Analyzing Your System Using rqt_console

In this tutorial, we will explore how to use the rqt_console tool in ROS 2 to analyze and debug your robotic system. The rqt_console is a graphical user interface that displays log messages from various nodes in your ROS 2 system, making it easier to identify and diagnose issues.

Sure, you could run your program and scroll through the terminal window to see all the logs. But rqt_console makes that process a lot more efficient, enabling you to filter for exactly what you are looking for.

Prerequisites

You have completed this tutorial: How to Simulate a Mobile Robot in Gazebo – ROS 2 Jazzy
I am assuming you are using Visual Studio Code, but you can use any code editor.

All my code for this project is located here on GitHub.

Launch

Start rqt_console:

ros2 run rqt_console rqt_console

The rqt_console window will open.

As explained on the official ROS 2 documentation, the top section of the console is where log messages from your system will display.

The middle section is where you can filter the messages by excluding severity levels.

The bottom section is for highlighting messages that include a string you input.

In the bottom section type: imu/data.

Open a terminal window, and type the following command to run the robot:

x3

bash ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_bringup/scripts/rosmaster_x3_gazebo.sh

The message list at the top will highlight only the messages related to the IMU data topic.

Let’s type another string.

mecanum_drive_controller

You will see all the messages related to the mecanum drive controller.

That’s it! Keep building!

How to Simulate a Mobile Robot in Gazebo – ROS 2 Jazzy

In this tutorial, we will simulate and control a mobile robot in Gazebo. I will show you how to set up and control a mecanum wheel robot using ROS 2 Control and Gazebo.

By the end of this tutorial, you will be able to build this:

Prerequisites

You have completed this tutorial: Create and Visualize a Mobile Robot with URDF – ROS 2 Jazzy.
You have completed this tutorial: How to Simulate a Robotic Arm in Gazebo – ROS 2 Jazzy (recommended but not required if you understand how Gazebo and ROS 2 Control work at a high level)
I am assuming you are using Visual Studio Code, but you can use any code editor.

All my code for this project is located here on GitHub.

Create Packages

Navigate to your workspace, and create the following packages. You can replace the maintainer-name and maintainer email with your own information.

cd ~/ros2_ws/src/yahboom_rosmaster/

ros2 pkg create --build-type ament_cmake \
                --license BSD-3-Clause \
                --maintainer-name ubuntu \
                --maintainer-email automaticaddison@todo.com \
                yahboom_rosmaster_bringup

ros2 pkg create --build-type ament_cmake \
                --license BSD-3-Clause \
                --maintainer-name ubuntu \
                --maintainer-email automaticaddison@todo.com \
               yahboom_rosmaster_gazebo

ros2 pkg create --build-type ament_cmake \
                --license BSD-3-Clause \
                --maintainer-name ubuntu \
                --maintainer-email automaticaddison@todo.com \
                yahboom_rosmaster_system_tests

Update the package.xml files for all packages, including the metapackage. Be sure to add a good description line for each.

You can also update the metapackage with the new packages you just created.

cd yahboom_rosmaster

gedit package.xml

<?xml version="1.0"?>
<?xml-model href="http://download.ros.org/schema/package_format3.xsd" schematypens="http://www.w3.org/2001/XMLSchema"?>
<package format="3">
  <name>yahboom_rosmaster</name>
  <version>0.0.0</version>
  <description>ROSMASTER series robots by Yahboom (metapackage).</description>
  <maintainer email="automaticaddison@todo.todo">ubuntu</maintainer>
  <license>BSD-3-Clause</license>

  <buildtool_depend>ament_cmake</buildtool_depend>

  <exec_depend>yahboom_rosmaster_bringup</exec_depend>
  <exec_depend>yahboom_rosmaster_description</exec_depend>
  <exec_depend>yahboom_rosmaster_gazebo</exec_depend>
  <exec_depend>yahboom_rosmaster_system_tests</exec_depend>

  <test_depend>ament_lint_auto</test_depend>
  <test_depend>ament_lint_common</test_depend>

  <export>
    <build_type>ament_cmake</build_type>
  </export>
</package>

Edit package.xml

Now let’s make sure some key packages are installed to handle the integration between ROS 2 and Gazebo. One important package is ros_gz. Here is the GitHub repository, and here are the official installation instructions. Let’s walk through this together.

Open a terminal window, and go to your package.xml folder inside the yahboom_rosmaster_gazebo package.

cd ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_gazebo

Open the package.xml file.

Make sure it has this block:

<depend>controller_manager</depend>
<depend>gz_ros2_control</depend>
<depend>python3-numpy</depend>
<depend>rclcpp</depend>
<depend>ros_gz</depend>
<depend>ros_gz_bridge</depend>
<depend>ros_gz_image</depend>
<depend>ros_gz_sim</depend>
<depend>ros2_control</depend>
<depend>ros2_controllers</depend>
<depend>trajectory_msgs</depend>
<depend>xacro</depend>
<exec_depend>gz_ros2_control_demos</exec_depend>
<exec_depend>rqt_robot_steering</exec_depend>
<exec_depend>rviz_imu_plugin</exec_depend>

Edit CMakeLists.txt

Now open the CMakeLists.txt file, and add this block:

find_package(ament_cmake REQUIRED)
find_package(controller_manager REQUIRED)
find_package(gz_ros2_control REQUIRED)
find_package(rclcpp REQUIRED)
find_package(ros_gz REQUIRED)
find_package(ros_gz_bridge REQUIRED)
find_package(ros_gz_image REQUIRED)
find_package(ros_gz_sim REQUIRED)
find_package(ros2_control REQUIRED)
find_package(ros2_controllers REQUIRED)
find_package(trajectory_msgs REQUIRED)
find_package(xacro REQUIRED)

Build the Workspace

Now let’s build our workspace.

cd ~/ros2_ws/

rosdep install -i --from-path src --rosdistro $ROS_DISTRO -y

colcon build && source ~/.bashrc

Open a terminal window, and type:

echo "alias build='cd ~/dev_ws/ && colcon build && source ~/.bashrc'" >> ~/.bashrc

Now going forward, any time you want to build you workspace, just type:

build

Test Your Installation

Let’s test to see if Gazebo and ROS 2 Control are working properly:

ros2 launch gz_ros2_control_demos diff_drive_example.launch.py

To move the robot from the terminal window, you can type:

ros2 topic pub /diff_drive_base_controller/cmd_vel geometry_msgs/msg/TwistStamped "{header: {stamp: now, frame_id: 'base_link'}, twist: {linear: {x: 0.2, y: 0.0, z: 0.0}, angular: {x: 0.0, y: 0.0, z: 0.5}}}" --rate 5

To stop the robot:

CTRL + C

ros2 topic pub /diff_drive_base_controller/cmd_vel geometry_msgs/msg/TwistStamped "{header: {stamp: now, frame_id: 'base_link'}, twist: {linear: {x: 0.0, y: 0.0, z: 0.0}, angular: {x: 0.0, y: 0.0, z: 0.0}}}" --rate 5

Create World Files

Now we will create an environment for our simulated robot.

Open a terminal window, and type:

cd ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_gazebo/

Create a worlds folder and other folders we will need later:

mkdir -p worlds launch models

Now let’s create our world. The first world we will create is an empty world.

cd worlds

gedit empty.world

Add this code.

Save the file, and close it.

Now launch your Gazebo world:

cd ~/ros2_ws/src/mycobot_ros2/mycobot_gazebo/worlds/

gz sim empty.world

Press CTRL + C to close everything.

Now let’s create a world called pick_and_place_demo.world.

gedit pick_and_place_demo.world

Add this code.

Now let’s create a world called house.world.

gedit house.world

Add this code.

Save the file, and close it.

Now let’s create a world called cafe.world.

gedit cafe.world

Add this code.

Save the file, and close it.

Add all these models to your models folder.

Create a Mecanum Drive Controller

We need to create a controller for a mobile robot with mecanum omnidirectional wheels since none exists in the official ros2_controllers package. The official instructions for creating a new controller are on this page. We will adapt these instructions to your use case.

Create a Package

cd ~/ros2_ws/src/yahboom_rosmaster/

ros2 pkg create --build-type ament_cmake \
                --license BSD-3-Clause \
                --maintainer-name ubuntu \
                --maintainer-email automaticaddison@todo.com \
                mecanum_drive_controller

Now let’s prepare our source files. Move into the new package directory and create the necessary folders:

cd mecanum_drive_controller

mkdir -p test config

Prepare Files

Let’s create the header files:

touch include/mecanum_drive_controller/mecanum_drive_controller.hpp
touch include/mecanum_drive_controller/odometry.hpp
touch include/mecanum_drive_controller/speed_limiter.hpp
touch include/mecanum_drive_controller/visibility_control.h

Next, create the source files we need to implement:

touch src/mecanum_drive_controller.cpp
touch src/mecanum_drive_controller_parameter.yaml
touch src/odometry.cpp
touch src/speed_limiter.cpp

Create the test files we need to create:

mkdir -p test/config/
touch test/config/test_mecanum_drive_controller.yaml
touch test/test_mecanum_drive_controller.cpp
touch test/test_load_mecanum_drive_controller.cpp

Create other files we need to implement:

touch mecanum_drive_plugin.xml

Add Declarations into the Header File

Open mecanum_drive_controller.hpp inside the include/mecanum_drive_controller folder.

Add this code.

Save the file, and close it.

Open odometry.hpp inside the include/mecanum_drive_controller folder.

Add this code.

Save the file, and close it.

Open speed_limiter.hpp inside the include/mecanum_drive_controller folder.

Add this code.

Save the file, and close it.

Open visibility_control.h inside the include/mecanum_drive_controller folder.

Add this code.

Save the file, and close it.

Mecanum Wheel Forward and Inverse Kinematics

Before we write our source code, let’s dive into the mathematics that make omnidirectional movement possible. This foundation will be important when we implement our controller in the next section.

The coordinate system for our robot follows ROS 2 conventions. The base frame’s X-axis points forward, Y-axis points left, and rotations follow the right-hand rule with positive counterclockwise rotation. We number our wheels starting from the front-left as Wheel 1 (FL), moving clockwise to Wheel 2 (FR), Wheel 3 (RL), and Wheel 4 (RR).

Understanding Wheel Rotation Direction

Before diving into the kinematics equations, we need to understand how wheel rotations are defined in our system.

Each wheel’s rotation axis aligns with its positive y-axis, which runs parallel to the robot base’s y-axis. You can see this in the mecanum_wheel.urdf.xacro file. A positive wheel velocity value indicates counterclockwise rotation when viewed down this y-axis (imagine looking at the wheel from its side with the y-axis pointing towards you).

This convention has practical implications. For example, when commanding the robot to move forward, each wheel rotates counterclockwise around its y-axis, creating a positive velocity value. Think of the wheel’s 2D plane (formed by its positive z and x axes) rotating counterclockwise around the y-axis. This coordinated motion drives the robot base forward.

Forward Kinematics: From Wheel Speeds to Robot Motion

The forward kinematics equations tell us how individual wheel velocities combine to create the robot’s overall motion. These equations are particularly useful when we need to estimate the robot’s actual movement based on wheel encoder feedback.

Looking at the equations, we can see how each wheel contributes to the robot’s linear velocities (vx and vy) and angular velocity (ωz). The wheel radius R scales the contribution of each wheel’s angular velocity (ω1 through ω4).

Inverse Kinematics for Motion Control

In our ROS 2 controller, we’ll primarily use inverse kinematics. These equations help us calculate the required wheel velocities to achieve desired robot motion. When we receive velocity commands (typically from the /cmd_vel topic), we’ll use these equations to determine appropriate wheel speeds.

The inverse kinematics equations consider:

The robot’s desired linear velocities (vx and vy)
The desired angular velocity (ωz)
The robot’s physical dimensions (L and W)
The wheel radius (R)

In our mecanum drive controller we transform velocity commands into actual wheel motions. We also handle odometry feedback using the forward kinematics equations to provide accurate motion estimation of the full robot.

Mecanum Wheel Kinematics in ROS 2: Translating Equations into Code

Now that we understand the mathematics behind forward and inverse kinematics, let’s map these equations to ROS 2 concepts. This step bridges the gap between theory and implementation, ensuring a smooth transition into developing a functional mecanum drive controller.

Forward Kinematics in ROS 2

These equations estimate the robot’s motion based on wheel encoder feedback, providing odometry as linear and angular velocities in meters per second and radians per second.

Inverse Kinematics in ROS 2

These equations allow us to translate velocity commands into individual wheel speeds.

Create Source Files

Now let’s create the source files.

cd ~/ros2_ws/src/yahboom_rosmaster/mecanum_drive_controller/

Open speed_limiter.cpp inside the src folder.

Add this code.

Save the file, and close it.

