add env_manager folder
This commit is contained in:
Bill Finger
parent
2d8c7217fe
commit
0a868b5163
135 changed files with 18342 additions and 0 deletions
426
env_manager/rbs_gym/launch/evaluate.launch.py
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426
env_manager/rbs_gym/launch/evaluate.launch.py
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from launch import LaunchContext, LaunchDescription
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from launch.actions import (
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DeclareLaunchArgument,
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IncludeLaunchDescription,
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OpaqueFunction,
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SetEnvironmentVariable,
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TimerAction
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)
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from launch.launch_description_sources import PythonLaunchDescriptionSource
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from launch.substitutions import LaunchConfiguration, PathJoinSubstitution
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from launch_ros.substitutions import FindPackageShare
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from launch_ros.actions import Node
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import os
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from os import cpu_count
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from ament_index_python.packages import get_package_share_directory
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def launch_setup(context, *args, **kwargs):
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# Initialize Arguments
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robot_type = LaunchConfiguration("robot_type")
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# General arguments
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with_gripper_condition = LaunchConfiguration("with_gripper")
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controllers_file = LaunchConfiguration("controllers_file")
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cartesian_controllers = LaunchConfiguration("cartesian_controllers")
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description_package = LaunchConfiguration("description_package")
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description_file = LaunchConfiguration("description_file")
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robot_name = LaunchConfiguration("robot_name")
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start_joint_controller = LaunchConfiguration("start_joint_controller")
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initial_joint_controller = LaunchConfiguration("initial_joint_controller")
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launch_simulation = LaunchConfiguration("launch_sim")
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launch_moveit = LaunchConfiguration("launch_moveit")
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launch_task_planner = LaunchConfiguration("launch_task_planner")
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launch_perception = LaunchConfiguration("launch_perception")
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moveit_config_package = LaunchConfiguration("moveit_config_package")
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moveit_config_file = LaunchConfiguration("moveit_config_file")
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use_sim_time = LaunchConfiguration("use_sim_time")
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sim_gazebo = LaunchConfiguration("sim_gazebo")
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hardware = LaunchConfiguration("hardware")
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env_manager = LaunchConfiguration("env_manager")
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launch_controllers = LaunchConfiguration("launch_controllers")
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gazebo_gui = LaunchConfiguration("gazebo_gui")
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gripper_name = LaunchConfiguration("gripper_name")
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# training arguments
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env = LaunchConfiguration("env")
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algo = LaunchConfiguration("algo")
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num_threads = LaunchConfiguration("num_threads")
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seed = LaunchConfiguration("seed")
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log_folder = LaunchConfiguration("log_folder")
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verbose = LaunchConfiguration("verbose")
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# use_sim_time = LaunchConfiguration("use_sim_time")
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log_level = LaunchConfiguration("log_level")
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env_kwargs = LaunchConfiguration("env_kwargs")
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n_episodes = LaunchConfiguration("n_episodes")
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exp_id = LaunchConfiguration("exp_id")
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load_best = LaunchConfiguration("load_best")
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load_checkpoint = LaunchConfiguration("load_checkpoint")
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stochastic = LaunchConfiguration("stochastic")
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reward_log = LaunchConfiguration("reward_log")
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norm_reward = LaunchConfiguration("norm_reward")
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no_render = LaunchConfiguration("no_render")
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sim_gazebo = LaunchConfiguration("sim_gazebo")
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launch_simulation = LaunchConfiguration("launch_sim")
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initial_joint_controllers_file_path = os.path.join(
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get_package_share_directory('rbs_arm'), 'config', 'controllers.yaml'
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)
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single_robot_setup = IncludeLaunchDescription(
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PythonLaunchDescriptionSource([
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PathJoinSubstitution([
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FindPackageShare('rbs_bringup'),
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"launch",
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"rbs_robot.launch.py"
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])
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]),
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launch_arguments={
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"env_manager": env_manager,
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"with_gripper": with_gripper_condition,
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"gripper_name": gripper_name,
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# "controllers_file": controllers_file,
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"robot_type": robot_type,
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"controllers_file": initial_joint_controllers_file_path,
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"cartesian_controllers": cartesian_controllers,
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"description_package": description_package,
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"description_file": description_file,
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"robot_name": robot_name,
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"start_joint_controller": start_joint_controller,
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"initial_joint_controller": initial_joint_controller,
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"launch_simulation": launch_simulation,
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"launch_moveit": launch_moveit,
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"launch_task_planner": launch_task_planner,
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"launch_perception": launch_perception,
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"moveit_config_package": moveit_config_package,
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"moveit_config_file": moveit_config_file,
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"use_sim_time": use_sim_time,
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"sim_gazebo": sim_gazebo,
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"hardware": hardware,
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"launch_controllers": launch_controllers,
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# "gazebo_gui": gazebo_gui
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}.items()
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)
