_DEFAULT_IMAGE = "/aruco/image" +OUT_TT_IMAGE = "sensor_msgs/msg/Image" + +class ArucoLcNode(Node): + """Our lifecycle node.""" + def __init__(self, **kwargs): + # default value + self.dictionary_id_name = DEFAULT_ARUCO_DICTIONARY + self.marker_size = DEFAULT_MARKER_SIZE # Size of the markers in meters + self.use_depth_input = False # Use depth image for 3D pose estimation + self.is_image_mode = False # Publish Image with detected Aruco markers + + self.image_topic = INP_IMAGE + self.info_topic = INP_CAMERA_INFO + self.depth_image_topic = INP_DEPTH_IMAGE + self.camera_frame = CAMERA_FRAME + + self.detected_markers_topic = OUT_DEFAULT_DETECTED_MARKERS + self.markers_visualization_topic = OUT_DEFAULT_MARKERS_VISUALISATION + self.output_image_topic = OUT_DEFAULT_IMAGE + + # for other nodes + kwargs["allow_undeclared_parameters"] = True + kwargs["automatically_declare_parameters_from_overrides"] = True + super().__init__(NODE_NAME_DEFAULT, **kwargs) + str_cfg = self.get_parameter(PARAM_SKILL_CFG).get_parameter_value().string_value + + self.skill_cfg = json.loads(str_cfg) + self.nodeName = NODE_NAME_DEFAULT + + self.initialize_parameters() + + # Make sure we have a valid dictionary id: + try: + dictionary_id = cv2.aruco.__getattribute__(self.dictionary_id_name) + # check if the dictionary_id is a valid dictionary inside ARUCO_DICT values + if dictionary_id not in ARUCO_DICT.values(): + raise AttributeError + except AttributeError: + self.get_logger().error(f"bad aruco_dictionary_id: {self.dictionary_id_name}") + options = "\n".join([s for s in ARUCO_DICT]) + self.get_logger().error(f"valid options: {options}") + return False + + self.aruco_dictionary = cv2.aruco.getPredefinedDictionary(dictionary_id) + + self.bridge = CvBridge() + + # Set up publishers + self.poses_pub = self.create_lifecycle_publisher(PoseArray, self.markers_visualization_topic, 5) + self.markers_pub = self.create_lifecycle_publisher(ArucoMarkers, self.detected_markers_topic, 5) + self.image_pub = self.create_lifecycle_publisher(Image, self.output_image_topic, 5) + + self.markers = ArucoMarkers() + self._srv_condition = self.create_service(RbsBt, NODE_NAME_DEFAULT + CONDITION_SRV_NAME, self.condition_callback) + + self.clear_param() + + def clear_param(self): + # Set up fields for camera parameters + self.info_msg = None + self.intrinsic_mat = None + self.distortion = None + + def initialize_parameters(self): + """ + Read parameters from skill config (via interface node) + """ + self._Settings() + for prop in self.skill_cfg["topicsOut"]: + ty = prop["type"] + if ty == OUT_TT_DETECTED_MARKERS: + self.detected_markers_topic = prop["name"] + elif ty == OUT_TT_MARKERS_VISUALISATION: + self.markers_visualization_topic = prop["name"] + elif ty == OUT_TT_IMAGE: + self.output_image_topic = prop["name"] + + def _Settings(self): + # Initialization service settings + for prop in self.skill_cfg["Settings"]["output"]["params"]: + nam = prop["name"] + val = prop["value"] + if nam == "aruco_dictionary_id": + self.aruco_dictionary_id = val + elif nam == "marker_size": + self.marker_size = float(val) + elif nam == "camera_frame": # TODO перенести в dependencies для "arucoConfig" + self.camera_frame = val + elif nam == "is_image_mode": + self.is_image_mode = (val == "True") + + def condition_callback(self, request, response): + """ + Condition "isAruco" determines whether there is a marker with the given id in the frame + """ + _is = False + if request.command == "isAruco": + json_param = self.get_parameter(PARAM_SKILL_CFG).get_parameter_value().string_value + self.skill_cfg = json.loads(json_param) + for comm in self.skill_cfg["BTAction"]: + if comm["name"] == "isAruco": + for par in comm["param"]: + if par["type"] == "formBuilder": + aruco_id = int(par["dependency"]["output"]["aruco_id"]) + _is = (aruco_id in self.markers.marker_ids) # marker found in the image + self.get_logger().info(f"{aruco_id=} {_is=}") + response.ok = _is + return response + + def on_configure(self, state: LifecycleState) -> TransitionCallbackReturn: + """ + Configure the node, after a configuring transition is requested. + """ + json_param = self.get_parameter(PARAM_SKILL_CFG).get_parameter_value().string_value + self.skill_cfg = json.loads(json_param) + for comm in self.skill_cfg["BTAction"]: + for par in comm["param"]: + dependency = par["dependency"] + if par["type"] == "topic": + topic_type = dependency["topicType"] + topic_name = dependency["topicOut"] + if "CameraInfo" in topic_type: + self.info_topic = topic_name + elif "Image" in topic_type: + if "depth" in topic_name: + self.depth_image_topic = topic_name + else: + self.image_topic = topic_name + + # camera info topic for the camera calibration parameters + self.info_sub = self.create_subscription(CameraInfo, self.info_topic, self.info_callback, qos_profile_sensor_data) + + self.get_logger().info("on_configure is called.") + return TransitionCallbackReturn.SUCCESS + + def on_activate(self, state: LifecycleState) -> TransitionCallbackReturn: + # select the type of input to use for the pose estimation + if self.use_depth_input: + # use both rgb and depth image topics for the pose estimation + + # create a message filter to synchronize the image and depth image topics + self.image_sub = message_filters.Subscriber(self, Image, self.image_topic, qos_profile=qos_profile_sensor_data) + self.depth_image_sub = message_filters.Subscriber(self, Image, self.depth_image_topic, qos_profile=qos_profile_sensor_data) + + # create synchronizer between the 2 topics using message filters and approximate time policy + # slop is the maximum time difference between messages that are considered synchronized + self.synchronizer = message_filters.ApproximateTimeSynchronizer( + [self.image_sub, self.depth_image_sub], queue_size=10, slop=0.05 + ) + self.synchronizer.registerCallback(self.rgb_depth_sync_callback) + else: + # rely only on the rgb image topic for the pose estimation + + # create a subscription to the image topic + self.image_sub = self.create_subscription(Image, self.image_topic, self.image_callback, qos_profile_sensor_data) + + self.get_logger().info("on_activate is called") + return super().on_activate(state) + + def on_deactivate(self, state: LifecycleState) -> TransitionCallbackReturn: + if self.use_depth_input: + # TODO not tested + self.destroy_subscription(self.image_sub) + self.destroy_subscription(self.depth_image_sub) + else: + # Destroy the Image subscriber. + self.destroy_subscription(self.image_sub) + + self.get_logger().info("on_deactivate is called") + return super().on_deactivate(state) + + def on_cleanup(self, state: LifecycleState) -> TransitionCallbackReturn: + self.destroy_subscription(self.info_sub) + + self.clear_param() + + self.get_logger().info("on_cleanup is called") + return TransitionCallbackReturn.SUCCESS + + def on_shutdown(self, state: LifecycleState) -> TransitionCallbackReturn: + self.get_logger().info("on_shutdown is called") + return TransitionCallbackReturn.SUCCESS + + def info_callback(self, info_msg): + self.info_msg = info_msg + # get the intrinsic matrix and distortion coefficients from the camera info + self.intrinsic_mat = np.reshape(np.array(self.info_msg.k), (3, 3)) + self.distortion = np.array(self.info_msg.d) + + self.get_logger().info("Camera info received.") + self.get_logger().info(f"Intrinsic matrix: {self.intrinsic_mat}") + self.get_logger().info(f"Distortion coefficients: {self.distortion}") + self.get_logger().info(f"Camera frame: {self.info_msg.width}x{self.info_msg.height}") + + # Assume that camera parameters will remain the same... + self.destroy_subscription(self.info_sub) + + def image_callback(self, img_msg: Image): + if self.info_msg is None: + self.get_logger().warn("No camera info has been received!") + return + + # convert the image messages to cv2 format + cv_image = self.bridge.imgmsg_to_cv2(img_msg, desired_encoding="rgb8") + + # create the ArucoMarkers and PoseArray messages + self.markers = ArucoMarkers() + pose_array = PoseArray() + + # Set the frame id and timestamp for the markers and pose array + if self.camera_frame == "": + self.markers.header.frame_id = self.info_msg.header.frame_id + pose_array.header.frame_id = self.info_msg.header.frame_id + else: + self.markers.header.frame_id = self.camera_frame + pose_array.header.frame_id = self.camera_frame + + self.markers.header.stamp = img_msg.header.stamp + pose_array.header.stamp = img_msg.header.stamp + + """ + # OVERRIDE: use calibrated intrinsic matrix and distortion coefficients + self.intrinsic_mat = np.reshape([615.95431, 0., 325.26983, + 0., 617.92586, 257.57722, + 0., 0., 1.], (3, 3)) + self.distortion = np.array([0.142588, -0.311967, 0.003950, -0.006346, 0.000000]) + """ + + # call the pose estimation function + frame, pose_array, self.markers = pose_estimation(rgb_frame=cv_image, depth_frame=None, + aruco_dict=self.aruco_dictionary, + marker_size=self.marker_size, matrix_coefficients=self.intrinsic_mat, + distortion_coefficients=self.distortion, pose_array=pose_array, markers=self.markers) + # frame, pose_array, markers = pose_estimation(rgb_frame=cv_image, depth_frame=None, + # aruco_detector=self.aruco_detector, + # marker_size=self.marker_size, matrix_coefficients=self.intrinsic_mat, + # distortion_coefficients=self.distortion, pose_array=pose_array, markers=markers) + + # if some markers are detected + if len(self.markers.marker_ids) > 0: + # Publish the results with the poses and markes positions + self.poses_pub.publish(pose_array) + self.markers_pub.publish(self.markers) + + # publish the image frame with computed markers positions over the image + self.image_pub.publish(self.bridge.cv2_to_imgmsg(frame, "rgb8")) + + def rgb_depth_sync_callback(self, rgb_msg: Image, depth_msg: Image): + + # convert the image messages to cv2 format + cv_depth_image = self.bridge.imgmsg_to_cv2(depth_msg, desired_encoding="16UC1") + cv_image = self.bridge.imgmsg_to_cv2(rgb_msg, desired_encoding="rgb8") + + # create the ArucoMarkers and PoseArray messages + markers = ArucoMarkers() + pose_array = PoseArray() + + # Set the frame id and timestamp for the markers and pose array + if self.camera_frame == "": + markers.header.frame_id = self.info_msg.header.frame_id + pose_array.header.frame_id = self.info_msg.header.frame_id + else: + markers.header.frame_id = self.camera_frame + pose_array.header.frame_id = self.camera_frame + + markers.header.stamp = rgb_msg.header.stamp + pose_array.header.stamp = rgb_msg.header.stamp + + # call the pose estimation function + frame, pose_array, markers = pose_estimation(rgb_frame=cv_image, depth_frame=cv_depth_image, + aruco_dict=self.aruco_dictionary, + marker_size=self.marker_size, matrix_coefficients=self.intrinsic_mat, + distortion_coefficients=self.distortion, pose_array=pose_array, markers=markers) + # frame, pose_array, markers = pose_estimation(rgb_frame=cv_image, depth_frame=cv_depth_image, + # aruco_detector=self.aruco_detector, + # marker_size=self.marker_size, matrix_coefficients=self.intrinsic_mat, + # distortion_coefficients=self.distortion, pose_array=pose_array, markers=markers) + + # if some markers are detected + if len(markers.marker_ids) > 0: + # Publish the results with the poses and markes positions + self.poses_pub.publish(pose_array) + self.markers_pub.publish(markers) + + # publish the image frame with computed markers positions over the image + self.image_pub.publish(self.bridge.cv2_to_imgmsg(frame, "rgb8")) + +def main(): + rclpy.init() + + executor = rclpy.executors.SingleThreadedExecutor() + lc_node = ArucoLcNode() + if lc_node: + executor.add_node(lc_node) + try: + executor.spin() + except (KeyboardInterrupt, rclpy.executors.ExternalShutdownException): + lc_node.destroy_node() + rclpy.shutdown() + +if __name__ == "__main__": + main() diff --git a/rbss_movetopose/package.nix b/rbss_movetopose/package.nix new file mode 100644 index 0000000..70ba7ae --- /dev/null +++ b/rbss_movetopose/package.nix @@ -0,0 +1,23 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 + +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license + +{ lib, buildRosPackage, ament-cmake, ament-cmake-python, ament-lint-auto, ament-lint-common, geometry-msgs, rbs-skill-interfaces, rclcpp, rclpy, std-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-rbss-movetopose"; + version = "0.0.1"; + + src = ./.; + + buildType = "ament_cmake"; + buildInputs = [ ament-cmake ament-cmake-python ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ geometry-msgs rbs-skill-interfaces rclcpp rclpy std-msgs ]; + nativeBuildInputs = [ ament-cmake ament-cmake-python ]; + + meta = { + description = "The Move to pose skill"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/rbss_objectdetection/package.nix b/rbss_objectdetection/package.nix new file mode 100644 index 0000000..4e999d2 --- /dev/null +++ b/rbss_objectdetection/package.nix @@ -0,0 +1,23 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 + +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license + +{ lib, buildRosPackage, ament-cmake, ament-cmake-python, ament-lint-auto, ament-lint-common, cv-bridge, image-transport, lifecycle-msgs, rbs-skill-interfaces, rclpy, sensor-msgs, std-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-rbss-objectdetection"; + version = "0.0.1"; + + src = ./.; + + buildType = "ament_cmake"; + buildInputs = [ ament-cmake ament-cmake-python ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ cv-bridge image-transport lifecycle-msgs rbs-skill-interfaces rclpy sensor-msgs std-msgs ]; + nativeBuildInputs = [ ament-cmake ament-cmake-python ]; + + meta = { + description = "The Object Detection skill"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/rbss_objectdetection/scripts/od_yolo_lc.py b/rbss_objectdetection/scripts/od_yolo_lc.py index 6fa6bc9..929bb99 100755 --- a/rbss_objectdetection/scripts/od_yolo_lc.py +++ b/rbss_objectdetection/scripts/od_yolo_lc.py @@ -3,7 +3,8 @@ object_detection_lifecycle_node_via_interface_node ROS 2 program for Object Detection - @shalenikol release 0.3 + @shalenikol release 0.4 + ... """ from typing import Optional @@ -41,12 +42,15 @@ class ObjectDetection(Node): """Construct the node.""" self._count: int = 0 self._pub: Optional[Publisher] = None + self._pubI: Optional[Publisher] = None self._timer: Optional[Timer] = None self._image_cnt: int = 0 self._sub = None + self._threshold = 0.0 self._is_image_mode = False self.yolov8_weights_file = "" self.model = None + self.is_detection = False # object detection indicator in the frame # for other nodes kwargs["allow_undeclared_parameters"] = True @@ -75,14 +79,15 @@ class ObjectDetection(Node): def _Settings(self): # Initialization service settings - # TODO - # for prop in self.skill_cfg["Settings"]: - # nam = prop["name"] - # val = prop["value"] - # if nam == "publishDelay": - # self.publishDelay = val - # elif nam == "is_image_mode": - # self._is_image_mode = val + for prop in self.skill_cfg["Settings"]["output"]["params"]: + nam = prop["name"] + val = prop["value"] + if nam == "threshold": + self._threshold = float(val) + elif nam == "publishDelay": + self.publishDelay = float(val) + elif nam == "is_image_mode": + self._is_image_mode = (val == "True") for prop in self.skill_cfg["topicsOut"]: if prop["type"] == OUT_TOPIC_TYPE: @@ -97,6 +102,8 @@ class ObjectDetection(Node): # res = self._cli_getstate.call(req) # the program freezes id_,_ = self._state_machine.current_state _is = (id_ == State.PRIMARY_STATE_ACTIVE) + elif request.command == "isDetection": + _is = self.is_detection response.ok = _is return response @@ -116,25 +123,26 @@ class ObjectDetection(Node): dependency = {} for comm in self.skill_cfg["BTAction"]: for par in comm["param"]: - if par["type"] == "weights": - dependency = par["dependency"] - elif par["type"] == "topic": - self.topicImage = par["dependency"]["topicOut"] - assert dependency, "no weights dependency" + dependency = par["dependency"] + if par["type"] == "topic": + self.topicImage = dependency["topicOut"] + elif par["type"] == "formBuilder": + self.objName = dependency["output"]["object_name"] + val = dependency["output"]["process"]["selectProcess"]["value"] + self.yolov8_weights_file = os.path.join(val["instancePath"], val["instanceName"]+".pt") + assert self.objName, "no object name" assert