Open mecanum_drive_controller_parameter.yaml inside the src folder.

Add this code.

Save the file, and close it.

Open odometry.cpp inside the src folder.

Add this code.

Save the file, and close it.

Open mecanum_drive_controller.cpp inside the src folder.

Add this code.

Save the file, and close it.

Write Export Definition for Pluginlib

Now we need to create the pluginlib XML file in the package root.

cd ~/ros2_ws/src/yahboom_rosmaster/mecanum_drive_controller/

Open mecanum_drive_plugin.xml

Add this code.

Save the file, and close it.

Write a Test to Check if the Controller Can Be Found and Loaded

Now we are going to write tests to confirm the controller can be found and loaded.

cd ~/ros2_ws/src/yahboom_rosmaster/mecanum_drive_controller/test

Open test_mecanum_drive_controller.yaml.

Add this code.

Save the file, and close it.

We are not going to use this yaml file. I just put it there as a reference to list all the available parameters for this controller.

Now let’s write the code to test if the mecanum drive controller can be loaded into the ROS 2 Control framework.

Open test_load_mecanum_drive_controller.cpp.

Add this code.

Save the file, and close it.

Add Dependencies into package.xml File

Now we need to update our package dependencies.

cd ~/ros2_ws/src/yahboom_rosmaster/mecanum_drive_controller/

Open the package.xml file.

Add this code.

Save the file, and close it.

Add Compile Directives into the CMakeLists.txt File

Now we need to update our CMakeLists.txt file.

cd ~/ros2_ws/src/yahboom_rosmaster/mecanum_drive_controller/

Open the CMakeLists.txt file.

Add this code.

Save the file, and close it.

Compile and Test the Controller

Let’s build our package to make sure everything is set up correctly:

cd ~/ros2_ws

rosdep install --from-paths src --ignore-src -r -y

colcon build --packages-select mecanum_drive_controller

source ~/.bashrc

Finally, let’s run the tests to ensure our controller can be found and loaded:

colcon test --packages-select mecanum_drive_controller

OR (for detailed output)

colcon test --packages-select mecanum_drive_controller --event-handlers console_direct+

You can also see your new controller if you type:

ros2 pkg list

Connect Gazebo to ROS 2 Control

Create a YAML Configuration File for the Controller Manager

After setting up our simulation environment in Gazebo, we need to tell ROS 2 Control how to manage our robot’s movements in this virtual world. Let’s create a configuration file that defines how our robot’s wheels should be controlled.

Open a terminal window, and type:

cd ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_description/

mkdir -p config/rosmaster_x3/

Create a new file inside the config/rosmaster_x3 directory called:

ros2_controllers.yaml

Add this code:

# controller_manager provides the necessary infrastructure to manage multiple controllers
# efficiently and robustly using ROS 2 Control.
controller_manager:
 ros__parameters:
   update_rate: 50  # Hz

   # Declare the controllers
   joint_state_broadcaster:
     type: joint_state_broadcaster/JointStateBroadcaster

   mecanum_drive_controller:
     type: mecanum_drive_controller/MecanumDriveController

# Parameters for the mecanum drive controller
mecanum_drive_controller:
 ros__parameters:
   # Joint names
   front_left_joint_name: front_left_wheel_joint
   front_right_joint_name: front_right_wheel_joint
   back_left_joint_name: back_left_wheel_joint
   back_right_joint_name: back_right_wheel_joint

   # Robot physical parameters
   wheel_base: 0.16
   wheel_separation: 0.169
   wheel_radius: 0.0325
   wheel_separation_multiplier: 1.0
   front_left_wheel_radius_multiplier: 1.0
   front_right_wheel_radius_multiplier: 1.0
   back_left_wheel_radius_multiplier: 1.0
   back_right_wheel_radius_multiplier: 1.0

   # TF configuration
   tf_frame_prefix_enable: false
   tf_frame_prefix: ""
   odom_frame_id: odom
   base_frame_id: base_footprint

   # Odometry parameters
   pose_covariance_diagonal: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
   twist_covariance_diagonal: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
   position_feedback: true
   open_loop: true
   enable_odom_tf: true

   # Command handling
   cmd_vel_timeout: 0.5
   publish_limited_velocity: false
   velocity_rolling_window_size: 10
   publish_rate: 50.0

   # Velocity limits
   linear.x.has_velocity_limits: false
   linear.x.has_acceleration_limits: false
   linear.x.has_jerk_limits: false
   linear.x.max_velocity: 0.0
   linear.x.min_velocity: 0.0
   linear.x.max_acceleration: 0.0
   linear.x.max_jerk: 0.0
   linear.x.min_jerk: 0.0
   linear.y.has_velocity_limits: false
   linear.y.has_acceleration_limits: false
   linear.y.has_jerk_limits: false
   linear.y.max_velocity: 0.0
   linear.y.min_velocity: 0.0
   linear.y.max_acceleration: 0.0
   linear.y.max_jerk: 0.0
   linear.y.min_jerk: 0.0
   angular.z.has_velocity_limits: false
   angular.z.has_acceleration_limits: false
   angular.z.has_jerk_limits: false
   angular.z.max_velocity: 0.0
   angular.z.min_velocity: 0.0
   angular.z.max_acceleration: 0.0
   angular.z.min_acceleration: 0.0
   angular.z.max_jerk: 0.0
   angular.z.min_jerk: 0.0

Save the file, and close it.

Create a new file inside the config/rosmaster_x3 directory called:

ros2_controllers_template.yaml

Add this code, and save the file.

This file will help us substitute a prefix should we desire.

Update CMakeLists.txt with the new config folder.

Update yahboom_rosmaster_desciption/launch/robot_state_publisher.py with the relevant part to handle the finding and replacing.

cd ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_description/launch

Save the file, and close it.

Create the XACRO/URDF Files

Next, we need to add three essential XACRO/URDF files that bridge Gazebo simulation with ROS 2 Control. These files work alongside your controller configuration YAML file to create a complete control system.

gazebo_sim_ros2_control.urdf.xacro

Open a terminal window.

Type the following command:

cd ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_description/urdf/

mkdir control

Create the file named:

gazebo_sim_ros2_control.urdf.xacro

Add this code.

Save the file, and close it.

rosmaster_x3_ros2_control.urdf.xacro:

Open a terminal window.

Type the following command:

cd ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_description/urdf/control

Create the file named:

rosmaster_x3_ros2_control.urdf.xacro

Add this code.

Save the file, and close it.

velocity_control_plugin.urdf.xacro

One more file to add. Add this one. This plugin is used to send velocity commands to the robot.

<?xml version="1.0"?>
<robot xmlns:xacro="http://www.ros.org/wiki/xacro">
    <xacro:macro name="load_velocity_control_plugin" params="use_gazebo">
        <xacro:if value="${use_gazebo}">
            <gazebo>
                <plugin
                    filename="gz-sim-velocity-control-system"
                    name="gz::sim::systems::VelocityControl">
                    <topic>mecanum_drive_controller/cmd_vel</topic>
                    <initial_linear>0 0 0</initial_linear>
                    <initial_angular>0 0 0</initial_angular>
                </plugin>
            </gazebo>
        </xacro:if>
    </xacro:macro>
</robot>

Include the Files in rosmaster_x3.urdf.xacro

Next we need to include these files inside rosmaster_x3.urdf.xacro.

cd ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_description/urdf/robots/

Open the rosmaster_x3_urdf.xacro file.

Add this code at the end before the </robot> tag:

     <xacro:include filename="$(find yahboom_rosmaster_description)/urdf/control/gazebo_sim_ros2_control.urdf.xacro" />
      <xacro:load_gazebo_sim_ros2_control_plugin
        robot_name="$(arg robot_name)"
        use_gazebo="$(arg use_gazebo)"/>

      <xacro:include filename="$(find yahboom_rosmaster_description)/urdf/control/rosmaster_x3_ros2_control.urdf.xacro" />
      <xacro:yahboom_rosmaster_ros2_control
        prefix="$(arg prefix)"
        use_gazebo="$(arg use_gazebo)"/>

Save the file, and close it.

Create the Launch Files

Now let’s create the launch files.

load_ros2_controllers.launch.py

cd  ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_bringup/

mkdir launch

cd launch

Add this code called load_ros2_controllers.launch.py:

#!/usr/bin/env python3
"""
Launch ROS 2 controllers for the mecanum wheel robot.

This script creates a launch description that starts the necessary controllers
for operating the mecanum wheel robot in a specific sequence.

Launched Controllers:
    1. Joint State Broadcaster: Publishes joint states to /joint_states
    2. Mecanum Drive Controller: Controls the robot's mecanum drive movements via ~/cmd_vel

:author: Addison Sears-Collins
:date: November 20, 2024
"""

from launch import LaunchDescription
from launch.actions import ExecuteProcess, RegisterEventHandler, TimerAction
from launch.event_handlers import OnProcessExit


def generate_launch_description():
    """Generate a launch description for sequentially starting robot controllers.

    The function creates a launch sequence that ensures controllers are started
    in the correct order.

    Returns:
        LaunchDescription: Launch description containing sequenced controller starts
    """
    # Start mecanum drive controller
    start_mecanum_drive_controller_cmd = ExecuteProcess(
        cmd=['ros2', 'control', 'load_controller', '--set-state', 'active',
             'mecanum_drive_controller'],
        output='screen'
    )

    # Start joint state broadcaster
    start_joint_state_broadcaster_cmd = ExecuteProcess(
        cmd=['ros2', 'control', 'load_controller', '--set-state', 'active',
             'joint_state_broadcaster'],
        output='screen'
    )

    # Add delay to joint state broadcaster
    delayed_start = TimerAction(
        period=20.0,
        actions=[start_joint_state_broadcaster_cmd]
    )

    # Register event handler for sequencing
    load_joint_state_broadcaster_cmd = RegisterEventHandler(
        event_handler=OnProcessExit(
            target_action=start_joint_state_broadcaster_cmd,
            on_exit=[start_mecanum_drive_controller_cmd]))

    # Create and populate the launch description
    ld = LaunchDescription()

    # Add the actions to the launch description in sequence
    ld.add_action(delayed_start)
    ld.add_action(load_joint_state_broadcaster_cmd)

    return ld

Save the file, and close it.

Update CMakeLists.txt for the yahboom_rosmaster_bringup package to include the new launch folder. Make sure the block below, looks like this:

# Copy necessary files to designated locations in the project
install (
  DIRECTORY launch
  DESTINATION share/${PROJECT_NAME}
)

Create YAML File for ROS 2 Bridge

We now need to create a YAML file that bridges between ROS 2 and Gazebo topics. This file will specify how sensor data (camera info, point clouds, IMU data, and LIDAR data) should be translated between the Gazebo simulation environment and the ROS 2 ecosystem. The configuration ensures that simulated sensor data can be used by ROS 2 nodes for perception and planning tasks.

cd ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_gazebo/

mkdir config

Update CMakeLists.txt with the new config folder.

# Copy necessary files to designated locations in the project
install (
  DIRECTORY config
  DESTINATION share/${PROJECT_NAME}
)

Create a file called ros_gz_bridge.yaml inside the config folder.

Add this code.

# RGBD Camera topics
- ros_topic_name: "cam_1/color/camera_info"
  gz_topic_name: "cam_1/camera_info"
  ros_type_name: "sensor_msgs/msg/CameraInfo"
  gz_type_name: "gz.msgs.CameraInfo"
  direction: GZ_TO_ROS
  lazy: true # Determines whether connections are created immediately at startup (when false) or only when data is actually requested by a subscriber (when true), helping to conserve system resources at the cost of potential initial delays in data flow.

- ros_topic_name: "cam_1/depth/color/points"
  gz_topic_name: "cam_1/points"
  ros_type_name: "sensor_msgs/msg/PointCloud2"
  gz_type_name: "gz.msgs.PointCloudPacked"
  direction: GZ_TO_ROS
  lazy: true

  # LIDAR configuration
- ros_topic_name: "scan"
  gz_topic_name: "scan"
  ros_type_name: "sensor_msgs/msg/LaserScan"
  gz_type_name: "gz.msgs.LaserScan"
  direction: GZ_TO_ROS
  lazy: false

# IMU configuration
- ros_topic_name: "imu/data"
  gz_topic_name: "imu/data"
  ros_type_name: "sensor_msgs/msg/Imu"
  gz_type_name: "gz.msgs.IMU"
  direction: GZ_TO_ROS
  lazy: false

# Sending velocity commands from ROS 2 to Gazebo
- ros_topic_name: "mecanum_drive_controller/cmd_vel"
  gz_topic_name: "mecanum_drive_controller/cmd_vel"
  ros_type_name: "geometry_msgs/msg/TwistStamped"
  gz_type_name: "gz.msgs.Twist"
  direction: ROS_TO_GZ
  lazy: false

Save the file, and close it.

