github_url: | https://github.com/ros-controls/gz_ros2_control/blob/{REPOS_FILE_BRANCH}/doc/index.rst |
---|
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.
cd Dockerfile
docker build -t gz_ros2_control .
- 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:=falseThen on your local machine, you can run the Gazebo client:
gz sim -g
- 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:latestThe 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
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">
<hardware>
<plugin>gz_ros2_control/GazeboSimSystem</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>
To use mimic
joints in gz_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.
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.
<gazebo>
<plugin filename="libgz_ros2_control-system.so" name="gz_ros2_control::GazeboSimROS2ControlPlugin">
<robot_param>robot_description</robot_param>
<robot_param_node>robot_state_publisher</robot_param_node>
<parameters>$(find gz_ros2_control_demos)/config/cart_controller.yaml</parameters>
</plugin>
</gazebo>
The gz_ros2_control <plugin>
tag also has the following optional child elements:
<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.
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
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">
<hardware>
<plugin>gz_ros2_control/GazeboSimSystem</plugin>
</hardware>
...
<ros2_control>
<gazebo>
<plugin name="gz_ros2_control::GazeboSimROS2ControlPlugin" filename="libgz_ros2_control-system">
...
</plugin>
</gazebo>
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.
<gazebo>
<plugin name="gz_ros2_control::GazeboSimROS2ControlPlugin" filename="libgz_ros2_control-system">
<parameters>$(find gz_ros2_control_demos)/config/cart_controller.yaml</parameters>
<controller_manager_prefix_node_name>controller_manager</controller_manager_prefix_node_name>
</plugin>
<gazebo>
The following is a basic configuration of the controllers:
joint_state_broadcaster
: This controller publishes the state of all resources registered to ahardware_interface::StateInterface
to a topic of typesensor_msgs/msg/JointState
.joint_trajectory_controller
: This controller creates an action called/joint_trajectory_controller/follow_joint_trajectory
of typecontrol_msgs::action::FollowJointTrajectory
.
.. literalinclude:: ../gz_ros2_control_demos/config/cart_controller_position.yaml :language: yaml
There are some examples in the gz_ros2_control_demos package.
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
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
ros2 launch gz_ros2_control_demos ackermann_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
ros2 run gz_ros2_control_demos example_ackermann_drive
The following example shows a parallel gripper with a mimic joint:
ros2 launch gz_ros2_control_demos gripper_mimic_joint_example_position.launch.py
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 gz_ros2_control_demos gripper_mimic_joint_example_effort.launch.py
instead.
Send example commands:
ros2 run gz_ros2_control_demos example_gripper
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