self.topicImage, "no input topic dependency" + # assert self.yolov8_weights_file, "no weights dependency" - self.yolov8_weights_file = dependency["weights_file"] + # self.yolov8_weights_file = dependency["weights_file"] if not os.path.isfile(self.yolov8_weights_file): self.get_logger().warning(f"No weights found <{self.yolov8_weights_file}>") return TransitionCallbackReturn.FAILURE - self.objName = dependency["object_name"] - # Create the publisher. + self._pub = self.create_lifecycle_publisher(BoundBox, self.topicSrv, 10) if self._is_image_mode: - self._pub = self.create_lifecycle_publisher(Image, self.topicDetectImage, 3) - else: - self._pub = self.create_lifecycle_publisher(BoundBox, self.topicSrv, 10) + self._pubI = self.create_lifecycle_publisher(Image, self.topicDetectImage, 1) self._timer = self.create_timer(self.publishDelay, self.publish) @@ -147,7 +155,7 @@ class ObjectDetection(Node): def on_activate(self, state: LifecycleState) -> TransitionCallbackReturn: self.get_logger().info('on_activate() is called.') # Create the main subscriber. - self._sub = self.create_subscription(Image, self.topicImage, self.listener_callback, 3) + self._sub = self.create_subscription(Image, self.topicImage, self.listener_callback, 1) return super().on_activate(state) def on_deactivate(self, state: LifecycleState) -> TransitionCallbackReturn: @@ -169,9 +177,12 @@ class ObjectDetection(Node): self.image_det = [] self.bbox_res = None self.topicImage = "" + self.objName = "" + self.yolov8_weights_file = "" self.destroy_timer(self._timer) self.destroy_publisher(self._pub) + self.destroy_publisher(self._pubI) self.destroy_subscription(self._sub) self.get_logger().info('on_cleanup() is called.') @@ -183,6 +194,7 @@ class ObjectDetection(Node): """ self.destroy_timer(self._timer) self.destroy_publisher(self._pub) + self.destroy_publisher(self._pubI) self.destroy_subscription(self._sub) self.get_logger().info('on_shutdown() is called.') @@ -194,36 +206,40 @@ class ObjectDetection(Node): if self._pub is not None and self._pub.is_activated: # Publish result + if not self.bbox_res: + return + msg = BoundBox() + msg.is_detection = False + self.is_detection = False + #from ultralytics.engine.results + cconf = self._threshold # threshold + bb = None + for c in self.bbox_res.boxes: + idx = int(c.cls) + if self.bbox_res.names[idx] == self.objName: + conf = float(c.conf) + if cconf < conf: + cconf = conf + bb = c + if bb: + msg.is_detection = True + self.is_detection = True + msg.name = self.objName + msg.x = float(bb.xywhn[0,0]) + msg.y = float(bb.xywhn[0,1]) + msg.w = float(bb.xywhn[0,2]) + msg.h = float(bb.xywhn[0,3]) + msg.conf = float(bb.conf) + # Publish the message. + self._pub.publish(msg) + if self._is_image_mode: if len(self.image_det) == 0: return # The 'cv2_to_imgmsg' method converts an OpenCV image to a ROS 2 image message - msg = self.br.cv2_to_imgmsg(self.image_det, encoding="bgr8") - else: - if not self.bbox_res: - return - msg = BoundBox() - msg.is_detection = False - #from ultralytics.engine.results - cconf = 0.0 # threshold - bb = None - for c in self.bbox_res.boxes: - idx = int(c.cls) - if self.bbox_res.names[idx] == self.objName: - conf = float(c.conf) - if cconf < conf: - cconf = conf - bb = c - if bb: - msg.is_detection = True - msg.name = self.objName - msg.x = float(bb.xywhn[0,0]) - msg.y = float(bb.xywhn[0,1]) - msg.w = float(bb.xywhn[0,2]) - msg.h = float(bb.xywhn[0,3]) - msg.conf = float(bb.conf) - # Publish the message. - self._pub.publish(msg) + msg = self.br.cv2_to_imgmsg(self.image_det, encoding="rgb8") + # Publish the message. + self._pubI.publish(msg) def listener_callback(self, data): """ @@ -231,7 +247,7 @@ class ObjectDetection(Node): """ if self.model: self._image_cnt += 1 - if self._image_cnt % 100 == 1: + if self._image_cnt % 200 == 1: self.get_logger().info(f"detection: {self._image_cnt}") # Convert ROS Image message to OpenCV image @@ -239,12 +255,12 @@ class ObjectDetection(Node): # run inference results = self.model(current_frame) + for r in results: + self.bbox_res = r + if self._is_image_mode: for r in results: self.image_det = r.plot() # plot a BGR numpy array of predictions - else: - for r in results: - self.bbox_res = r # self.get_logger().info(f"detection: end {self._image_cnt}") diff --git a/rbss_poseestimation/package.nix b/rbss_poseestimation/package.nix new file mode 100644 index 0000000..52b8c7e --- /dev/null +++ b/rbss_poseestimation/package.nix @@ -0,0 +1,23 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 + +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license + +{ lib, buildRosPackage, ament-cmake, ament-cmake-python, ament-lint-auto, ament-lint-common, cv-bridge, geometry-msgs, image-transport, rclpy, sensor-msgs, std-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-rbss-poseestimation"; + version = "0.0.1"; + + src = ./.; + + buildType = "ament_cmake"; + buildInputs = [ ament-cmake ament-cmake-python ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ cv-bridge geometry-msgs image-transport rclpy sensor-msgs std-msgs ]; + nativeBuildInputs = [ ament-cmake ament-cmake-python ]; + + meta = { + description = "The Pose Estimation skill"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/repos/all-deps.repos b/repos/all-deps.repos index 6dde101..9e378b4 100644 --- a/repos/all-deps.repos +++ b/repos/all-deps.repos @@ -7,18 +7,10 @@ repositories: type: git url: https://github.com/solid-sinusoid/robot-builder.git version: main - rbs_gripper: - type: git - url: https://github.com/solid-sinusoid/rbs-gripper.git - version: main behavior_tree: type: git url: https://github.com/BehaviorTree/BehaviorTree.ROS2.git version: humble - dynamic_message_introspection: - type: git - url: https://github.com/osrf/dynamic_message_introspection.git - version: main robot_builder: type: git url: https://github.com/solid-sinusoid/robot-builder.git @@ -27,11 +19,7 @@ repositories: type: git url: https://github.com/solid-sinusoid/cartesian_controllers.git version: gazebo-simulation - ros2_control: + ai_worker: type: git - url: https://github.com/solid-sinusoid/ros2_control.git - version: gz-ros2-cartesian-controllers - gz_ros2_control: - type: git - url: https://github.com/solid-sinusoid/gz_ros2_control.git - version: fts-sensor + url: https://github.com/ROBOTIS-GIT/ai_worker + version: jazzy \ No newline at end of file diff --git a/repos/nix.repos b/repos/nix.repos new file mode 100644 index 0000000..329e71a --- /dev/null +++ b/repos/nix.repos @@ -0,0 +1,30 @@ +repositories: + rbs_arm: + type: git + url: https://github.com/solid-sinusoid/rbs-arm.git + version: main + robot_builder: + type: git + url: https://github.com/solid-sinusoid/robot-builder.git + version: main + behavior_tree: + type: git + url: https://github.com/BehaviorTree/BehaviorTree.ROS2.git + version: humble + robot_builder: + type: git + url: https://github.com/solid-sinusoid/robot-builder.git + version: main + cartesian_controllers: + type: git + url: https://github.com/solid-sinusoid/cartesian_controllers.git + version: gazebo-simulation +# temporal debug repositories with nix + scenario: + type: git + url: rad://z3RBwHLb4j66Q12dwkK1RGQj3ufhi + version: patches/740e5c2c969c54c0779f9511b1b1d6257fff547f + gym-gz: + type: git + url: rad://z33HXHSaU12N1tEgJCWJpB58w4KR + version: patches/82421599d3f30768e20f24d24eff270643956584 diff --git a/repos/nix/behaviortree-ros2.nix b/repos/nix/behaviortree-ros2.nix new file mode 100644 index 0000000..fc06e10 --- /dev/null +++ b/repos/nix/behaviortree-ros2.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --distro jazzy --output-dir repos/nix --output-as-nix-pkg-name --fetch +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, behaviortree-cpp, boost, btcpp-ros2-interfaces, fmt, generate-parameter-library, rclcpp, rclcpp-action }: +buildRosPackage rec { + pname = "ros-jazzy-behaviortree-ros2"; + version = "0.2.0"; + + src = fetchFromGitHub { + owner = "BehaviorTree"; + repo = "BehaviorTree.ROS2"; + rev = "cc31ea7b97947f1aac6e8c37df6cec379c84a7d9"; + sha256 = "0m0n85jab14rfssyjf9sf05rq1rdzs6kqwb467953f26bvcnckkh"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/behaviortree_ros2/"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ behaviortree-cpp boost btcpp-ros2-interfaces fmt generate-parameter-library rclcpp rclcpp-action ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "This package provides a ROS2 wrapper, on top of BehaviorTree.CPP."; + license = with lib.licenses; [ mit ]; + }; +} diff --git a/repos/nix/btcpp-ros2-interfaces.nix b/repos/nix/btcpp-ros2-interfaces.nix new file mode 100644 index 0000000..0ef975c --- /dev/null +++ b/repos/nix/btcpp-ros2-interfaces.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --distro jazzy --output-dir repos/nix --output-as-nix-pkg-name --fetch +{ lib, buildRosPackage, fetchFromGitHub, action-msgs, ament-cmake, rosidl-default-generators, rosidl-default-runtime }: +buildRosPackage rec { + pname = "ros-jazzy-btcpp-ros2-interfaces"; + version = "0.2.0"; + + src = fetchFromGitHub { + owner = "BehaviorTree"; + repo = "BehaviorTree.ROS2"; + rev = "cc31ea7b97947f1aac6e8c37df6cec379c84a7d9"; + sha256 = "0m0n85jab14rfssyjf9sf05rq1rdzs6kqwb467953f26bvcnckkh"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/btcpp_ros2_interfaces/"; + buildInputs = [ ament-cmake rosidl-default-generators ]; + propagatedBuildInputs = [ action-msgs rosidl-default-runtime ]; + nativeBuildInputs = [ ament-cmake rosidl-default-generators ]; + + meta = { + description = "ROS2 interfaces, mostly used to demonstrate behaviortree_ros2"; + license = with lib.licenses; [ mit ]; + }; +} diff --git a/repos/nix/btcpp-ros2-samples.nix b/repos/nix/btcpp-ros2-samples.nix new file mode 100644 index 0000000..8ca7cce --- /dev/null +++ b/repos/nix/btcpp-ros2-samples.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --distro jazzy --output-dir repos/nix --output-as-nix-pkg-name --fetch +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, behaviortree-ros2, btcpp-ros2-interfaces, std-msgs, std-srvs }: +buildRosPackage rec { + pname = "ros-jazzy-btcpp-ros2-samples"; + version = "0.2.0"; + + src = fetchFromGitHub { + owner = "BehaviorTree"; + repo = "BehaviorTree.ROS2"; + rev = "cc31ea7b97947f1aac6e8c37df6cec379c84a7d9"; + sha256 = "0m0n85jab14rfssyjf9sf05rq1rdzs6kqwb467953f26bvcnckkh"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/btcpp_ros2_samples/"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ behaviortree-ros2 btcpp-ros2-interfaces std-msgs std-srvs ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "Examples related to behaviortree_ros2"; + license = with lib.licenses; [ mit ]; + }; +} diff --git a/repos/nix/cartesian-compliance-controller.nix b/repos/nix/cartesian-compliance-controller.nix new file mode 100644 index 0000000..bad3b57 --- /dev/null +++ b/repos/nix/cartesian-compliance-controller.nix @@ -0,0 +1,25 @@ +# Automatically generated by: ros2nix --distro jazzy --output-dir repos/nix --output-as-nix-pkg-name --fetch +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, ament-lint-common, cartesian-controller-base, cartesian-force-controller, cartesian-motion-controller, controller-interface, hardware-interface, pluginlib, rclcpp }: +buildRosPackage rec { + pname = "ros-jazzy-cartesian-compliance-controller"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "cartesian_controllers"; + rev = "9ade57d3ef7f1bf6d514551e710110b014b4a664"; + sha256 = "0sgh7r30ga5lkx5kbdb6ms5arc4rhpbwky6k85xrgpjy1gs5nx1v"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/cartesian_compliance_controller/"; + buildInputs = [ ament-cmake ]; + checkInputs = [ ament-lint-common ]; + propagatedBuildInputs = [ cartesian-controller-base cartesian-force-controller cartesian-motion-controller controller-interface hardware-interface pluginlib rclcpp ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "Control your robot through Cartesian target poses and target wrenches"; + license = with lib.licenses; [ bsd3 ]; + }; +} diff --git a/repos/nix/cartesian-controller-base.nix b/repos/nix/cartesian-controller-base.nix new file mode 100644 index 0000000..8a52ab1 --- /dev/null +++ b/repos/nix/cartesian-controller-base.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --distro jazzy --output-dir repos/nix --output-as-nix-pkg-name --fetch +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, controller-interface, kdl-parser, pluginlib, rclcpp, realtime-tools, ros-environment, trajectory-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-cartesian-controller-base"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "cartesian_controllers"; + rev = "9ade57d3ef7f1bf6d514551e710110b014b4a664"; + sha256 = "0sgh7r30ga5lkx5kbdb6ms5arc4rhpbwky6k85xrgpjy1gs5nx1v"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/cartesian_controller_base/"; + buildInputs = [ ament-cmake ros-environment ]; + propagatedBuildInputs = [ controller-interface kdl-parser pluginlib rclcpp realtime-tools trajectory-msgs ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "The cartesian_controller_base package"; + license = with lib.licenses; [ bsd3 ]; + }; +} diff --git a/repos/nix/cartesian-controller-handles.nix b/repos/nix/cartesian-controller-handles.nix new file mode 100644 index 0000000..93689b3 --- /dev/null +++ b/repos/nix/cartesian-controller-handles.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --distro jazzy --output-dir repos/nix --output-as-nix-pkg-name --fetch +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, cartesian-controller-base, controller-interface, geometry-msgs, interactive-markers, kdl-parser, pluginlib, rclcpp, urdf }: +buildRosPackage rec { + pname = "ros-jazzy-cartesian-controller-handles"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "cartesian_controllers"; + rev = "9ade57d3ef7f1bf6d514551e710110b014b4a664"; + sha256 = "0sgh7r30ga5lkx5kbdb6ms5arc4rhpbwky6k85xrgpjy1gs5nx1v"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/cartesian_controller_handles/"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ cartesian-controller-base controller-interface geometry-msgs interactive-markers kdl-parser pluginlib rclcpp urdf ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "The cartesian_controller_handles package"; + license = with lib.licenses; [ bsd3 ]; + }; +} diff --git a/repos/nix/cartesian-controller-utilities.nix b/repos/nix/cartesian-controller-utilities.nix new file mode 100644 index 0000000..f25d297 --- /dev/null +++ b/repos/nix/cartesian-controller-utilities.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --distro jazzy --output-dir repos/nix --output-as-nix-pkg-name --fetch +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, geometry-msgs, launch, launch-ros, rclcpp, sensor-msgs }: +buildRosPackage rec { + pname = "ros-jazzy-cartesian-controller-utilities"; + version = "0.1.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "cartesian_controllers"; + rev = "9ade57d3ef7f1bf6d514551e710110b014b4a664"; + sha256 = "0sgh7r30ga5lkx5kbdb6ms5arc4rhpbwky6k85xrgpjy1gs5nx1v"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/cartesian_controller_utilities/"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ geometry-msgs launch launch-ros rclcpp sensor-msgs ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "Make the spacemouse a teach device for contact-based teleoperation"; + license = with lib.licenses; [ bsd3 ]; + }; +} diff --git a/repos/nix/cartesian-force-controller.nix b/repos/nix/cartesian-force-controller.nix new file mode 100644 index 0000000..5c7d59f --- /dev/null +++ b/repos/nix/cartesian-force-controller.