Create an RViz configuration file.

cd ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_gazebo/

mkdir rviz

Add this file to the rviz folder: yahboom_rosmaster_gazebo_sim.rviz.

Update CMakeLists.txt

Go to the CMakeLists.txt.

cd ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_gazebo/

Make sure it has this block of code:

# Copy necessary files to designated locations in the project
install (
  DIRECTORY launch models worlds rviz
  DESTINATION share/${PROJECT_NAME}
)

gedit CMakeLists.txt

Save the file, and close it.

yahboom_rosmaster.gazebo.launch.py

cd ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_gazebo/launch

Create a new file called yahboom_rosmaster.gazebo.launch.py.

Add this code.

Save the file, and close it.

Create a Bash Script for Quick Launching

Create a bash script to launch multiple launch files:

cd  ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_bringup/

mkdir scripts

Add a bash file called: rosmaster_x3_gazebo.sh.

Add this code.

Save the file, and close it.

Make it executable.

sudo chmod +x rosmaster_x3_gazebo.sh

I will add an alias for quick launch:

echo "alias x3='bash ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_bringup/scripts/rosmaster_x3_gazebo.sh'" >> ~/.bashrc && source ~/.bashrc

Make sure to update CMakeLists.txt for the yahboom_rosmaster_bringup folder.

Build the Workspace

Now let’s build the package. Open a terminal window, and type:

build

Launch Everything and Move the Robot

Now let’s launch everything.

Open a terminal window, and type the following command:

x3

bash ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_bringup/scripts/rosmaster_x3_gazebo.sh

To change the default camera view in Gazebo, we will need to use the /gui/move_to/pose service (found via gz service -l):

gz service -s /gui/move_to/pose --reqtype gz.msgs.GUICamera --reptype gz.msgs.Boolean --timeout 2000 --req "pose: {position: {x: 0.0, y: -2.0, z: 2.0} orientation: {x: -0.2706, y: 0.2706, z: 0.6533, w: 0.6533}}"

I added this command directly to the bash startup script.

Be patient. It can take up to 60 seconds to load everything.

To move the robot, type this:

ros2 topic pub /mecanum_drive_controller/cmd_vel geometry_msgs/msg/TwistStamped "{
  header: {
    stamp: {sec: `date +%s`, nanosec: 0},
    frame_id: ''
  },
  twist: {
    linear: {
      x: 0.0,
      y: 0.1,
      z: 0.0
    },
    angular: {
      x: 0.0,
      y: 0.0,
      z: 0.0
    }
  }
}"

Press CTRL + C.

Now type this:

ros2 topic pub /mecanum_drive_controller/cmd_vel geometry_msgs/msg/TwistStamped "{
  header: {
    stamp: {sec: `date +%s`, nanosec: 0},
    frame_id: ''
  },
  twist: {
    linear: {
      x: 0.0,
      y: 0.1,
      z: 0.0
    },
    angular: {
      x: 0.0,
      y: 0.0,
      z: 0.0
    }
  }
}"

Press CTRL + C.

Now stop the robot:

ros2 topic pub /mecanum_drive_controller/cmd_vel geometry_msgs/msg/TwistStamped "{
  header: {
    stamp: {sec: `date +%s`, nanosec: 0},
    frame_id: ''
  },
  twist: {
    linear: {
      x: 0.0,
      y: 0.0,
      z: 0.0
    },
    angular: {
      x: 0.0,
      y: 0.0,
      z: 0.0
    }
  }
}"

Here is the output using the empty.world file.

8-mecanum-wheel-robot-gazebo-ros2-simulation

To see a list of active topics, type:

ros2 topic list

To see a list of active topics, type:

gz topic -l

To see the options, you can type:

gz topic --help

See the active controllers:

ros2 control list_controllers

To get more information, type:

ros2 control list_controllers -v

Let’s see the information coming across some of the ROS 2 topics.

ros2 topic echo /mecanum_drive_controller/cmd_vel displays the velocity commands sent to the robot, telling it how fast and in which direction to move.

ros2 topic echo /joint_states shows the current positions (in radians) and velocities (in radians per second) of the robot’s wheels.

ros2 topic echo/mecanum_drive_controller/odom provides information about the robot’s estimated position, orientation, linear, and angular velocity based on wheel rotation data.

ros2 topic echo /imu/data outputs readings from the robot’s inertial measurement unit (IMU), which includes data about angular velocity and linear acceleration.

ros2 topic echo /scan displays data from the robot’s laser scanner or LiDAR, providing information about the distances to obstacles in the environment.

You can see the /scan data, if you go to RViz, and click the Add button in the Displays panel on the left.

Click the “By topic” tab, and scroll down to LaserScan. Click on that, and click OK to add it.

You can see the LIDAR scan data.

Here is what things look like when launching the robot in pick_and_place_demo.world. You can see how the scans match with the objects in the environment.

To see the frequency of publishing, type:

ros2 topic hz /scan

To get information about this topic, type:

ros2 topic info /scan

I also recommend checking out /cam_1/color/image_raw in RViz to see if the camera transformation for the cam_1_depth_optical_frame is oriented correctly. Compare Gazebo (on the left) to what the camera is actually seeing in ROS 2 (on the right).

Click the “By topic” tab.

Click /cam_1 -> /depth -> /color -> /points -> PointCloud2 so you can see the point cloud in RViz.

While the point cloud data shows perfectly fine in my robotic arm applications with Gazebo and RViz, I had big time rendering issues when trying to get it to display in RViz. You can see these issues in the image below. I suspect it is related to the amount of memory on my virtual machine given all the sensor data that is flowing through from Gazebo to ROS 2.

If you want to move the robot forward, type this:

ros2 topic pub /mecanum_drive_controller/cmd_vel geometry_msgs/msg/TwistStamped "{
  header: {
    stamp: {sec: `date +%s`, nanosec: 0},
    frame_id: ''
  },
  twist: {
    linear: {
      x: 0.05,
      y: 0.0,
      z: 0.0
    },
    angular: {
      x: 0.0,
      y: 0.0,
      z: 0.0
    }
  }
}"

If you want to move the robot backward, type this:


ros2 topic pub /mecanum_drive_controller/cmd_vel geometry_msgs/msg/TwistStamped "{
  header: {
    stamp: {sec: `date +%s`, nanosec: 0},
    frame_id: ''
  },
  twist: {
    linear: {
      x: -0.05,
      y: 0.0,
      z: 0.0
    },
    angular: {
      x: 0.0,
      y: 0.0,
      z: 0.0
    }
  }
}"

If you want to move the robot to the left, type this:

ros2 topic pub /mecanum_drive_controller/cmd_vel geometry_msgs/msg/TwistStamped "{
  header: {
    stamp: {sec: `date +%s`, nanosec: 0},
    frame_id: ''
  },
  twist: {
    linear: {
      x: 0.0,
      y: 0.05,
      z: 0.0
    },
    angular: {
      x: 0.0,
      y: 0.0,
      z: 0.0
    }
  }
}"

If you want to move the robot to the right, type this:

ros2 topic pub /mecanum_drive_controller/cmd_vel geometry_msgs/msg/TwistStamped "{
  header: {
    stamp: {sec: `date +%s`, nanosec: 0},
    frame_id: ''
  },
  twist: {
    linear: {
      x: 0.0,
      y: -0.05,
      z: 0.0
    },
    angular: {
      x: 0.0,
      y: 0.0,
      z: 0.0
    }
  }
}"

If you want to rotate the robot in place clockwise, type this:

ros2 topic pub /mecanum_drive_controller/cmd_vel geometry_msgs/msg/TwistStamped "{
  header: {
    stamp: {sec: `date +%s`, nanosec: 0},
    frame_id: ''
  },
  twist: {
    linear: {
      x: 0.0,
      y: 0.0,
      z: 0.0
    },
    angular: {
      x: 0.0,
      y: 0.0,
      z: -0.4
    }
  }
}"

Counter-clockwise:

ros2 topic pub /mecanum_drive_controller/cmd_vel geometry_msgs/msg/TwistStamped "{
  header: {
    stamp: {sec: `date +%s`, nanosec: 0},
    frame_id: ''
  },
  twist: {
    linear: {
      x: 0.0,
      y: 0.0,
      z: 0.0
    },
    angular: {
      x: 0.0,
      y: 0.0,
      z: 0.4
    }
  }
}"

Diagonal forward-left:

ros2 topic pub /mecanum_drive_controller/cmd_vel geometry_msgs/msg/TwistStamped "{
  header: {
    stamp: {sec: `date +%s`, nanosec: 0},
    frame_id: ''
  },
  twist: {
    linear: {
      x: 0.05,
      y: 0.05,
      z: 0.0
    },
    angular: {
      x: 0.0,
      y: 0.0,
      z: 0.0
    }
  }
}"

Diagonal forward-right:

ros2 topic pub /mecanum_drive_controller/cmd_vel geometry_msgs/msg/TwistStamped "{
  header: {
    stamp: {sec: `date +%s`, nanosec: 0},
    frame_id: ''
  },
  twist: {
    linear: {
      x: 0.05,
      y: -0.05,
      z: 0.0
    },
    angular: {
      x: 0.0,
      y: 0.0,
      z: 0.0
    }
  }
}"

Diagonal backward left:

ros2 topic pub /mecanum_drive_controller/cmd_vel geometry_msgs/msg/TwistStamped "{
  header: {
    stamp: {sec: `date +%s`, nanosec: 0},
    frame_id: ''
  },
  twist: {
    linear: {
      x: -0.05,
      y: 0.05,
      z: 0.0
    },
    angular: {
      x: 0.0,
      y: 0.0,
      z: 0.0
    }
  }
}"

Diagonal backward-right:

ros2 topic pub /mecanum_drive_controller/cmd_vel geometry_msgs/msg/TwistStamped "{
  header: {
    stamp: {sec: `date +%s`, nanosec: 0},
    frame_id: ''
  },
  twist: {
    linear: {
      x: -0.05,
      y: -0.05,
      z: 0.0
    },
    angular: {
      x: 0.0,
      y: 0.0,
      z: 0.0
    }
  }
}"

Press CTRL + C to close everything out.

Control the Robot with Code

Let’s create a ROS 2 node that can make the robot move repeatedly in a square pattern.

Let’s start by creating a program.

cd ~/ros2_ws/src/yahboom_rosmaster/yahboom_rosmaster_system_tests/src

Add a file called square_mecanum_controller.cpp.

/**
 * @file square_mecanum_controller.cpp
 * @brief Controls a mecanum wheeled robot to move in a square pattern
 *
 * This program creates a ROS 2 node that publishes velocity commands to make a
 * mecanum wheeled robot move in a square pattern. It takes advantage of the
 * omnidirectional capabilities of mecanum wheels to move in straight lines
 * along both X and Y axes.
 *
 * Publishing Topics:
 *     /mecanum_drive_controller/cmd_vel (geometry_msgs/TwistStamped):
 *         Velocity commands for the robot's motion
 *
 * @author Addison Sears-Collins
 * @date November 22, 2024
 */

#include <chrono>
#include <functional>
#include <memory>
#include "rclcpp/rclcpp.hpp"
#include "geometry_msgs/msg/twist_stamped.hpp"

using namespace std::chrono_literals;

class SquareController : public rclcpp::Node
{
public:
    SquareController() : Node("square_controller")
    {
        // Create publisher for velocity commands
        publisher_ = this->create_publisher<geometry_msgs::msg::TwistStamped>(
            "/mecanum_drive_controller/cmd_vel", 10);

        // Create timer that calls our control function every 200ms
        timer_ = this->create_wall_timer(
            200ms, std::bind(&SquareController::timer_callback, this));

        // Initialize variables
        current_side_ = 0;  // Which side of square we're on (0-3)
        elapsed_time_ = 0.0;  // Time spent on current side
        robot_speed_ = 0.2;  // Speed in meters/second
        side_length_ = 2.0;  // Length of each side in meters
        time_per_side_ = side_length_ / robot_speed_;  // Time to complete one side
    }

    // Send stop command when node is shut down
    ~SquareController()
    {
        stop_robot();
    }

    // Function to stop the robot
    void stop_robot()
    {
        auto msg = geometry_msgs::msg::TwistStamped();
        msg.header.stamp = this->now();
        publisher_->publish(msg);  // All velocities default to 0
    }

private:
    void timer_callback()
    {
        // Create velocity command message
        auto msg = geometry_msgs::msg::TwistStamped();
        msg.header.stamp = this->now();

        // Set velocity based on which side of the square we're on
        switch (current_side_) {
            case 0:  // Moving forward (positive X)
                msg.twist.linear.x = robot_speed_;
                break;
            case 1:  // Moving left (positive Y)
                msg.twist.linear.y = robot_speed_;
                break;
            case 2:  // Moving backward (negative X)
                msg.twist.linear.x = -robot_speed_;
                break;
            case 3:  // Moving right (negative Y)
                msg.twist.linear.y = -robot_speed_;
                break;
        }

        // Publish the velocity command
        publisher_->publish(msg);

        // Update time tracking
        elapsed_time_ += 0.2;  // 200ms in seconds

        // Check if we've completed the current side
        if (elapsed_time_ >= time_per_side_) {
            elapsed_time_ = 0.0;
            current_side_ = (current_side_ + 1) % 4;  // Move to next side (0-3)
        }
    }

    // Class member variables
    rclcpp::TimerBase::SharedPtr timer_;
    rclcpp::Publisher<geometry_msgs::msg::TwistStamped>::SharedPtr publisher_;
    int current_side_;
    double elapsed_time_;
    double side_length_;
    double robot_speed_;
    double time_per_side_;
};

int main(int argc, char * argv[])
{
    rclcpp::init(argc, argv);
    auto node = std::make_shared<SquareController>();
    rclcpp::spin(node);
    rclcpp::shutdown();
    return 0;
}

Update your CMakeLists.txt file and package.xml file.

build

Launch your robot in Gazebo.

x3

Now run your node:

ros2 run yahboom_rosmaster_system_tests square_mecanum_controller

Your robot will move in a pattern that resembles a square.