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args = [
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"--env",
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env,
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"--env-kwargs",
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env_kwargs,
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"--algo",
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algo,
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"--seed",
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seed,
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"--num-threads",
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num_threads,
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"--n-episodes",
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n_episodes,
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"--log-folder",
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log_folder,
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"--exp-id",
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exp_id,
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"--load-best",
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load_best,
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"--load-checkpoint",
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load_checkpoint,
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"--stochastic",
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stochastic,
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"--reward-log",
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reward_log,
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"--norm-reward",
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norm_reward,
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"--no-render",
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no_render,
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"--verbose",
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verbose,
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"--ros-args",
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"--log-level",
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log_level,
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]
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rl_task = Node(
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package="rbs_gym",
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executable="evaluate",
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output="log",
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arguments=args,
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parameters=[{"use_sim_time": use_sim_time}],
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)
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delay_robot_control_stack = TimerAction(
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period=10.0,
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actions=[single_robot_setup]
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)
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nodes_to_start = [
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# env,
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rl_task,
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delay_robot_control_stack
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]
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return nodes_to_start
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def generate_launch_description():
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declared_arguments = []
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declared_arguments.append(
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DeclareLaunchArgument(
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"robot_type",
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description="Type of robot by name",
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choices=["rbs_arm","ur3", "ur3e", "ur5", "ur5e", "ur10", "ur10e", "ur16e"],
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default_value="rbs_arm",
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)
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)
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# General arguments
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declared_arguments.append(
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DeclareLaunchArgument(
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"controllers_file",
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default_value="controllers_gazebosim.yaml",
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description="YAML file with the controllers configuration.",
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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"description_package",
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default_value="rbs_arm",
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description="Description package with robot URDF/XACRO files. Usually the argument \
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is not set, it enables use of a custom description.",
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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"description_file",
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default_value="rbs_arm_modular.xacro",
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description="URDF/XACRO description file with the robot.",
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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"robot_name",
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default_value="arm0",
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description="Name for robot, used to apply namespace for specific robot in multirobot setup",
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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"start_joint_controller",
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default_value="false",
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description="Enable headless mode for robot control",
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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"initial_joint_controller",
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default_value="joint_trajectory_controller",
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description="Robot controller to start.",
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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"moveit_config_package",
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default_value="rbs_arm",
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description="MoveIt config package with robot SRDF/XACRO files. Usually the argument \
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is not set, it enables use of a custom moveit config.",
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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"moveit_config_file",
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default_value="rbs_arm.srdf.xacro",
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description="MoveIt SRDF/XACRO description file with the robot.",
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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"use_sim_time",
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default_value="true",
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description="Make MoveIt to use simulation time.\
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This is needed for the trajectory planing in simulation.",
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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"gripper_name",
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default_value="rbs_gripper",
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choices=["rbs_gripper", ""],
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description="choose gripper by name (leave empty if hasn't)",
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)
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)
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declared_arguments.append(
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DeclareLaunchArgument("with_gripper",
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default_value="true",
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description="With gripper or not?")
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)
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declared_arguments.append(
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DeclareLaunchArgument("sim_gazebo",
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default_value="true",
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description="Gazebo Simulation")
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)
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declared_arguments.append(
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DeclareLaunchArgument("env_manager",
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default_value="false",
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description="Launch env_manager?")
