refactor env_manager and rbs_gym to work with rbs_runtime
This commit is contained in:
parent
6ea2eefc42
commit
bc8745abe5
95 changed files with 2972 additions and 4304 deletions
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@ -1,18 +1,21 @@
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import os
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from os import cpu_count
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import xacro
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from ament_index_python.packages import get_package_share_directory
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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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SetEnvironmentVariable,
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TimerAction
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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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from launch_ros.substitutions import FindPackageShare
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def launch_setup(context, *args, **kwargs):
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# Initialize Arguments
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@ -45,33 +48,50 @@ def launch_setup(context, *args, **kwargs):
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log_level = LaunchConfiguration("log_level")
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env_kwargs = LaunchConfiguration("env_kwargs")
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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', 'rbs_arm0_controllers.yaml'
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get_package_share_directory("rbs_arm"), "config", "rbs_arm0_controllers.yaml"
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)
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xacro_file = os.path.join(
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get_package_share_directory(description_package.perform(context)),
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"urdf",
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description_file.perform(context),
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)
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robot_description_doc = xacro.process_file(
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xacro_file,
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mappings={
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"gripper_name": gripper_name.perform(context),
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"hardware": hardware.perform(context),
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"simulation_controllers": initial_joint_controllers_file_path,
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"namespace": "",
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},
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)
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robot_description_content = robot_description_doc.toprettyxml(indent=" ")
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robot_description = {"robot_description": robot_description_content}
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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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PythonLaunchDescriptionSource(
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[
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PathJoinSubstitution(
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[FindPackageShare("rbs_bringup"), "launch", "rbs_robot.launch.py"]
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)
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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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"robot_type": robot_type,
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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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"robot_name": robot_type,
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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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@ -83,9 +103,9 @@ def launch_setup(context, *args, **kwargs):
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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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"launch_controllers": "true",
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"robot_description": robot_description_content,
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}.items(),
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)
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args = [
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@ -103,26 +123,23 @@ def launch_setup(context, *args, **kwargs):
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executable="test_agent.py",
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output="log",
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arguments=args,
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parameters=[{"use_sim_time": True}]
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parameters=[{"use_sim_time": True}, robot_description],
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)
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clock_bridge = Node(
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package='ros_gz_bridge',
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executable='parameter_bridge',
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arguments=['/clock@rosgraph_msgs/msg/Clock[ignition.msgs.Clock'],
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output='screen')
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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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package="ros_gz_bridge",
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executable="parameter_bridge",
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arguments=["/clock@rosgraph_msgs/msg/Clock[ignition.msgs.Clock"],
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output="screen",
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)
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delay_robot_control_stack = TimerAction(period=10.0, actions=[single_robot_setup])
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nodes_to_start = [
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# env,
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rl_task,
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clock_bridge,
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delay_robot_control_stack
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delay_robot_control_stack,
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]
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return nodes_to_start
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@ -133,7 +150,7 @@ def generate_launch_description():
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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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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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@ -213,62 +230,72 @@ def generate_launch_description():
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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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DeclareLaunchArgument(
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"with_gripper", default_value="true", description="With gripper or not?"
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)
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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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DeclareLaunchArgument(
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"sim_gazebo", default_value="true", description="Gazebo Simulation"
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)
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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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DeclareLaunchArgument(
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"env_manager", default_value="false", description="Launch env_manager?"
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)
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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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DeclareLaunchArgument(
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"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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)
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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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DeclareLaunchArgument(
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"launch_moveit", default_value="false", description="Launch moveit?"
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)
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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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DeclareLaunchArgument(
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"launch_perception", default_value="false", description="Launch perception?"
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)
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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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DeclareLaunchArgument(
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"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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)
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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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DeclareLaunchArgument(
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"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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)
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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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DeclareLaunchArgument(
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"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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)
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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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DeclareLaunchArgument(
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"launch_controllers",
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default_value="true",
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description="Launch controllers?",
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)
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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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DeclareLaunchArgument(
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"gazebo_gui", default_value="true", description="Launch gazebo with gui?"
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)
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)
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# training arguments
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declared_arguments.append(
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@ -276,140 +303,165 @@ def generate_launch_description():
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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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)
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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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)
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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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)
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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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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"n_timesteps",
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default_value="-1",
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description="Overwrite the number of timesteps.",
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))
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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"hyperparams",
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default_value="",
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description="Optional RL hyperparameter overwrite (e.g. learning_rate:0.01 train_freq:10).",
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))
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)
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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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# Continue training an already trained agent
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)
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)
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# Continue training an already trained agent
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declared_arguments.append(
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DeclareLaunchArgument(
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"trained_agent",
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default_value="",
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description="Path to a pretrained agent to continue training.",
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))
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# Random seed
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)
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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="-1",
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description="Random generator seed.",
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))
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# Saving of model
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)
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)
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# Saving of model
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declared_arguments.append(
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DeclareLaunchArgument(
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"save_freq",
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default_value="10000",
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description="Save the model every n steps (if negative, no checkpoint).",
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))
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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"save_replay_buffer",
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default_value="False",
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description="Save the replay buffer too (when applicable).",
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))
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# Pre-load a replay buffer and start training on it
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)
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)
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# Pre-load a replay buffer and start training on it
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declared_arguments.append(
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DeclareLaunchArgument(
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"preload_replay_buffer",
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default_value="",
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description="Path to a replay buffer that should be preloaded before starting the training process.",
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))
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# Logging
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)
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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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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"tensorboard_log",
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default_value="tensorboard_logs",
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description="Tensorboard log dir.",
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))
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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"log_interval",
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default_value="-1",
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description="Override log interval (default: -1, no change).",
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))
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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"uuid",
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default_value="False",
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description="Ensure that the run has a unique ID.",
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))
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# Evaluation
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)
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)
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# Evaluation
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declared_arguments.append(
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DeclareLaunchArgument(
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"eval_freq",
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default_value="-1",
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description="Evaluate the agent every n steps (if negative, no evaluation).",
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))
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)
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)
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declared_arguments.append(
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DeclareLaunchArgument(
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"eval_episodes",
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default_value="5",
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description="Number of episodes to use for evaluation.",
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))
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# Verbosity
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)
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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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"truncate_last_trajectory",
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default_value="True",
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description="When using HER with online sampling the last trajectory in the replay buffer will be truncated after) reloading the replay buffer."
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)),
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)
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)
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# HER specifics
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(
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declared_arguments.append(
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DeclareLaunchArgument(
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"truncate_last_trajectory",
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default_value="True",
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description="When using HER with online sampling the last trajectory in the replay buffer will be truncated after) reloading the replay buffer.",
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)
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),
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)
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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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)
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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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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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return LaunchDescription(
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declared_arguments + [OpaqueFunction(function=launch_setup)] + env_variables
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)
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