That’s it! You made it to the end! Congratulations!

Keep building!

How to Simulate a Robotic Arm in Gazebo – ROS 2 Jazzy

In this tutorial, we will simulate and control a robotic arm in Gazebo. I will show you how to set up and control a robotic arm using ROS 2 Control and Gazebo.

By the end of this tutorial, you will be able to build this:

Prerequisites

You have completed this tutorial: Create Launch Files to Display URDF Files – ROS 2 Jazzy
I am assuming you are using Visual Studio Code, but you can use any code editor.

All my code for this project is located here on GitHub.

What is Gazebo?

Ever wondered how robotics engineers test their robots without risking expensive hardware?

Enter Gazebo – a simulator that lets you test robots in a virtual world before building them in real life. You can work with different types of robots and connect them with ROS 2, which means your virtual tests will translate to real robots. This makes Gazebo an important tool when you’re developing and perfecting robotics projects.

What is ROS 2 Control?

Imagine you want to control a robot – maybe move its arm or make its wheels turn. You need a way for your computer programs to talk to the robot’s physical parts (like motors and sensors). This is where ROS 2 Control comes in.

ROS 2 Control is like a universal translator between:

Your control programs (the software you write)
The robot’s physical parts (the hardware)

How It Works

Where it runs:
- ROS 2 Control lives on the main computer that controls your robot
- This could be a laptop, Raspberry Pi, Intel NUC, or any computer running ROS 2
Sending Commands (Software → Hardware)
- You write a program to make the robot move
- ROS 2 Control takes these commands
- It translates them into instructions the robot’s hardware can understand
- These instructions go to devices like Arduino boards that directly control the motors
Getting Feedback (Hardware → Software)
- The robot’s sensors and motors send back information
- For example: “Motor #1 is currently at 45 degrees”
- ROS 2 Control receives this information
- It shares this data with other ROS 2 programs that need it

Real-World Example: Moving a Robotic Arm

ros2-control-mobile-manipulator-control-arch-independent_hardware

Let’s look at how ROS 2 Control works with a robotic arm that has 6 degrees of freedom (like the myCobot robotic arms) – meaning it can move in 6 different ways, just like your human arm. Each degree comes from a motor, or “joint,” that enables specific movements. Want to pick up a cup? Here’s how ROS 2 Control makes this happen:

Your Program’s Command
- You want the arm to move to pick up the cup.
- Your program (i.e. MoveIt 2) calculates all the positions each joint needs to move through to get the gripper from the starting location to the goal location around the cup.
- Your program sends a “joint trajectory” – think of it as a list of positions for each joint- to the Joint Trajectory Controller (which is part of ROS 2 Control)
- For example: “Joint 1 should move from 0° to 45°, Joint 2 from 30° to 60°, etc…”
ROS 2 Control’s Job
- The Joint Trajectory Controller gets this list of joint positions
- The Joint Trajectory Controller knows it needs to smoothly move through these positions and passes the appropriate angle values to the Hardware Interface.
- The Hardware Interface converts these angles into commands the Arduino (or some other microcontroller) can understand
- The Hardware Interface sends these commands to the microcontroller many times per second
Arduino’s Role
- Gets these commands through a USB cable
- Controls the actual motors in the robot arm
- Tells each motor exactly how fast and how far to turn
- Also reads sensors (called encoders) on each motor
Feedback Path (This is important!)
- Arduino constantly reads the sensors: “Joint 1 is at 22°, Joint 2 is at 45°…”
- Sends this information back to ROS 2 Control
- ROS 2 Control shares this with your program
- Your program can check if the arm is moving correctly
Continuous Process
- This whole cycle happens many times every second
- Your program keeps checking the arm’s position
- ROS 2 Control keeps sending updated commands
- Arduino keeps moving motors and reading sensors
- Until the arm reaches all the positions needed to pick up the cup

What ROS 2 Control Does For You

ROS 2 Control provides a standard hardware interface – think of it like a universal adapter between your software and robot hardware. With ROS 2 Control:

You only need to think about where you want the arm to move
Don’t need to worry about how to control individual motors
Can focus on the task (picking up the cup) instead of the details
Works with different types of robot arms – just change the settings
Write your robot program once
Want to switch from servo motors to stepper motors? Just update a configuration file
Change from Arduino to a different microcontroller? Just update the hardware interface
Your original program keeps working without changes
Can more easily share your code with others

A complete block diagram showing an overview of ROS 2 Control is on this page.

Real Hardware + ROS 2 Control: Following a Single Command

Let’s take a look at a more technical example of how ROS 2 Control works for a real robotics project. We will follow a joint position command as it travels through each part of ROS 2 Control, looking at exactly at the inputs and outputs at each stage. Think of it like tracking a package through the delivery system.

1. The Starting Point: Terminal Command or MoveIt 2 Action

INPUT: Your terminal command or Move It 2 action

ros2 topic pub /arm_controller/joint_trajectory trajectory_msgs/msg/JointTrajectory

OUTPUT: A ROS 2 message containing:

Joint names: [link1_to_link2, link2_to_link3, …, link6_to_link6flange]
Desired positions: [0.5, 0.2, 0.3, 0.1, 0.7, 0.0] (in radians)

2. ROS 2 Control Joint Trajectory Controller (The Message Processor)

INPUT: Exactly what we sent above

The joint names and positions from our message

OUTPUT: Command interface angle values (processed 100 times per second)

link1_to_link2/position: 0.5 radians
link2_to_link3/position: 0.2 radians
(and so on for each joint)

3. ROS 2 Control Hardware Interface (The Translator)

INPUT: Those command interface angle values

Position commands for each joint in radians

OUTPUT: A serial message to Arduino

e.g. “p <joint1_pos> <joint2_pos> <joint3_pos> …\r”
“p 1500 1200 1800 … \r”
Here, each value represents the target position of a servo in microseconds, corresponding to each joint in the arm.

4. Arduino (The Final Handler)

INPUT: The serial message from the ROS 2 Control hardware interface

OUTPUT: Motor commands

Servo1: 50.0 degrees
Servo2: 20.0 degrees
(and so on for each servo)

Gazebo + ROS 2 Control: Following a Single Command

Now that we have taken a look at what happens in a real robotics project, let’s understand how Gazebo and ROS 2 Control interact with each other by tracking the same joint command.

1. The Starting Point: Terminal Command or MoveIt 2 Action

INPUT: Your terminal command or Move It 2 action

ros2 topic pub /arm_controller/joint_trajectory trajectory_msgs/msg/JointTrajectory

OUTPUT: A ROS 2 message containing:

Joint names: [link1_to_link2, link2_to_link3, …, link6_to_link6flange]
Desired positions: [0.5, 0.2, 0.3, 0.1, 0.7, 0.0] (in radians)

2. ROS 2 Control Joint Trajectory Controller (The Message Processor)

INPUT: Exactly what we sent above

The joint names and positions from our message

OUTPUT: Command interface angle values (processed 100 times per second)

link1_to_link2/position: 0.5 radians
link2_to_link3/position: 0.2 radians
(and so on for each joint)

3. GazeboSimSystem (The Virtual Hardware Interface)

INPUT: Those command interface values

Position commands for each joint in radians

OUTPUT: Gazebo physics commands (internal to Gazebo)

SetPosition(“link1_to_link2”, 0.5)
SetPosition(“link2_to_link3”, 0.2)
(and so on for each joint)

4. Gazebo Physics Engine (The Virtual Robot)

INPUT: Physics commands for each joint

Position setpoints in radians

OUTPUT: Simulated motion

Updates joint positions in physics simulation
Considers inertia, gravity, joint limits
Provides visual feedback in Gazebo

Key Similarities Between Gazebo and Real Hardware

Control Flow: Both use the same ROS 2 Control architecture and message pipeline
Joint Interfaces: Same position/velocity/effort command and state interfaces are used
Update Rate: Both typically run control loops at similar frequencies (e.g., 50Hz, 100Hz)
Command Format: Joint commands from the software (e.g. MoveIt 2) use identical message types and coordinate systems

Key Differences Between Gazebo and Real Hardware

Communication Layer: Real hardware requires serial protocols and motor drivers, while Gazebo interfaces directly through its simulation system
Motion Physics: Real robots must handle physical wear, friction and imperfections. Gazebo uses idealized physics models
System Feedback: Real hardware relies on potentially noisy sensor data, while Gazebo provides perfect state information from its physics engine
Error Handling: Real systems need robust error detection and recovery. Gazebo simulation can ignore many real-world failure modes

The beauty of simulation is that the commands flow through almost the same path, but instead of dealing with real motors and encoders, everything happens in the physics engine. This makes testing and development safer and faster.

Each stage transforms the command into something the next stage can understand, like a series of translators working together to deliver your message to the robot.

Let’s put this knowledge into practice by setting up our own robot simulation. We’ll start by creating the necessary ROS 2 packages that will house our configuration files, launch scripts, and test code.

Create Packages

Navigate to your workspace and create the following packages. You can replace the maintainer-name and maintainer email with your own information.

cd ~/ros2_ws/src/mycobot_ros2/

ros2 pkg create --build-type ament_cmake \
                --license BSD-3-Clause \
                --maintainer-name ubuntu \
                --maintainer-email automaticaddison@todo.com \
                mycobot_bringup

ros2 pkg create --build-type ament_cmake \
                --license BSD-3-Clause \
                --maintainer-name ubuntu \
                --maintainer-email automaticaddison@todo.com \
                mycobot_gazebo

ros2 pkg create --build-type ament_cmake \
                --license BSD-3-Clause \
                --maintainer-name ubuntu \
                --maintainer-email automaticaddison@todo.com \
                mycobot_moveit_config

ros2 pkg create --build-type ament_cmake \
                --license BSD-3-Clause \
                --maintainer-name ubuntu \
                --maintainer-email automaticaddison@todo.com \
                mycobot_system_tests

Update the package.xml files for all packages, including the metapackage. Be sure to add a good description line for each.

You can also update the metapackage with the new packages you just created.

cd mycobot_ros2

gedit package.xml

<?xml version="1.0"?>
<?xml-model href="http://download.ros.org/schema/package_format3.xsd" schematypens="http://www.w3.org/2001/XMLSchema"?>
<package format="3">
  <name>mycobot_ros2</name>
  <version>0.0.0</version>
  <description>myCobot series robots by Elephant Robotics (metapackage).</description>
  <maintainer email="automaticaddison@todo.todo">ubuntu</maintainer>
  <license>BSD-3-Clause</license>
  <buildtool_depend>ament_cmake</buildtool_depend>

  <exec_depend>mycobot_bringup</exec_depend>
  <exec_depend>mycobot_description</exec_depend>
  <exec_depend>mycobot_gazebo</exec_depend>
  <exec_depend>mycobot_moveit_config</exec_depend>
  <exec_depend>mycobot_system_tests</exec_depend>

  <test_depend>ament_lint_auto</test_depend>
  <test_depend>ament_lint_common</test_depend>

  <export>
    <build_type>ament_cmake</build_type>
  </export>
</package>

Edit package.xml

Open a terminal window, and go to your package.xml folder inside the mycobot_gazebo package.

cd ~/ros2_ws/src/mycobot_ros2/mycobot_gazebo

Open the package.xml file.