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)
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declared_arguments.append(
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DeclareLaunchArgument("launch_sim",
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default_value="true",
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description="Launch simulator (Gazebo)?\
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Most general arg")
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)
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declared_arguments.append(
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DeclareLaunchArgument("launch_moveit",
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default_value="false",
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description="Launch moveit?")
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)
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declared_arguments.append(
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DeclareLaunchArgument("launch_perception",
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default_value="false",
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description="Launch perception?")
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)
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declared_arguments.append(
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DeclareLaunchArgument("launch_task_planner",
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default_value="false",
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description="Launch task_planner?")
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)
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declared_arguments.append(
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DeclareLaunchArgument("cartesian_controllers",
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default_value="true",
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description="Load cartesian\
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controllers?")
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)
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declared_arguments.append(
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DeclareLaunchArgument("hardware",
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choices=["gazebo", "mock"],
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default_value="gazebo",
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description="Choose your harware_interface")
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)
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declared_arguments.append(
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DeclareLaunchArgument("launch_controllers",
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default_value="true",
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description="Launch controllers?")
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)
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declared_arguments.append(
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DeclareLaunchArgument("gazebo_gui",
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default_value="true",
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description="Launch gazebo with gui?")
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)
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# training arguments
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declared_arguments.append(
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DeclareLaunchArgument(
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"env",
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default_value="Reach-Gazebo-v0",
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description="Environment ID",
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))
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declared_arguments.append(
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DeclareLaunchArgument(
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"env_kwargs",
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default_value="",
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description="Optional keyword argument to pass to the env constructor.",
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))
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declared_arguments.append(
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DeclareLaunchArgument(
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"vec_env",
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default_value="dummy",
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description="Type of VecEnv to use (dummy or subproc).",
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))
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# Algorithm and training
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declared_arguments.append(
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DeclareLaunchArgument(
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"algo",
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default_value="sac",
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description="RL algorithm to use during the training.",
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))
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declared_arguments.append(
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DeclareLaunchArgument(
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"num_threads",
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default_value="-1",
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description="Number of threads for PyTorch (-1 to use default).",
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))
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# Random seed
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declared_arguments.append(
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DeclareLaunchArgument(
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"seed",
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default_value="84",
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description="Random generator seed.",
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))
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# Logging
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declared_arguments.append(
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DeclareLaunchArgument(
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"log_folder",
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default_value="logs",
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description="Path to the log directory.",
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))
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# Verbosity
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declared_arguments.append(
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DeclareLaunchArgument(
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"verbose",
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default_value="1",
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description="Verbose mode (0: no output, 1: INFO).",
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))
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# HER specifics
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declared_arguments.append(
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DeclareLaunchArgument(
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"log_level",
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default_value="error",
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description="The level of logging that is applied to all ROS 2 nodes launched by this script.",
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))
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declared_arguments.append(
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DeclareLaunchArgument(
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"n_episodes",
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default_value="200",
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description="Number of evaluation episodes.",
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))
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declared_arguments.append(
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DeclareLaunchArgument(
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"exp_id",
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default_value="0",
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description="Experiment ID (default: 0: latest, -1: no exp folder).",
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))
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declared_arguments.append(
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DeclareLaunchArgument(
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"load_best",
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default_value="false",
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description="Load best model instead of last model if available.",
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))
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declared_arguments.append(
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DeclareLaunchArgument(