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --distro jazzy --output-dir repos/nix --output-as-nix-pkg-name --fetch +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, cartesian-controller-base, controller-interface, rclcpp }: +buildRosPackage rec { + pname = "ros-jazzy-cartesian-force-controller"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "cartesian_controllers"; + rev = "9ade57d3ef7f1bf6d514551e710110b014b4a664"; + sha256 = "0sgh7r30ga5lkx5kbdb6ms5arc4rhpbwky6k85xrgpjy1gs5nx1v"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/cartesian_force_controller/"; + buildInputs = [ ament-cmake ]; + propagatedBuildInputs = [ cartesian-controller-base controller-interface rclcpp ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "The cartesian_force_controller package"; + license = with lib.licenses; [ bsd3 ]; + }; +} diff --git a/repos/nix/cartesian-motion-controller.nix b/repos/nix/cartesian-motion-controller.nix new file mode 100644 index 0000000..54d0631 --- /dev/null +++ b/repos/nix/cartesian-motion-controller.nix @@ -0,0 +1,22 @@ +# Automatically generated by: ros2nix --distro jazzy --output-dir repos/nix --output-as-nix-pkg-name --fetch +{ lib, buildRosPackage, fetchFromGitHub, cartesian-controller-base, controller-interface, rclcpp }: +buildRosPackage rec { + pname = "ros-jazzy-cartesian-motion-controller"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "cartesian_controllers"; + rev = "9ade57d3ef7f1bf6d514551e710110b014b4a664"; + sha256 = "0sgh7r30ga5lkx5kbdb6ms5arc4rhpbwky6k85xrgpjy1gs5nx1v"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/cartesian_motion_controller/"; + propagatedBuildInputs = [ cartesian-controller-base controller-interface rclcpp ]; + + meta = { + description = "The cartesian_motion_controller package"; + license = with lib.licenses; [ bsd3 ]; + }; +} diff --git a/repos/nix/cartesian-twist-controller.nix b/repos/nix/cartesian-twist-controller.nix new file mode 100644 index 0000000..8d20f5e --- /dev/null +++ b/repos/nix/cartesian-twist-controller.nix @@ -0,0 +1,22 @@ +# Automatically generated by: ros2nix --distro jazzy --output-dir repos/nix --output-as-nix-pkg-name --fetch +{ lib, buildRosPackage, fetchFromGitHub, cartesian-controller-base, controller-interface, rclcpp }: +buildRosPackage rec { + pname = "ros-jazzy-cartesian-twist-controller"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "cartesian_controllers"; + rev = "9ade57d3ef7f1bf6d514551e710110b014b4a664"; + sha256 = "0sgh7r30ga5lkx5kbdb6ms5arc4rhpbwky6k85xrgpjy1gs5nx1v"; + }; + + buildType = "ament_cmake"; + sourceRoot = "${src.name}/cartesian_twist_controller/"; + propagatedBuildInputs = [ cartesian-controller-base controller-interface rclcpp ]; + + meta = { + description = "The cartesian_twist_controller package"; + license = with lib.licenses; [ bsd3 ]; + }; +} diff --git a/repos/nix/gym-gz.nix b/repos/nix/gym-gz.nix new file mode 100644 index 0000000..b2755c8 --- /dev/null +++ b/repos/nix/gym-gz.nix @@ -0,0 +1,20 @@ +# Automatically generated by: ros2nix --distro jazzy --output-dir repos/nix --output-as-nix-pkg-name --fetch +{ lib, buildRosPackage, fetchgit, ament-copyright, ament-flake8, ament-pep257, python3Packages }: +buildRosPackage rec { + pname = "ros-jazzy-gym-gz"; + version = "1.5.0"; + + src = fetchgit { + url = "https://seed.solid-sinusoid.com/z48UvJQFxusYkCxa8WCjr5JNSVsVR.git"; + rev = "48a8a56d5f2441627cabdf0f85b3adab3eea33af"; + sha256 = "0hs3rmszdizbkxpvvkihrki61l4whnhsf1a6dwjw9ahgh98yc0qf"; + }; + + buildType = "ament_python"; + checkInputs = [ ament-copyright ament-flake8 ament-pep257 python3Packages.pytest ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ "TODO-License-declaration" ]; + }; +} diff --git a/repos/nix/rbs-arm.nix b/repos/nix/rbs-arm.nix new file mode 100644 index 0000000..f93b4f1 --- /dev/null +++ b/repos/nix/rbs-arm.nix @@ -0,0 +1,24 @@ +# Automatically generated by: ros2nix --distro jazzy --output-dir repos/nix --output-as-nix-pkg-name --fetch +{ lib, buildRosPackage, fetchFromGitHub, ament-cmake, ament-lint-auto, ament-lint-common, joint-trajectory-controller, ros-gz, ros2-control, ros2-controllers }: +buildRosPackage rec { + pname = "ros-jazzy-rbs-arm"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "rbs-arm"; + rev = "c7c02247fdb4a65cd9bc0a6e6b01e429c3523558"; + sha256 = "0ja9y52g3g172pcr9jr7ww68yh4qcj65j679hdv39cca53h4ljzx"; + }; + + buildType = "ament_cmake"; + buildInputs = [ ament-cmake ]; + checkInputs = [ ament-lint-auto ament-lint-common ]; + propagatedBuildInputs = [ joint-trajectory-controller ros-gz ros2-control ros2-controllers ]; + nativeBuildInputs = [ ament-cmake ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/repos/nix/rbs-assets-library.nix b/repos/nix/rbs-assets-library.nix new file mode 100644 index 0000000..4cd50fe --- /dev/null +++ b/repos/nix/rbs-assets-library.nix @@ -0,0 +1,36 @@ +{ + lib, + buildPythonPackage, + fetchgit, + poetry-core, + trimesh, +}: + +buildPythonPackage rec { + pname = "rbs-assets-library"; + version = "unstable-2024-12-01"; + pyproject = true; + + src = fetchgit { + url = "https://gitlab.com/solid-sinusoid/rbs-assets-library"; + rev = "16d3f6d750a8c903532f4bde22bbe41ebd35ec5c"; + hash = "sha256-p0f3hRVxVilFPUoqGAzjcffoUw1KWz1L5JaEydmfPHo="; + fetchLFS = true; + }; + + build-system = [ + poetry-core + trimesh + ]; + + pythonImportsCheck = [ + "rbs_assets_library" + ]; + + meta = { + description = ""; + homepage = "https://github.com/solid-sinusoid/rbs_assets_library"; + license = lib.licenses.asl20; + maintainers = with lib.maintainers; [ ]; + }; +} diff --git a/repos/nix/robot-builder.nix b/repos/nix/robot-builder.nix new file mode 100644 index 0000000..c8e3ebb --- /dev/null +++ b/repos/nix/robot-builder.nix @@ -0,0 +1,22 @@ +# Automatically generated by: ros2nix --distro jazzy --output-dir repos/nix --output-as-nix-pkg-name --fetch +{ lib, buildRosPackage, fetchFromGitHub, ament-copyright, ament-flake8, ament-pep257, python3Packages }: +buildRosPackage rec { + pname = "ros-jazzy-robot-builder"; + version = "0.0.0"; + + src = fetchFromGitHub { + owner = "solid-sinusoid"; + repo = "robot-builder"; + rev = "abad78494eea370d825c0e60805639f5f3b8af02"; + sha256 = "1sl3gghi3fgp946ddj5dhzx7p500yaqgklnyc15nchym0xh144lf"; + }; + + buildType = "ament_python"; + checkInputs = [ ament-copyright ament-flake8 ament-pep257 python3Packages.pytest ]; + propagatedBuildInputs = [ python3Packages.loguru ]; + + meta = { + description = "TODO: Package description"; + license = with lib.licenses; [ asl20 ]; + }; +} diff --git a/repos/nix/scenario.nix b/repos/nix/scenario.nix new file mode 100644 index 0000000..1073578 --- /dev/null +++ b/repos/nix/scenario.nix @@ -0,0 +1,73 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 + +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license +{ + stdenv, + git, + swig, + cmake, + lib, + buildRosPackage, + ament-cmake, + ament-lint-auto, + ament-lint-common, + gz-ros2-control, + ros-gz-bridge, + ros-gz-sim, + gym-gz, + fetchFromGitLab, + fetchgit +}: let + tiny-process-library = stdenv.mkDerivation rec { + pname = "tiny-process-library"; + version = "2.0.4"; + + src = fetchFromGitLab { + owner = "eidheim"; + repo = "tiny-process-library"; + rev = "v${version}"; + sha256 = "sha256-ntg0e3Ox5swCoimZG6gwpD2eKKFQx5+vXq77cK+wT1Y="; + }; + nativeBuildInputs = [cmake git]; + + meta = with lib; { + description = "A small platform-independent library making it simple to create and stop new processes in C++, as well as writing to stdin and reading from stdout and stderr of a new process"; + homepage = "https://gitlab.com/eidheim/tiny-process-library"; + license = licenses.mit; + maintainers = []; + mainProgram = "tiny-process-library"; + platforms = platforms.all; + }; + }; +in +buildRosPackage rec { + pname = "ros-jazzy-scenario"; + version = "1.4.0"; + + src = /home/movefasta/Documents/robossembler/scenario; + + buildType = "ament_cmake"; + checkInputs = [ament-lint-auto ament-lint-common]; + propagatedBuildInputs = [ament-cmake swig cmake tiny-process-library gz-ros2-control ros-gz-bridge ros-gz-sim]; + nativeBuildInputs = [ament-cmake]; + + cmakeFlags = [ + "-DSCENARIO_USE_GAZEBO=ON" + "-DSCENARIO_BUILD_SHARED_LIBRARY=OFF" + "-DSCENARIO_USE_SYSTEM_TPL=ON" + "-DCMAKE_EXPORT_COMPILE_COMMANDS=ON" + "-DSCENARIO_ENABLE_BINDINGS=ON" + "-DSCENARIO_BINDINGS_USE_ROS=ON" + ]; + + shellHook = '' + export GZ_SIM_SYSTEM_PLUGIN_PATH=${gz-ros2-control}/lib:$out/lib:$LD_LIBRARY_PATH + ''; + + meta = with lib; { + description = "ROS 2 Jazzy Scenario package"; + homepage = "https://gym-gz.pages.dev/"; + license = licenses.lgpl21Plus; + }; +} diff --git a/repos/requirements.txt b/repos/requirements.txt index 10555b1..4e8a8f8 100644 --- a/repos/requirements.txt +++ b/repos/requirements.txt @@ -1,9 +1,9 @@ -tensorflow==2.17.1 -torch==2.4.1 -optuna==2.10.0 -torchvision==0.19.1 -stable-baselines3==2.3.2 -sb3-contrib==2.3.0 +# tensorflow==2.17.1 +# torch==2.4.1 +# optuna==2.10.0 +# torchvision==0.19.1 +# stable-baselines3==2.3.2 +# sb3-contrib==2.3.0 pcg-gazebo loguru @@ -11,25 +11,25 @@ aim # monitoring tool # markupsafe==2.0.1 # Jinja2==2.6 -numpy==1.24.0 -flask==3.0.3 -Jinja2>=3.1.2 -docutils<0.18,>=0.15 -markdown-it-py<3.0.0,>=1.0.0 +# numpy==1.24.0 +# flask==3.0.3 +# Jinja2>=3.1.2 +# docutils<0.18,>=0.15 +# markdown-it-py<3.0.0,>=1.0.0 # setuptools-scm dacite>=1.8.1 -gymnasium==0.29.1 +gymnasium numpy>=1.24.0 open3d>=0.18.0 scipy>=1.14.1 trimesh>=3.9,<4.0 -wandb>=0.18.6 +# wandb>=0.18.6 # Packages from devpi custom repository -scenario @ https://devpi.solid-sinusoid.com/narmak/dev/+f/3a1/edce90594f954/scenario-1.4.1-cp310-cp310-linux_x86_64.whl#sha256=3a1edce90594f954f5eb9b1f67dd0e1b31b274a9f05cca551b1401c7b854db4f -gym-gz @ https://devpi.solid-sinusoid.com/narmak/dev/+f/539/1f448c1391486/gym_gz-1.4.0-py3-none-any.whl#sha256=5391f448c13914860e2a65904f6d0fac7eba71daaa3327d8399d7ae516471a68 -gym-gz-models @ https://devpi.solid-sinusoid.com/narmak/dev/+f/f42/4784934183e88/gym_gz_models-1.2.0-cp310-cp310-linux_x86_64.whl#sha256=f424784934183e88541c703c789315ba6118661bd221a4bf9135c6a0ee012e96 +# scenario @ https://devpi.solid-sinusoid.com/narmak/dev/+f/3a1/edce90594f954/scenario-1.4.1-cp310-cp310-linux_x86_64.whl#sha256=3a1edce90594f954f5eb9b1f67dd0e1b31b274a9f05cca551b1401c7b854db4f +# gym-gz @ https://devpi.solid-sinusoid.com/narmak/dev/+f/539/1f448c1391486/gym_gz-1.4.0-py3-none-any.whl#sha256=5391f448c13914860e2a65904f6d0fac7eba71daaa3327d8399d7ae516471a68 +# gym-gz-models @ https://devpi.solid-sinusoid.com/narmak/dev/+f/f42/4784934183e88/gym_gz_models-1.2.0-cp310-cp310-linux_x86_64.whl#sha256=f424784934183e88541c703c789315ba6118661bd221a4bf9135c6a0ee012e96 # rbs_assets_library git+https://gitlab.com/solid-sinusoid/rbs-assets-library.git@master diff --git a/robonomics/package.nix b/robonomics/package.nix new file mode 100644 index 0000000..75872d9 --- /dev/null +++ b/robonomics/package.nix @@ -0,0 +1,21 @@ +# Automatically generated by: ros2nix --distro jazzy --flake --license Apache-2.0 + +# Copyright 2025 None +# Distributed under the terms of the Apache-2.0 license + +{ lib, buildRosPackage, ament-copyright, ament-flake8, ament-pep257, pythonPackages, rclpy }: +buildRosPackage rec { + pname = "ros-jazzy-robonomics"; + version = "0.1.0"; + + src = ./.; + + buildType = "ament_python"; + checkInputs = [ ament-copyright ament-flake8 ament-pep257 pythonPackages.pytest ]; + propagatedBuildInputs = [ rclpy ]; + + meta = { + description = "Package for Robossember-Robonomics interoperability"; + license = with lib.licenses; [ "Apache-license-2.0" ]; + }; +}