Make sure it has this block:

<depend>controller_manager</depend>
<depend>gripper_controllers</depend>
<depend>gz_ros2_control</depend>
<depend>python3-numpy</depend>
<depend>rclcpp</depend>
<depend>ros_gz</depend>
<depend>ros_gz_bridge</depend>
<depend>ros_gz_image</depend>
<depend>ros_gz_sim</depend>
<depend>ros2_control</depend>
<depend>ros2_controllers</depend>
<depend>trajectory_msgs</depend>
<depend>xacro</depend>
<exec_depend>gz_ros2_control_demos</exec_depend>

controller_manager: Acts like a supervisor for all your robot’s ROS 2 controllers, making sure they work together properly.

gripper_controllers: Ready-to-use controllers that help you open and close robot grippers.

gz_ros2_control: The bridge that lets your simulated robot in Gazebo understand ROS 2 Control commands.

gz_ros2_control_demos: Example robot projects that show you how to use Gazebo with ROS 2 Control.

python3-numpy: A Python package that helps with math calculations for robotics.

rclcpp: The basic tools you need to write ROS 2 programs in C++.

ros_gz: Connects ROS 2 with the latest version of Gazebo so they can work together.

ros_gz_bridge: Helps ROS 2 and Gazebo talk to each other by translating their messages.

ros_gz_image: Handles camera images between ROS 2 and Gazebo simulation.

ros_gz_sim: The main package that lets you run robot simulations in Gazebo.

ros2_control: The main system that lets you control robots (both real and simulated) in ROS 2.

ros2_controllers: A collection of pre-made controllers for common robot movements.

trajectory_msgs: Messages that tell the robot how to move from point A to point B.

xacro: A tool that makes it easier to write and edit robot description files.

Edit CMakeLists.txt

Now open the CMakeLists.txt file, and add this block:

find_package(ament_cmake REQUIRED)
find_package(controller_manager REQUIRED)
find_package(gripper_controllers REQUIRED)
find_package(gz_ros2_control REQUIRED)
find_package(rclcpp REQUIRED)
find_package(ros_gz REQUIRED)
find_package(ros_gz_bridge REQUIRED)
find_package(ros_gz_image REQUIRED)
find_package(ros_gz_sim REQUIRED)
find_package(ros2_control REQUIRED)
find_package(ros2_controllers REQUIRED)
find_package(trajectory_msgs REQUIRED)
find_package(xacro REQUIRED)

Build the Workspace

Now let’s build our workspace.

cd ~/ros2_ws/

rosdep install -i --from-path src --rosdistro $ROS_DISTRO -y

colcon build && source ~/.bashrc

Open a terminal window, and type:

echo "alias build='cd ~/dev_ws/ && colcon build && source ~/.bashrc'" >> ~/.bashrc

Now going forward, any time you want to build you workspace, just type:

build

Test Your Installation

Let’s test our installation:

ros2 pkg list | grep gz_ros2_control

You should see:

gz_ros2_control
gz_ros2_control_demos

Run an example:

ros2 launch ros_gz_sim gz_sim.launch.py gz_args:="shapes.sdf"

Here is what you should see:

Feel free to run the other demos which you can find here on the ros_gz GitHub or here on the gz_ros2_control GitHub.

ros2 launch ros_gz_sim_demos joint_states.launch.py

When you run each demo, you can explore the topics by typing:

ros2 topic list

To run the gripper example, type:

ros2 launch gz_ros2_control_demos gripper_mimic_joint_example_effort.launch.py

To close the gripper, type:

ros2 run gz_ros2_control_demos example_gripper

You can try the differential drive mobile robot example as well:

ros2 launch gz_ros2_control_demos diff_drive_example.launch.py

To move the robot from the terminal window, you can type:

ros2 topic pub /diff_drive_base_controller/cmd_vel geometry_msgs/msg/TwistStamped "{header: {stamp: now, frame_id: 'base_link'}, twist: {linear: {x: 0.2, y: 0.0, z: 0.0}, angular: {x: 0.0, y: 0.0, z: 0.5}}}" --rate 5

To stop the robot:

ros2 topic pub /diff_drive_base_controller/cmd_vel geometry_msgs/msg/TwistStamped "{header: {stamp: now, frame_id: 'base_link'}, twist: {linear: {x: 0.0, y: 0.0, z: 0.0}, angular: {x: 0.0, y: 0.0, z: 0.0}}}" --rate 5

To move the robot using a program, type this command in another terminal window:

ros2 run gz_ros2_control_demos example_diff_drive

Create World Files

Now we will create an environment for our simulated robot.

Open a terminal window, and type:

cd ~/ros2_ws/src/mycobot_ros2/mycobot_gazebo/

Create a worlds folder and other folders we will need later:

mkdir -p worlds launch models

Now let’s create our world. The first world we will create is an empty world.

cd worlds

gedit empty.world

Add this code.

<?xml version="1.0" ?>

<sdf version="1.6">
  <world name="default">

    <!-- Plugin for simulating physics -->
    <plugin
      filename="gz-sim-physics-system"
      name="gz::sim::systems::Physics">
      <engine>
        <filename>libgz-physics-bullet-featherstone-plugin.so</filename>
      </engine>
    </plugin>

    <!-- Plugin for handling user commands -->
    <plugin
      filename="gz-sim-user-commands-system"
      name="gz::sim::systems::UserCommands">
    </plugin>

    <!-- Plugin for broadcasting scene updates -->
    <plugin
      filename="gz-sim-scene-broadcaster-system"
      name="gz::sim::systems::SceneBroadcaster">
    </plugin>

    <!-- Plugin for handling sensors like the LIDAR -->
    <plugin
      filename="gz-sim-sensors-system"
      name="gz::sim::systems::Sensors">
      <render_engine>ogre2</render_engine>
    </plugin>

    <!-- Plugin for IMU -->
    <plugin filename="gz-sim-imu-system"
      name="gz::sim::systems::Imu">
    </plugin>

    <!-- To add realistic gravity, do: 0.0 0.0 -9.8, otherwise do 0.0 0.0 0.0 -->
    <gravity>0.0 0.0 -9.8</gravity>

    <!-- Include a model of the Sun from an external URI -->
    <include>
      <uri>
        https://fuel.gazebosim.org/1.0/OpenRobotics/models/Sun
      </uri>
    </include>

    <!-- Local Ground Plane with modified friction -->
    <model name="ground_plane">
      <static>true</static>
      <link name="link">
        <collision name="collision">
          <geometry>
            <plane>
              <normal>0 0 1</normal>
            </plane>
          </geometry>
          <surface>
            <friction>
              <torsional>
                <coefficient>0.0</coefficient>
              </torsional>
            </friction>
          </surface>
        </collision>
        <visual name="visual">
          <geometry>
            <plane>
              <normal>0 0 1</normal>
              <size>100 100</size>
            </plane>
          </geometry>
          <material>
            <ambient>0.8 0.8 0.8 1</ambient>
            <diffuse>0.8 0.8 0.8 1</diffuse>
            <specular>0.8 0.8 0.8 1</specular>
          </material>
        </visual>
      </link>
    </model>

    <!-- Define scene properties -->
    <scene>
      <shadows>false</shadows>
    </scene>

  </world>
</sdf>

Save the file, and close it.

This file describes a simulated world using the Simulation Description Format (SDF) version 1.6. It defines a world named “default”.

The world includes five important plugins:

Physics System – for simulating physics
User Commands System – for handling user inputs
Scene Broadcaster System – for broadcasting scene updates
Sensors System – for handling sensors like LIDAR
IMU System – for inertial measurement unit simulation

Gravity is set to mimic Earth’s gravity, pulling objects downward.

Two models are brought into the world from external sources:

Sun, which provides light
Ground Plane, which gives a flat surface for objects to rest on.

The scene settings specify that shadows should not be rendered in this world.

This file serves as a basic template for creating a simulated environment, providing the fundamental elements needed for a functional simulation.

Now launch your Gazebo world:

cd ~/ros2_ws/src/mycobot_ros2/mycobot_gazebo/worlds/

gz sim empty.world

Press CTRL + C to close everything.

Now let’s create a world called house.world.

gedit house.world

Add this code.

Save the file, and close it.

Now add one more world. We will call it: pick_and_place_demo.world.

gedit pick_and_place_demo.world

<?xml version="1.0" ?>

<sdf version="1.7">
  <world name="default">

    <!-- Plugin for simulating physics -->
    <plugin
      filename="gz-sim-physics-system"
      name="gz::sim::systems::Physics">
      <engine>
        <filename>libgz-physics-bullet-featherstone-plugin.so</filename>
      </engine>
    </plugin>

    <!-- Plugin for handling user commands -->
    <plugin
      filename="gz-sim-user-commands-system"
      name="gz::sim::systems::UserCommands">
    </plugin>

    <!-- Plugin for broadcasting scene updates -->
    <plugin
      filename="gz-sim-scene-broadcaster-system"
      name="gz::sim::systems::SceneBroadcaster">
    </plugin>

    <!-- Plugin for sensor handling -->
    <plugin
      filename="gz-sim-sensors-system"
      name="gz::sim::systems::Sensors">
      <render_engine>ogre2</render_engine>
    </plugin>

    <!-- Plugin for IMU -->
    <plugin filename="gz-sim-imu-system"
      name="gz::sim::systems::Imu">
    </plugin>

    <!-- To add realistic gravity, do: 0.0 0.0 -9.8, otherwise do 0.0 0.0 0.0 -->
    <gravity>0.0 0.0 -9.8</gravity>

    <!-- Include a model of the Sun from an external URI -->
    <include>
      <uri>
        https://fuel.gazebosim.org/1.0/OpenRobotics/models/Sun
      </uri>
    </include>

    <!-- Local Ground Plane with modified friction -->
    <model name="ground_plane">
      <static>true</static>
      <link name="link">
        <collision name="collision">
          <geometry>
            <plane>
              <normal>0 0 1</normal>
            </plane>
          </geometry>
          <surface>
            <friction>
              <torsional>
                <coefficient>0.0</coefficient>
              </torsional>
            </friction>
          </surface>
        </collision>
        <visual name="visual">
          <geometry>
            <plane>
              <normal>0 0 1</normal>
              <size>100 100</size>
            </plane>
          </geometry>
          <material>
            <ambient>0.8 0.8 0.8 1</ambient>
            <diffuse>0.8 0.8 0.8 1</diffuse>
            <specular>0.8 0.8 0.8 1</specular>
          </material>
        </visual>
      </link>
    </model>

    <!-- Include the cylinder model -->
    <include>
      <uri>model://red_cylinder</uri>
      <name>red_cylinder</name>
      <pose>0.22 0.12 0.175 0 0 0</pose>
    </include>

    <!-- Include the other objects -->

    <include>
      <uri>model://mustard</uri>
      <pose>0.7 0.15 0.08 0 0 0</pose>
    </include>

    <include>
      <uri>model://cheezit_big_original</uri>
      <pose>0.64 0.23 0.13 1.571 0 0</pose>
    </include>

    <include>
      <uri>model://cardboard_box</uri>
      <pose>0.65 0.60 0.15 0 0 0.5</pose>
    </include>

    <include>
      <uri>model://coke_can</uri>
      <pose>0.5 0.15 0.0 0 0 2.3</pose>
    </include>

    <!-- Define scene properties -->
    <scene>
      <shadows>false</shadows>
    </scene>

  </world>
</sdf>

Now we need to add models to our models folder. Models are physical objects that will exist inside your house and pick_and_place_demo worlds. These objects include things like boxes, lamps, chairs, and tables.

Add all these models to your models folder.

Let’s walk through one of those models. We will take a look at the refrigerator model.

The refrigerator model is defined using the Simulation Description Format (SDF) version 1.6. Here’s a breakdown of its structure:

The model is named “aws_robomaker_residential_Refrigerator_01“. It contains a single link, which represents the main body of the refrigerator.

The link has three main components:

Inertial properties: A mass of 1 unit is specified, which affects how the object behaves in physical simulations.
Collision geometry: This defines the shape used for collision detection. It uses a mesh file named “aws_Refrigerator_01_collision.DAE” located in the model’s meshes directory. This mesh is a simplified version of the refrigerator’s shape for efficient collision calculations.
Visual geometry: This defines how the refrigerator looks in the simulation. It uses a separate mesh file named “aws_Refrigerator_01_visual.DAE“. This mesh is more detailed than the collision mesh to provide a realistic appearance.

Both the collision and visual meshes are scaled to 1:1:1, meaning they use their original size.

The visual component also includes a metadata tag specifying it belongs to layer 1, which is used for rendering or interaction purposes in the simulation environment.

Finally, the model is set to static, meaning it won’t move during the simulation. This is appropriate for a large appliance like a refrigerator that typically stays in one place.

This structure allows the simulation to efficiently handle both the physical interactions and visual representation of the refrigerator in the Gazebo virtual environment.

