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gazebo_ros2_control

This is a ROS 2 package for integrating the ros2_control controller architecture with the Gazebo Classic simulator.

This package provides a Gazebo plugin which instantiates a ros2_control controller manager and connects it to a Gazebo model.

Cart DiffBot

Usage

Modifying or building your own

cd Docker
docker build -t gazebo_ros2_control .

To run the demo

  1. Using Docker

Docker allows us to run the demo without GUI if we don’t configure it properly. The following command runs the demo without GUI:

docker run -it --rm --name gazebo_ros2_control_demo --net host gazebo_ros2_control ros2 launch gazebo_ros2_control_demos cart_example_position.launch.py gui:=false

The in your local machine you can run the Gazebo Classic client:

gzclient
  1. Using Rocker

To run the demo with GUI we are going to use rocker which is a tool to run docker images with customized local support injected for things like nvidia support. And user id specific files for cleaner mounting file permissions. You can install this tool with the following instructions.

The following command will launch Gazebo Classic:

rocker --x11 --nvidia --name gazebo_ros2_control_demo gazebo_ros2_control:latest

The following commands allow to move the cart in the rail:

docker exec -it gazebo_ros2_control_demo bash
source /home/ros2_ws/install/setup.bash
ros2 run gazebo_ros2_control_demos example_position

Add ros2_control tag to a URDF

Simple setup

To use ros2_control with your robot, you need to add some additional elements to your URDF. You should include the tag <ros2_control> to access and control the robot interfaces. We should include

  • a specific <plugin> for our robot

  • <joint> tag including the robot controllers: commands and states.

<ros2_control name="GazeboSystem" type="system">
  <hardware>
    <plugin>gazebo_ros2_control/GazeboSystem</plugin>
  </hardware>
  <joint name="slider_to_cart">
    <command_interface name="effort">
      <param name="min">-1000</param>
      <param name="max">1000</param>
    </command_interface>
    <state_interface name="position">
      <param name="initial_value">1.0</param>
    </state_interface>
    <state_interface name="velocity"/>
    <state_interface name="effort"/>
  </joint>
</ros2_control>

Using mimic joints in simulation

To use mimic joints in gazebo_ros2_control you should define its parameters in your URDF, i.e, set the <mimic> tag to the mimicked joint (see the URDF specification)

<joint name="right_finger_joint" type="prismatic">
  <axis xyz="0 1 0"/>
  <origin xyz="0.0 -0.48 1" rpy="0.0 0.0 0.0"/>
  <parent link="base"/>
  <child link="finger_right"/>
  <limit effort="1000.0" lower="0" upper="0.38" velocity="10"/>
</joint>
<joint name="left_finger_joint" type="prismatic">
  <mimic joint="right_finger_joint" multiplier="1" offset="0"/>
  <axis xyz="0 1 0"/>
  <origin xyz="0.0 0.48 1" rpy="0.0 0.0 3.1415926535"/>
  <parent link="base"/>
  <child link="finger_left"/>
  <limit effort="1000.0" lower="0" upper="0.38" velocity="10"/>
</joint>

The mimic joint must not have command interfaces configured in the <ros2_control> tag, but state interfaces can be configured.

Note

Independent of the interface type of the mimicked joint in the <ros2_control> tag, the mimic joint will use the position interface of the gazebo classic physic engine to follow the position of the mimicked joint.

Add the gazebo_ros2_control plugin

In addition to the ros2_control tags, a Gazebo plugin needs to be added to your URDF that actually parses the ros2_control tags and loads the appropriate hardware interfaces and controller manager. By default the gazebo_ros2_control plugin is very simple, though it is also extensible via an additional plugin architecture to allow power users to create their own custom robot hardware interfaces between ros2_control and Gazebo Classic.

<gazebo>
    <plugin filename="libgazebo_ros2_control.so" name="gazebo_ros2_control">
      <robot_param>robot_description</robot_param>
      <robot_param_node>robot_state_publisher</robot_param_node>
      <parameters>$(find gazebo_ros2_control_demos)/config/cart_controller.yaml</parameters>
      <controller_manager_name>simulation_controller_manager</controller_manager_name>
    </plugin>
</gazebo>

The gazebo_ros2_control <plugin> tag also has the following optional child elements:

  • <robot_param>: The location of the robot_description (URDF) on the parameter server, defaults to robot_description

  • <robot_param_node>: Name of the node where the robot_param is located, defaults to robot_state_publisher

  • <parameters>: YAML file with the configuration of the controllers

  • <hold_joints>: if set to true (default), it will hold the joints’ position if their interface was not claimed, e.g., the controller hasn’t been activated yet.

