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

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


Modifying or building your own

cd Dockerfile
docker build -t gz_ros2_control .

To run the demo

  1. Using Docker

Docker allows us to run the demo without the GUI if configured properly. The following command runs the demo without the GUI:

docker run -it --rm --name gz_ros2_control_demo --net host gz_ros2_control ros2 launch gz_ros2_control_demos cart_example_position.launch.py gui:=false

Then on your local machine, you can run the Gazebo client:

ign gazebo -g
  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. Rocker also supports user id specific files for cleaner mounting file permissions. You can install this tool with the following instructions. (make sure you meet all of the prerequisites.

The following command will launch Gazebo:

rocker --x11 --nvidia --name gz_ros2_control_demo gz_ros2_control:latest

The following commands allow the cart to be moved along the rail:

docker exec -it gz_ros2_control_demo bash
source /home/ros2_ws/install/setup.bash
ros2 run gz_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="GazeboSimSystem" type="system">
  <joint name="slider_to_cart">
    <command_interface name="effort">
      <param name="min">-1000</param>
      <param name="max">1000</param>
    <state_interface name="position">
      <param name="initial_value">1.0</param>
    <state_interface name="velocity"/>
    <state_interface name="effort"/>

Using mimic joints in simulation

To use mimic joints in gz_ros2_control you should define its parameters to your URDF. We should include:

  • <mimic> tag to the mimicked joint detailed manual

  • mimic and multiplier parameters to joint definition in <ros2_control> tag

<joint name="left_finger_joint" type="prismatic">
  <mimic joint="right_finger_joint"/>
  <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 name="left_finger_joint">
  <param name="mimic">right_finger_joint</param>
  <param name="multiplier">1</param>
  <command_interface name="position"/>
  <state_interface name="position"/>
  <state_interface name="velocity"/>
  <state_interface name="effort"/>

Add the gz_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 gz_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.

    <plugin filename="libgz_ros2_control-system.so" name="gz_ros2_control::GazeboSimROS2ControlPlugin">
      <parameters>$(find gz_ros2_control_demos)/config/cart_controller.yaml</parameters>

The gz_ros2_control <plugin> tag also has the following optional child elements:

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

Default gz_ros2_control Behavior

By default, without a <plugin> tag, gz_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 gz_ros2_control Simulation Plugins

The gz_ros2_control Gazebo plugin also provides a pluginlib-based interface to implement custom interfaces between Gazebo and ros2_control for simulating more complex mechanisms (nonlinear springs, linkages, etc).

These plugins must inherit the gz_ros2_control::GazeboSimSystemInterface, which implements a simulated ros2_control hardware_interface::SystemInterface. SystemInterface provides API-level access to read and command joint properties.

The respective GazeboSimSystemInterface 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="GazeboSimSystem" type="system">
  <plugin name="gz_ros2_control::GazeboSimROS2ControlPlugin" filename="libgz_ros2_control-system">

Set up controllers

Use the tag <parameters> inside <plugin> to set the YAML file with the controller configuration and use the tag <controller_manager_prefix_node_name> to set the controller manager node name.

  <plugin name="gz_ros2_control::GazeboSimROS2ControlPlugin" filename="libgz_ros2_control-system">
    <parameters>$(find gz_ros2_control_demos)/config/cart_controller.yaml</parameters>

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.

    update_rate: 1000  # Hz

      type: joint_trajectory_controller/JointTrajectoryController

      type: joint_state_broadcaster/JointStateBroadcaster

      - slider_to_cart
      - position
      - position
      - velocity


There are some examples in the gz_ros2_control_demos package.

Cart on rail

These examples allow to launch a cart in a 30 meter rail.


You can run some of the example configurations by running the following commands:

ros2 launch gz_ros2_control_demos cart_example_position.launch.py
ros2 launch gz_ros2_control_demos cart_example_velocity.launch.py
ros2 launch gz_ros2_control_demos cart_example_effort.launch.py

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

ros2 run gz_ros2_control_demos example_position
ros2 run gz_ros2_control_demos example_velocity
ros2 run gz_ros2_control_demos example_effort

Mobile robots


You can run some of the mobile robots running the following commands:

ros2 launch gz_ros2_control_demos diff_drive_example.launch.py
ros2 launch gz_ros2_control_demos tricycle_drive_example.launch.py

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

ros2 run gz_ros2_control_demos example_diff_drive
ros2 run gz_ros2_control_demos example_tricycle_drive


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

ros2 launch gz_ros2_control_demos gripper_mimic_joint_example.launch.py

Send example commands:

ros2 run gz_ros2_control_demos example_gripper

Pendulum with passive joints (cart-pole)

The following example shows a cart with a pendulum arm:

ros2 launch gz_ros2_control_demos pendulum_example_effort.launch.py
ros2 run gz_ros2_control_demos example_effort

This uses the effort command interface for the cart’s degree of freedom on the rail. To demonstrate that the physics of the passive joint of the pendulum is solved correctly even with the position command interface, run

ros2 launch gz_ros2_control_demos pendulum_example_position.launch.py
ros2 run gz_ros2_control_demos example_position