Oh and one other thing I should mention. DAE (Digital Asset Exchange) files, also known as COLLADA (COLLAborative Design Activity) files, can be created by various 3D modeling and animation software.

The DAE format is widely used in game development, virtual reality, augmented reality, and simulation environments because it’s an open standard that can store 3D assets along with their associated metadata.

For the specific refrigerator model mentioned in the SDF file, it was likely created using a 3D modeling software as part of the AWS RoboMaker residential models set. The modelers would have created both a detailed visual mesh and a simplified collision mesh, exporting each as separate DAE files for use in the simulation environment.

The model.sdf and model.config files are typically created manually using a basic text editor.

To see your house.world file in action, move to the worlds folder in the terminal.

cd ~/ros2_ws/src/mycobot_ros2/mycobot_gazebo/worlds/

Type the following command to let Gazebo know how to find the models:

export GZ_SIM_RESOURCE_PATH=/home/ubuntu/ros2_ws/src/mycobot_ros2/mycobot_gazebo/models

Now launch your Gazebo world. Be patient. It takes a while to load. If prompted, click “Wait”. Do not click “Force Quit.”

gz sim house.world

Now type:

gz sim pick_and_place_demo.world

Press CTRL + C to close.

Connect Gazebo to ROS 2 Control

Create a YAML Configuration File for the Controller Manager

The configuration file acts as a bridge between Gazebo and ROS 2, defining:

How often the controllers should update (100Hz)
Which joints can move
How these joints should move (position, velocity, etc.)
What kind of feedback the system should provide

Think of this file as a manual that tells Gazebo:

What parts of your robot can move
How they’re allowed to move
How to report back the robot’s current state

This configuration is essential because it ensures your simulated robot behaves similarly to how a real robot would respond to commands.

Open a terminal window, and type:

cd ~/ros2_ws/src/mycobot_ros2/mycobot_moveit_config/

mkdir -p config/mycobot_280

Create a new file inside the config/mycobot_280 directory called:

ros2_controllers.yaml

Add this code:

# controller_manager provides the necessary infrastructure to manage multiple controllers
# efficiently and robustly using ROS 2 Control.
controller_manager:
  ros__parameters:
    update_rate: 100 # update_rate specifies how often (in Hz) the controllers should be updated.

    # The JointTrajectoryController allows you to send joint trajectory commands to a group
    # of joints on a robot. These commands specify the desired positions for each joint.
    arm_controller:
      type: joint_trajectory_controller/JointTrajectoryController

    # Controls the gripper
    gripper_action_controller:
      type: position_controllers/GripperActionController

    # Responsible for publishing the current state of the robot's
    # joints to the /joint_states ROS 2 topic
    joint_state_broadcaster:
      type: joint_state_broadcaster/JointStateBroadcaster

# Define the parameters for each controller
arm_controller:
  ros__parameters:
    joints:
      - link1_to_link2
      - link2_to_link3
      - link3_to_link4
      - link4_to_link5
      - link5_to_link6
      - link6_to_link6_flange

    # The controller will expect position commands as input for each of these joints.
    command_interfaces:
      - position

    # Tells the controller that it should expect to receive position data as the state
    # feedback from the hardware interface.
    state_interfaces:
      - position

    # If true, When set to true, the controller will not use any feedback from the system
    # (e.g., joint positions, velocities, efforts) to compute the control commands.
    open_loop_control: false

    # When set to true, it allows the controller to integrate the trajectory goals it receives.
    # This means that if the goal trajectory only specifies positions, the controller will
    # numerically integrate the positions to compute the velocities and accelerations required
    # to follow the trajectory.
    allow_integration_in_goal_trajectories: true

    # Allow non-zero velocity at the end of the trajectory
    allow_nonzero_velocity_at_trajectory_end: true

gripper_action_controller:
  ros__parameters:
    joint: gripper_controller
    action_monitor_rate: 20.0
    goal_tolerance: 0.01
    max_effort: 100.0
    allow_stalling: false
    stall_velocity_threshold: 0.001
    stall_timeout: 1.0

Save the file, and close it.

Create a new file inside the config/mycobot_280 directory called:

ros2_controllers_template.yaml

# controller_manager provides the necessary infrastructure to manage multiple controllers
# efficiently and robustly using ROS 2 Control.
controller_manager:
  ros__parameters:
    update_rate: 100 # update_rate specifies how often (in Hz) the controllers should be updated.

    # The JointTrajectoryController allows you to send joint trajectory commands to a group
    # of joints on a robot. These commands specify the desired positions for each joint.
    arm_controller:
      type: joint_trajectory_controller/JointTrajectoryController

    # Controls the gripper
    gripper_action_controller:
      type: position_controllers/GripperActionController

    # Responsible for publishing the current state of the robot's
    # joints to the /joint_states ROS 2 topic
    joint_state_broadcaster:
      type: joint_state_broadcaster/JointStateBroadcaster

# Define the parameters for each controller
arm_controller:
  ros__parameters:
    joints:
      - ${prefix}link1_to_${prefix}link2
      - ${prefix}link2_to_${prefix}link3
      - ${prefix}link3_to_${prefix}link4
      - ${prefix}link4_to_${prefix}link5
      - ${prefix}link5_to_${prefix}link6
      - ${prefix}link6_to_${prefix}${flange_link}

    # The controller will expect position commands as input for each of these joints.
    command_interfaces:
      - position

    # Tells the controller that it should expect to receive position data as the state
    # feedback from the hardware interface.
    state_interfaces:
      - position

    # If true, When set to true, the controller will not use any feedback from the system
    # (e.g., joint positions, velocities, efforts) to compute the control commands.
    open_loop_control: false

    # When set to true, it allows the controller to integrate the trajectory goals it receives.
    # This means that if the goal trajectory only specifies positions, the controller will
    # numerically integrate the positions to compute the velocities and accelerations required
    # to follow the trajectory.
    allow_integration_in_goal_trajectories: true

    # Allow non-zero velocity at the end of the trajectory
    allow_nonzero_velocity_at_trajectory_end: true

gripper_action_controller:
  ros__parameters:
    joint: ${prefix}gripper_controller
    action_monitor_rate: 20.0
    goal_tolerance: 0.01
    max_effort: 100.0
    allow_stalling: false
    stall_velocity_threshold: 0.001
    stall_timeout: 1.0

This file will help us substitute a prefix (e.g. “left” or “right”) should we desire, for example.

Update CMakeLists.txt with the new config folder. Here is CMakeLists.txt for the mycobot_moveit_config package.

cmake_minimum_required(VERSION 3.8)
project(mycobot_moveit_config)

if(CMAKE_COMPILER_IS_GNUCXX OR CMAKE_CXX_COMPILER_ID MATCHES "Clang")
  add_compile_options(-Wall -Wextra -Wpedantic)
endif()

# find dependencies
find_package(ament_cmake REQUIRED)
# uncomment the following section in order to fill in
# further dependencies manually.
# find_package(<dependency> REQUIRED)

# Copy necessary files to designated locations in the project
install (
  DIRECTORY config launch
  DESTINATION share/${PROJECT_NAME}
)

if(BUILD_TESTING)
  find_package(ament_lint_auto REQUIRED)
  # the following line skips the linter which checks for copyrights
  # comment the line when a copyright and license is added to all source files
  set(ament_cmake_copyright_FOUND TRUE)
  # the following line skips cpplint (only works in a git repo)
  # comment the line when this package is in a git repo and when
  # a copyright and license is added to all source files
  set(ament_cmake_cpplint_FOUND TRUE)
  ament_lint_auto_find_test_dependencies()
endif()

ament_package()

Also update mycobot_desciption/launch/robot_state_publisher.py with the relevant part to handle the finding and replacing.

#!/usr/bin/env python3
"""
Launch RViz visualization for the mycobot robot.

This launch file sets up the complete visualization environment for the mycobot robot,
including robot state publisher, joint state publisher, and RViz2. It handles loading
and processing of URDF/XACRO files and controller configurations.

:author: Addison Sears-Collins
:date: November 15, 2024
"""
import os
from pathlib import Path
from launch import LaunchDescription
from launch.actions import DeclareLaunchArgument, OpaqueFunction
from launch.conditions import IfCondition, UnlessCondition
from launch.substitutions import Command, LaunchConfiguration, PathJoinSubstitution
from launch_ros.actions import Node
from launch_ros.parameter_descriptions import ParameterValue
from launch_ros.substitutions import FindPackageShare


def process_ros2_controllers_config(context):
    """Process the ROS 2 controller configuration yaml file before loading the URDF.

    This function reads a template configuration file, replaces placeholder values
    with actual configuration, and writes the processed file to both source and
    install directories.

    Args:
        context: Launch context containing configuration values

    Returns:
        list: Empty list as required by OpaqueFunction
    """

    # Get the configuration values
    prefix = LaunchConfiguration('prefix').perform(context)
    flange_link = LaunchConfiguration('flange_link').perform(context)
    robot_name = LaunchConfiguration('robot_name').perform(context)

    home = str(Path.home())

    # Define both source and install paths
    src_config_path = os.path.join(
        home,
        'ros2_ws/src/mycobot_ros2/mycobot_moveit_config/config',
        robot_name
    )
    install_config_path = os.path.join(
        home,
        'ros2_ws/install/mycobot_moveit_config/share/mycobot_moveit_config/config',
        robot_name
    )

    # Read from source template
    template_path = os.path.join(src_config_path, 'ros2_controllers_template.yaml')
    with open(template_path, 'r', encoding='utf-8') as file:
        template_content = file.read()

    # Create processed content (leaving template untouched)
    processed_content = template_content.replace('${prefix}', prefix)
    processed_content = processed_content.replace('${flange_link}', flange_link)

    # Write processed content to both source and install directories
    for config_path in [src_config_path, install_config_path]:
        os.makedirs(config_path, exist_ok=True)
        output_path = os.path.join(config_path, 'ros2_controllers.yaml')
        with open(output_path, 'w', encoding='utf-8') as file:
            file.write(processed_content)

    return []


# Define the arguments for the XACRO file
ARGUMENTS = [
    DeclareLaunchArgument('robot_name', default_value='mycobot_280',
                          description='Name of the robot'),
    DeclareLaunchArgument('prefix', default_value='',
                          description='Prefix for robot joints and links'),
    DeclareLaunchArgument('add_world', default_value='true',
                          choices=['true', 'false'],
                          description='Whether to add world link'),
    DeclareLaunchArgument('base_link', default_value='base_link',
                          description='Name of the base link'),
    DeclareLaunchArgument('base_type', default_value='g_shape',
                          description='Type of the base'),
    DeclareLaunchArgument('flange_link', default_value='link6_flange',
                          description='Name of the flange link'),
    DeclareLaunchArgument('gripper_type', default_value='adaptive_gripper',
                          description='Type of the gripper'),
    DeclareLaunchArgument('use_gazebo', default_value='false',
                          choices=['true', 'false'],
                          description='Whether to use Gazebo simulation'),
    DeclareLaunchArgument('use_gripper', default_value='true',
                          choices=['true', 'false'],
                          description='Whether to attach a gripper')
]


def generate_launch_description():
    """Generate the launch description for the mycobot robot visualization.