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"load_checkpoint",
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default_value="0",
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description="Load checkpoint instead of last model if available, you must pass the number of timesteps corresponding to it.",
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))
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declared_arguments.append(
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DeclareLaunchArgument(
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"stochastic",
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default_value="false",
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description="Use stochastic actions instead of deterministic.",
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))
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declared_arguments.append(
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DeclareLaunchArgument(
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"reward_log",
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default_value="reward_logs",
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description="Where to log reward.",
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))
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declared_arguments.append(
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DeclareLaunchArgument(
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"norm_reward",
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default_value="false",
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description="Normalize reward if applicable (trained with VecNormalize)",
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))
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declared_arguments.append(
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DeclareLaunchArgument(
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"no_render",
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default_value="true",
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description="Do not render the environment (useful for tests).",
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))
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env_variables = [
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SetEnvironmentVariable(name="OMP_DYNAMIC", value="TRUE"),
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SetEnvironmentVariable(name="OMP_NUM_THREADS", value=str(cpu_count() // 2))
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]
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return LaunchDescription(declared_arguments + [OpaqueFunction(function=launch_setup)] + env_variables)
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519
env_manager/rbs_gym/launch/optimize.launch.py
Normal file
519
env_manager/rbs_gym/launch/optimize.launch.py
Normal file
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@ -0,0 +1,519 @@
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from launch import LaunchDescription
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from launch.actions import (
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DeclareLaunchArgument,
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IncludeLaunchDescription,
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OpaqueFunction,
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TimerAction
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)
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from launch.launch_description_sources import PythonLaunchDescriptionSource
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from launch.substitutions import LaunchConfiguration, PathJoinSubstitution
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from launch_ros.substitutions import FindPackageShare
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from launch_ros.actions import Node
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import os
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from os import cpu_count
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from ament_index_python.packages import get_package_share_directory
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def launch_setup(context, *args, **kwargs):
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# Initialize Arguments
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robot_type = LaunchConfiguration("robot_type")
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# General arguments
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with_gripper_condition = LaunchConfiguration("with_gripper")
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controllers_file = LaunchConfiguration("controllers_file")
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cartesian_controllers = LaunchConfiguration("cartesian_controllers")
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description_package = LaunchConfiguration("description_package")
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description_file = LaunchConfiguration("description_file")
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robot_name = LaunchConfiguration("robot_name")
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start_joint_controller = LaunchConfiguration("start_joint_controller")
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initial_joint_controller = LaunchConfiguration("initial_joint_controller")
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launch_simulation = LaunchConfiguration("launch_sim")
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launch_moveit = LaunchConfiguration("launch_moveit")
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launch_task_planner = LaunchConfiguration("launch_task_planner")
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launch_perception = LaunchConfiguration("launch_perception")
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moveit_config_package = LaunchConfiguration("moveit_config_package")
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moveit_config_file = LaunchConfiguration("moveit_config_file")
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use_sim_time = LaunchConfiguration("use_sim_time")
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sim_gazebo = LaunchConfiguration("sim_gazebo")
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hardware = LaunchConfiguration("hardware")
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env_manager = LaunchConfiguration("env_manager")
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launch_controllers = LaunchConfiguration("launch_controllers")
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gripper_name = LaunchConfiguration("gripper_name")
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# training arguments
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env = LaunchConfiguration("env")
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env_kwargs = LaunchConfiguration("env_kwargs")
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algo = LaunchConfiguration("algo")
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hyperparams = LaunchConfiguration("hyperparams")
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n_timesteps = LaunchConfiguration("n_timesteps")
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num_threads = LaunchConfiguration("num_threads")
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seed = LaunchConfiguration("seed")
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preload_replay_buffer = LaunchConfiguration("preload_replay_buffer")
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log_folder = LaunchConfiguration("log_folder")
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tensorboard_log = LaunchConfiguration("tensorboard_log")
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log_interval = LaunchConfiguration("log_interval")
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uuid = LaunchConfiguration("uuid")
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eval_episodes = LaunchConfiguration("eval_episodes")
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verbose = LaunchConfiguration("verbose")
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truncate_last_trajectory = LaunchConfiguration("truncate_last_trajectory")
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use_sim_time = LaunchConfiguration("use_sim_time")
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log_level = LaunchConfiguration("log_level")
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sampler = LaunchConfiguration("sampler")
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pruner = LaunchConfiguration("pruner")
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n_trials = LaunchConfiguration("n_trials")
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||||
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)])
|
||||
507
env_manager/rbs_gym/launch/test_env.launch.py
Normal file
507
env_manager/rbs_gym/launch/test_env.launch.py
Normal file
|
|
@ -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
|
||||
)
|
||||
524
env_manager/rbs_gym/launch/train.launch.py
Normal file
524
env_manager/rbs_gym/launch/train.launch.py
Normal file
|
|
@ -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)
|
||||
Loading…
Add table
Add a link
Reference in a new issue