  • <controller_manager_name>: Set controller manager name (default: controller_manager)

Default gazebo_ros2_control Behavior

By default, without a <plugin> tag, gazebo_ros2_control will attempt to get all of the information it needs to interface with a ros2_control-based controller out of the URDF. This is sufficient for most cases, and good for at least getting started.

The default behavior provides the following ros2_control interfaces:

  • hardware_interface::JointStateInterface

  • hardware_interface::EffortJointInterface

  • hardware_interface::VelocityJointInterface

Advanced: custom gazebo_ros2_control Simulation Plugins

The gazebo_ros2_control Gazebo plugin also provides a pluginlib-based interface to implement custom interfaces between Gazebo Classic and ros2_control for simulating more complex mechanisms (nonlinear springs, linkages, etc).

These plugins must inherit gazebo_ros2_control::GazeboSystemInterface which implements a simulated ros2_control hardware_interface::SystemInterface. SystemInterface provides API-level access to read and command joint properties.

The respective GazeboSystemInterface sub-class is specified in a URDF model and is loaded when the robot model is loaded. For example, the following XML will load the default plugin:

<ros2_control name="GazeboSystem" type="system">
  <hardware>
    <plugin>gazebo_ros2_control/GazeboSystem</plugin>
  </hardware>
  ...
<ros2_control>
<gazebo>
  <plugin name="gazebo_ros2_control" filename="libgazebo_ros2_control.so">
    ...
  </plugin>
</gazebo>

Set up controllers

Use the tag <parameters> inside <plugin> to set the YAML file with the controller configuration.

<gazebo>
  <plugin name="gazebo_ros2_control" filename="libgazebo_ros2_control.so">
    <parameters>$(find gazebo_ros2_control_demos)/config/cart_controller.yaml</parameters>
  </plugin>
<gazebo>

The following is a basic configuration of the controllers:

  • joint_state_broadcaster: This controller publishes the state of all resources registered to a hardware_interface::StateInterface to a topic of type sensor_msgs/msg/JointState.

  • joint_trajectory_controller: This controller creates an action called /joint_trajectory_controller/follow_joint_trajectory of type control_msgs::action::FollowJointTrajectory.

controller_manager:
  ros__parameters:
    update_rate: 100  # Hz

    joint_trajectory_controller:
      type: joint_trajectory_controller/JointTrajectoryController

    joint_state_broadcaster:
      type: joint_state_broadcaster/JointStateBroadcaster

joint_trajectory_controller:
  ros__parameters:
    joints:
      - slider_to_cart
    command_interfaces:
      - position
    state_interfaces:
      - position
      - velocity

gazebo_ros2_control_demos

This package contains the contents for testing gazebo_ros2_control. It is running Gazebo Classic and some other ROS 2 nodes.

There are some examples in the Gazebo_ros2_control_demos package. These examples allow to launch a cart in a 30 meter rail.

Cart

You can run some of the configuration running the following commands:

ros2 launch gazebo_ros2_control_demos cart_example_position.launch.py
ros2 launch gazebo_ros2_control_demos cart_example_velocity.launch.py
ros2 launch gazebo_ros2_control_demos cart_example_effort.launch.py
ros2 launch gazebo_ros2_control_demos diff_drive.launch.py
ros2 launch gazebo_ros2_control_demos tricycle_drive.launch.py

When the Gazebo world is launched you can run some of the following commands to move the cart.

ros2 run gazebo_ros2_control_demos example_position
ros2 run gazebo_ros2_control_demos example_velocity
ros2 run gazebo_ros2_control_demos example_effort
ros2 run gazebo_ros2_control_demos example_diff_drive
ros2 run gazebo_ros2_control_demos example_tricycle_drive

The following example shows a parallel gripper with a mimic joint:

ros2 launch gazebo_ros2_control_demos gripper_mimic_joint_example_position.launch.py
Gripper

To demonstrate the setup of the initial position and a position-mimicked joint in case of an effort command interface of the joint to be mimicked, run

ros2 launch gazebo_ros2_control_demos gripper_mimic_joint_example_effort.launch.py

instead.

Send example commands with

ros2 run gazebo_ros2_control_demos example_gripper