    This function sets up all necessary nodes and parameters for visualizing
    the mycobot robot in RViz, including:
    - Robot state publisher for broadcasting transforms
    - Joint state publisher for simulating joint movements
    - RViz for visualization

    Returns:
        LaunchDescription: Complete launch description for the visualization setup
    """
    # Define filenames
    urdf_package = 'mycobot_description'
    urdf_filename = 'mycobot_280.urdf.xacro'
    rviz_config_filename = 'mycobot_280_description.rviz'

    # Set paths to important files
    pkg_share_description = FindPackageShare(urdf_package)
    default_urdf_model_path = PathJoinSubstitution(
        [pkg_share_description, 'urdf', 'robots', urdf_filename])
    default_rviz_config_path = PathJoinSubstitution(
        [pkg_share_description, 'rviz', rviz_config_filename])

    # Launch configuration variables
    jsp_gui = LaunchConfiguration('jsp_gui')
    rviz_config_file = LaunchConfiguration('rviz_config_file')
    urdf_model = LaunchConfiguration('urdf_model')
    use_rviz = LaunchConfiguration('use_rviz')
    use_sim_time = LaunchConfiguration('use_sim_time')

    # Declare the launch arguments
    declare_jsp_gui_cmd = DeclareLaunchArgument(
        name='jsp_gui',
        default_value='true',
        choices=['true', 'false'],
        description='Flag to enable joint_state_publisher_gui')

    declare_rviz_config_file_cmd = DeclareLaunchArgument(
        name='rviz_config_file',
        default_value=default_rviz_config_path,
        description='Full path to the RVIZ config file to use')

    declare_urdf_model_path_cmd = DeclareLaunchArgument(
        name='urdf_model',
        default_value=default_urdf_model_path,
        description='Absolute path to robot urdf file')

    declare_use_rviz_cmd = DeclareLaunchArgument(
        name='use_rviz',
        default_value='true',
        description='Whether to start RVIZ')

    declare_use_sim_time_cmd = DeclareLaunchArgument(
        name='use_sim_time',
        default_value='false',
        description='Use simulation (Gazebo) clock if true')

    robot_description_content = ParameterValue(Command([
        'xacro', ' ', urdf_model, ' ',
        'robot_name:=', LaunchConfiguration('robot_name'), ' ',
        'prefix:=', LaunchConfiguration('prefix'), ' ',
        'add_world:=', LaunchConfiguration('add_world'), ' ',
        'base_link:=', LaunchConfiguration('base_link'), ' ',
        'base_type:=', LaunchConfiguration('base_type'), ' ',
        'flange_link:=', LaunchConfiguration('flange_link'), ' ',
        'gripper_type:=', LaunchConfiguration('gripper_type'), ' ',
        'use_gazebo:=', LaunchConfiguration('use_gazebo'), ' ',
        'use_gripper:=', LaunchConfiguration('use_gripper')
    ]), value_type=str)

    # Subscribe to the joint states of the robot, and publish the 3D pose of each link.
    start_robot_state_publisher_cmd = Node(
        package='robot_state_publisher',
        executable='robot_state_publisher',
        name='robot_state_publisher',
        output='screen',
        parameters=[{
            'use_sim_time': use_sim_time,
            'robot_description': robot_description_content}])

    # Publish the joint state values for the non-fixed joints in the URDF file.
    start_joint_state_publisher_cmd = Node(
        package='joint_state_publisher',
        executable='joint_state_publisher',
        name='joint_state_publisher',
        parameters=[{'use_sim_time': use_sim_time}],
        condition=UnlessCondition(jsp_gui))

    # Depending on gui parameter, either launch joint_state_publisher or joint_state_publisher_gui
    start_joint_state_publisher_gui_cmd = Node(
        package='joint_state_publisher_gui',
        executable='joint_state_publisher_gui',
        name='joint_state_publisher_gui',
        parameters=[{'use_sim_time': use_sim_time}],
        condition=IfCondition(jsp_gui))

    # Launch RViz
    start_rviz_cmd = Node(
        condition=IfCondition(use_rviz),
        package='rviz2',
        executable='rviz2',
        name='rviz2',
        output='screen',
        arguments=['-d', rviz_config_file],
        parameters=[{'use_sim_time': use_sim_time}])

    # Create the launch description and populate
    ld = LaunchDescription(ARGUMENTS)

    # Process the controller configuration before starting nodes
    ld.add_action(OpaqueFunction(function=process_ros2_controllers_config))

    # Declare the launch options
    ld.add_action(declare_jsp_gui_cmd)
    ld.add_action(declare_rviz_config_file_cmd)
    ld.add_action(declare_urdf_model_path_cmd)
    ld.add_action(declare_use_rviz_cmd)
    ld.add_action(declare_use_sim_time_cmd)

    # Add any actions
    ld.add_action(start_joint_state_publisher_cmd)
    ld.add_action(start_joint_state_publisher_gui_cmd)
    ld.add_action(start_robot_state_publisher_cmd)
    ld.add_action(start_rviz_cmd)

    return ld

Let’s discuss the key components of the configuration files.

Controller Manager

The controller manager acts as the central orchestrator, running at 100Hz to manage multiple controllers simultaneously. This high update rate ensures smooth motion control and responsive behavior of the robot.

Arm Controller (JointTrajectoryController)

This controller handles the coordinated motion of the robot’s six-axis arm. It uses a joint trajectory controller implementation, which means it can process complex movement paths while maintaining synchronization between joints. The controller operates in closed-loop mode (open_loop_control: false), utilizing position feedback to ensure accurate movement.

The arm configuration shows six joints, connecting from link1 through to the flange link. Each joint accepts position commands and reports back its current position state. The controller supports trajectory integration, meaning it can calculate required velocities and accelerations from position-only commands, and allows for trajectories that end with non-zero velocities.

Gripper Controller

The gripper uses a position-based action controller, monitoring its state at 20Hz. It includes practical safety features like:

A goal tolerance of 0.01 units
Maximum effort limit of 100 units
Stall detection (if movement falls below 0.001 units/s for more than 1 second)

Joint State Broadcaster

This component publishes the real-time state of all joints to ROS 2’s joint_states topic, enabling other nodes in the system to monitor the robot’s current configuration. This is important for tasks like collision checking, visualization, and coordinated motion planning.

The configuration uses parameter substitution (indicated by ${prefix}) to allow for flexible naming schemes, which is particularly useful when deploying the same configuration across different robot instances or configurations.

Each controller is defined with specific interfaces for commands and state feedback, establishing a clear contract for how the controller interacts with the hardware layer of the robot.

Create the XACRO/URDF Files

Next, we need to add two essential XACRO/URDF files that bridge Gazebo simulation with ROS 2 Control. These files work alongside your controller configuration YAML file to create a complete control system.

The first file creates a connection between Gazebo and ROS 2 control:

gazebo_sim_ros2_control.urdf.xacro

The second file is the instruction manual for using that connection:

mycobot_280_ros2_control.urdf.xacro

Without the first file, Gazebo wouldn’t know to use ROS 2 Control. Without the second file, ROS 2 Control wouldn’t know how to control the robot’s joints.

gazebo_sim_ros2_control.urdf.xacro

Loads the Gazebo ROS 2 Control plugin
Points Gazebo to your controller settings file (mycobot_280_controllers.yaml)
Makes sure ROS 2 and Gazebo can communicate properly
Think of this as the “middle man” between Gazebo and ROS 2 Control
Without this file, Gazebo wouldn’t know to accept ROS 2 commands

Open a terminal window.

Type the following command:

cd ~/ros2_ws/src/mycobot_ros2/mycobot_description/urdf/

mkdir control

Create the file named:

gazebo_sim_ros2_control.urdf.xacro

Add this code.

<?xml version="1.0" ?>
<robot xmlns:xacro="http://wiki.ros.org/xacro">
    <xacro:macro name="load_gazebo_sim_ros2_control_plugin" params="robot_name use_gazebo">
        <xacro:if value="${use_gazebo}">
            <gazebo>
                <plugin filename="gz_ros2_control-system" name="gz_ros2_control::GazeboSimROS2ControlPlugin">
                    <parameters>$(find mycobot_moveit_config)/config/${robot_name}/ros2_controllers.yaml</parameters>
                    <ros>
                        <remapping>/controller_manager/robot_description:=/robot_description</remapping>
                    </ros>
                </plugin>
            </gazebo>
        </xacro:if>
    </xacro:macro>
</robot>

Save the file, and close it.

mycobot_280_ros2_control.urdf.xacro:

The main robot control “instruction manual”
Sets up two important interfaces for each joint:
- Command interface: How you send desired angles to each joint (like “move to 45 degrees”)
- State interface: How you read back what angle each joint is currently at
Defines safe movement limits for each joint
Tells the gripper joints how to move together (mimic joints)
Think of this as defining “what each part can do and how to do it”

Open a terminal window.

Type the following command:

cd ~/ros2_ws/src/mycobot_ros2/mycobot_description/urdf/control

Create the file named:

mycobot_280_ros2_control.urdf.xacro

Add this code.

<?xml version="1.0" ?>
<robot xmlns:xacro="http://wiki.ros.org/xacro">

    <xacro:macro name="mycobot_ros2_control" params="prefix flange_link use_gazebo">
        <ros2_control name="RobotSystem" type="system">
            <hardware>
                <xacro:if value="${use_gazebo}">
                    <plugin>gz_ros2_control/GazeboSimSystem</plugin>
                </xacro:if>
            </hardware>

            <joint name="${prefix}link1_to_${prefix}link2">
                <command_interface name="position">
                    <param name="min">-2.879793</param>
                    <param name="max">2.879793</param>
                </command_interface>
                <state_interface name="position"/>
            </joint>

            <joint name="${prefix}link2_to_${prefix}link3">
                <command_interface name="position">
                    <param name="min">-2.879793</param>
                    <param name="max">2.879793</param>
                </command_interface>
                <state_interface name="position"/>
            </joint>

            <joint name="${prefix}link3_to_${prefix}link4">
                <command_interface name="position">
                    <param name="min">-2.879793</param>
                    <param name="max">2.879793</param>
                </command_interface>
                <state_interface name="position"/>
            </joint>

            <joint name="${prefix}link4_to_${prefix}link5">
                <command_interface name="position">
                    <param name="min">-2.879793</param>
                    <param name="max">2.879793</param>
                </command_interface>
                <state_interface name="position"/>
            </joint>

            <joint name="${prefix}link5_to_${prefix}link6">
                <command_interface name="position">
                    <param name="min">-2.879793</param>
                    <param name="max">2.879793</param>
                </command_interface>
                <state_interface name="position"/>
            </joint>

            <joint name="${prefix}link6_to_${prefix}${flange_link}">
                <command_interface name="position">
                    <param name="min">-3.05</param>
                    <param name="max">3.05</param>
                </command_interface>
                <state_interface name="position"/>
            </joint>

            <joint name="${prefix}gripper_controller">
                <command_interface name="position">
                    <param name="min">-0.7</param>
                    <param name="max">0.15</param>
                </command_interface>
                <state_interface name="position"/>
                <state_interface name="velocity"/>
            </joint>

            <joint name="${prefix}gripper_base_to_${prefix}gripper_left2">
                <param name="mimic">gripper_controller</param>
                <param name="multiplier">1.0</param>
                <state_interface name="position"/>
                <state_interface name="velocity"/>
            </joint>

            <joint name="${prefix}gripper_left3_to_${prefix}gripper_left1">
                <param name="mimic">gripper_controller</param>
                <param name="multiplier">-1.0</param>
                <state_interface name="position"/>
                <state_interface name="velocity"/>
            </joint>

            <joint name="${prefix}gripper_base_to_${prefix}gripper_right3">
                <param name="mimic">gripper_controller</param>
                <param name="multiplier">-1.0</param>
                <state_interface name="position"/>
                <state_interface name="velocity"/>
            </joint>

            <joint name="${prefix}gripper_base_to_${prefix}gripper_right2">
                <param name="mimic">gripper_controller</param>
                <state_interface name="position"/>
                <state_interface name="velocity"/>
            </joint>

            <joint name="${prefix}gripper_right3_to_${prefix}gripper_right1">
                <param name="mimic">gripper_controller</param>
                <param name="multiplier">1.0</param>
                <state_interface name="position"/>
                <state_interface name="velocity"/>
            </joint>

        </ros2_control>
    </xacro:macro>

</robot>

Save the file, and close it.

Include the Files in mycobot_280.urdf.xacro

Next we need to include these files inside mycobot_280.urdf.xacro.

cd ~/ros2_ws/src/mycobot_ros2/mycobot_description/urdf/robots/

Open the mycobot_280_urdf.xacro file.

Add this code at the bottom of the file:

    <xacro:include filename="$(find mycobot_description)/urdf/control/gazebo_sim_ros2_control.urdf.xacro" />
    <xacro:load_gazebo_sim_ros2_control_plugin
      robot_name="$(arg robot_name)"
      use_gazebo="$(arg use_gazebo)"/>

   <xacro:include filename="$(find mycobot_description)/urdf/control/mycobot_280_ros2_control.urdf.xacro" />
    <xacro:mycobot_ros2_control
      prefix="$(arg prefix)"
      flange_link="$(arg flange_link)"
      use_gazebo="$(arg use_gazebo)"/>

Create the Launch Files

Now let’s create the launch files.

load_ros2_controllers.launch.py

cd  ~/ros2_ws/src/mycobot_ros2/mycobot_moveit_config/

mkdir launch

cd launch

Add this code called load_ros2_controllers.launch.py:

#!/usr/bin/env python3
"""
Launch ROS 2 controllers for the robot.

This script creates a launch description that starts the necessary controllers
for operating the robotic arm and gripper in a specific sequence.

Launched Controllers:
    1. Joint State Broadcaster: Publishes joint states to /joint_states
    2. Arm Controller: Controls the robot arm movements via /follow_joint_trajectory
    3. Gripper Action Controller: Controls gripper actions via /gripper_action

Launch Sequence:
    1. Joint State Broadcaster
    2. Arm Controller (starts after Joint State Broadcaster)
    3. Gripper Action Controller (starts after Arm Controller)

:author: Addison Sears-Collins
:date: November 15, 2024
"""

from launch import LaunchDescription
from launch.actions import ExecuteProcess, RegisterEventHandler
from launch.event_handlers import OnProcessExit


def generate_launch_description():
    """Generate a launch description for sequentially starting robot controllers.

    Returns:
        LaunchDescription: Launch description containing sequenced controller starts
    """
    # Start arm controller
    start_arm_controller_cmd = ExecuteProcess(
        cmd=['ros2', 'control', 'load_controller', '--set-state', 'active',
             'arm_controller'],
        output='screen')

    # Start gripper action controller
    start_gripper_action_controller_cmd = ExecuteProcess(
        cmd=['ros2', 'control', 'load_controller', '--set-state', 'active',
             'gripper_action_controller'],
        output='screen')

    # Launch joint state broadcaster
    start_joint_state_broadcaster_cmd = ExecuteProcess(
        cmd=['ros2', 'control', 'load_controller', '--set-state', 'active',
             'joint_state_broadcaster'],
        output='screen')

    # Register event handlers for sequencing
    # Launch the joint state broadcaster after spawning the robot
    load_joint_state_broadcaster_cmd = RegisterEventHandler(
        event_handler=OnProcessExit(
            target_action=start_joint_state_broadcaster_cmd,
            on_exit=[start_arm_controller_cmd]))

    # Launch the arm controller after launching the joint state broadcaster
    load_arm_controller_cmd = RegisterEventHandler(
        event_handler=OnProcessExit(
            target_action=start_arm_controller_cmd,
            on_exit=[start_gripper_action_controller_cmd]))

    # Create the launch description and populate
    ld = LaunchDescription()

    # Add the actions to the launch description in sequence
    ld.add_action(start_joint_state_broadcaster_cmd)
    ld.add_action(load_joint_state_broadcaster_cmd)
    ld.add_action(load_arm_controller_cmd)

    return ld

Update CMakeLists.txt for the mycobot_moveit_config package to include the new launch folder. Make sure the block below, looks like this:

# Copy necessary files to designated locations in the project
install (
  DIRECTORY config launch
  DESTINATION share/${PROJECT_NAME}
)

mycobot.gazebo.launch.py

cd ~/ros2_ws/src/mycobot_ros2/mycobot_gazebo/launch

Create a new file called mycobot.gazebo.launch.py.

Add this code, and save the file.

Create a Bash Script for Quick Launching

Create a bash script to launch multiple launch files:

cd  ~/ros2_ws/src/mycobot_ros2/mycobot_bringup/

mkdir scripts

Add a bash file called: mycobot_280_gazebo.sh.

Add this code:

#!/bin/bash
# Single script to launch the myCobot with Gazebo and ROS 2 Controllers

cleanup() {
    echo "Cleaning up..."
    sleep 5.0
    pkill -9 -f "ros2|gazebo|gz|nav2|amcl|bt_navigator|nav_to_pose|rviz2|assisted_teleop|cmd_vel_relay|robot_state_publisher|joint_state_publisher|move_to_free|mqtt|autodock|cliff_detection|moveit|move_group|basic_navigator"
}

# Set up cleanup trap
trap 'cleanup' SIGINT SIGTERM

echo "Launching Gazebo simulation..."
ros2 launch mycobot_gazebo mycobot.gazebo.launch.py \
    load_controllers:=true \
    world_file:=pick_and_place_demo.world \
    use_rviz:=true \
    use_robot_state_pub:=true \
    use_sim_time:=true \
    x:=0.0 \
    y:=0.0 \
    z:=0.05 \
    roll:=0.0 \
    pitch:=0.0 \
    yaw:=0.0

Save the file, and close it.

Make it executable.

sudo chmod +x mycobot_280_gazebo.sh

I will add an alias for quick launch:

echo "alias robot='bash ~/ros2_ws/src/mycobot_ros2/mycobot_bringup/scripts/mycobot_280_gazebo.sh'" >> ~/.bashrc && source ~/.bashrc

Make sure to update CMakeLists.txt for the mycobot_bringup folder.

Update CMakeLists.txt

Go to the CMakeLists.txt.

cd ~/ros2_ws/src/mycobot_ros2/mycobot_gazebo/

Make sure it has this block of code:

# Copy necessary files to designated locations in the project
install (
  DIRECTORY launch models worlds
  DESTINATION share/${PROJECT_NAME}
)

gedit CMakeLists.txt

Save the file, and close it.

Build the Workspace

Now let’s build the package. Open a terminal window, and type:

build

Launch Everything and Move the Arm

Now let’s launch everything.

Open a terminal window, and type the following command:

robot

bash ~/ros2_ws/src/mycobot_ros2/mycobot_bringup/scripts/mycobot_280_gazebo.sh

Here is the output using the empty.world file:

To see a list of active Gazebo topics, type:

gz topic -l

To see the options, you can type:

gz topic -help

See the active controllers:

ros2 control list_controllers

To get more information, type:

ros2 control list_controllers -v

If you want to close the gripper, you can do this:

ros2 action send_goal /gripper_action_controller/gripper_cmd control_msgs/action/GripperCommand "{command: {position: -0.7, max_effort: 5.0}}"

If you want to open the gripper, you can do this:

ros2 action send_goal /gripper_action_controller/gripper_cmd control_msgs/action/GripperCommand "{command: {position: 0.0, max_effort: 5.0}}"

Deactivate the gripper_action_controller (which uses the position_controllers/GripperActionController interface…we will use this in a later tutorial)

ros2 control set_controller_state gripper_action_controller inactive

To see a list of all the commands you can use type:

ros2 control

Then press Tab twice.

List all the available hardware components that are loaded and ready to be used by the ros2_control controller manager.

ros2 control list_hardware_components

Now let’s send a command to the robotic arm to move it.

Let’s check out the topics:

ros2 topic list

We need this topic: /arm_controller/joint_trajectory

We can publish a trajectory to that topic to move the arm. Let’s get more information about the topic:

ros2 topic info /arm_controller/joint_trajectory

We need we to publish a message of type:

trajectory_msgs/msg/JointTrajectory

Remember, here were the list of joints that are controlled by the arm_controller:

link1_to_link2
link2_to_link3
link3_to_link4
link4_to_link5
link5_to_link6
link6_to_link6_flange

There are 6 joints in total.

Here is a command you can use to move the arm (this is all a single command):

ros2 topic pub --once /arm_controller/joint_trajectory trajectory_msgs/msg/JointTrajectory "{joint_names: ['link1_to_link2', 'link2_to_link3', 'link3_to_link4', 'link4_to_link5', 'link5_to_link6', 'link6_to_link6_flange'], points: [{positions: [1.345, -1.23, 0.264, -0.296, 0.389, -1.5], time_from_start: {sec: 3.0, nanosec: 0}}]}"

ros2 action send_goal /arm_controller/follow_joint_trajectory control_msgs/action/FollowJointTrajectory "{
  trajectory: {
    joint_names: ['link1_to_link2', 'link2_to_link3', 'link3_to_link4', 'link4_to_link5', 'link5_to_link6', 'link6_to_link6_flange'],
    points: [{
      positions: [1.345, -1.23, 0.264, -0.296, 0.389, -1.5],
      velocities: [],
      accelerations: [],
      effort: [],
      time_from_start: {sec: 3, nanosec: 0}
    }]
  }
}"

You can also move it back home now:

ros2 topic pub --once /arm_controller/joint_trajectory trajectory_msgs/msg/JointTrajectory "{joint_names: ['link1_to_link2', 'link2_to_link3', 'link3_to_link4', 'link4_to_link5', 'link5_to_link6', 'link6_to_link6_flange'], points: [{positions: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0], time_from_start: {sec: 1.5, nanosec: 0}}]}"

ros2 action send_goal /arm_controller/follow_joint_trajectory control_msgs/action/FollowJointTrajectory "{
  trajectory: {
    joint_names: ['link1_to_link2', 'link2_to_link3', 'link3_to_link4', 'link4_to_link5', 'link5_to_link6', 'link6_to_link6_flange'],
    points: [{
      positions: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
      velocities: [],
      accelerations: [],
      effort: [],
      time_from_start: {sec: 1, nanosec: 500000000}
    }]
  }
}"

Move the Robotic Arm Using Code

Let’s create a ROS 2 node that can loop through a list of trajectories to simulate the arm moving from the home position to a goal location and then back to home.

Python

Let’s start by creating a script using Python.

cd ~/ros2_ws/src/mycobot_ros2/mycobot_system_tests/

mkdir scripts

Create a new file called: arm_gripper_loop_controller.py

#!/usr/bin/env python3
"""
Control robot arm and gripper to perform repetitive movements between positions.

This script creates a ROS 2 node that moves a robot arm between target and home positions,
coordinating with gripper actions (open/close) at each position. The movement happens
in a continuous loop.

Action Clients:
    /arm_controller/follow_joint_trajectory (control_msgs/FollowJointTrajectory):
        Commands for controlling arm joint positions
    /gripper_action_controller/gripper_cmd (control_msgs/GripperCommand):
        Commands for opening and closing the gripper

:author: Addison Sears-Collins
:date: November 15, 2024
"""

import time
import rclpy
from rclpy.node import Node
from rclpy.action import ActionClient
from control_msgs.action import FollowJointTrajectory, GripperCommand
from trajectory_msgs.msg import JointTrajectoryPoint
from builtin_interfaces.msg import Duration


class ArmGripperLoopController(Node):
    """
    A ROS 2 node for controlling robot arm movements and gripper actions.

    This class creates a simple control loop that:
    1. Moves the arm to a target position
    2. Closes the gripper
    3. Returns the arm to home position
    4. Opens the gripper
    """

    def __init__(self):
        """
        Initialize the node and set up action clients for arm and gripper control.

        Sets up two action clients:
        - One for controlling arm movements
        - One for controlling gripper open/close actions
        Also defines the positions for movement and starts a timer for the control loop.
        """
        super().__init__('arm_gripper_loop_controller')

        # Set up arm trajectory action client for arm movement control
        self.arm_client = ActionClient(
            self,
            FollowJointTrajectory,
            '/arm_controller/follow_joint_trajectory'
        )

        # Set up gripper action client for gripper control
        self.gripper_client = ActionClient(
            self,
            GripperCommand,
            '/gripper_action_controller/gripper_cmd'
        )

        # Wait for both action servers to be available
        self.get_logger().info('Waiting for action servers...')
        self.arm_client.wait_for_server()
        self.gripper_client.wait_for_server()
        self.get_logger().info('Action servers connected!')

        # List of joint names for the robot arm
        self.joint_names = [
            'link1_to_link2', 'link2_to_link3', 'link3_to_link4',
            'link4_to_link5', 'link5_to_link6', 'link6_to_link6_flange'
        ]

        # Define target and home positions for the arm
        self.target_pos = [1.345, -1.23, 0.264, -0.296, 0.389, -1.5]
        self.home_pos = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0]

        # Create timer that triggers the control loop quickly after start (0.1 seconds)
        self.create_timer(0.1, self.control_loop_callback)

    def send_arm_command(self, positions: list) -> None:
        """
        Send a command to move the robot arm to specified joint positions.

        Args:
            positions (list): List of 6 joint angles in radians
        """
        # Create a trajectory point with the target positions
        point = JointTrajectoryPoint()
        point.positions = positions
        point.time_from_start = Duration(sec=2)  # Allow 2 seconds for movement

        # Create and send the goal message
        goal_msg = FollowJointTrajectory.Goal()
        goal_msg.trajectory.joint_names = self.joint_names
        goal_msg.trajectory.points = [point]

        self.arm_client.send_goal_async(goal_msg)

    def send_gripper_command(self, position: float) -> None:
        """
        Send a command to the gripper to open or close.

        Args:
            position (float): Position value for gripper (0.0 for open, -0.7 for closed)
        """
        # Create and send the gripper command
        goal_msg = GripperCommand.Goal()
        goal_msg.command.position = position
        goal_msg.command.max_effort = 5.0

        self.gripper_client.send_goal_async(goal_msg)

    def control_loop_callback(self) -> None:
        """
        Execute one cycle of the control loop.

        This method performs the following sequence:
        1. Move arm to target position
        2. Pause at target
        3. Close gripper
        4. Move arm to home position
        5. Pause at home
        6. Open gripper
        7. Pause before next cycle
        """
        # Move to target position
        self.get_logger().info('Moving to target position')
        self.send_arm_command(self.target_pos)
        time.sleep(2.5)  # Wait for arm to reach target (2.5s)

        # Pause at target position
        self.get_logger().info('Reached target position - Pausing')
        time.sleep(1.0)  # Pause for 1 second at target

        # Close gripper
        self.get_logger().info('Closing gripper')
        self.send_gripper_command(-0.7)  # Close gripper
        time.sleep(0.5)  # Wait for gripper to close

        # Move to home position
        self.get_logger().info('Moving to home position')
        self.send_arm_command(self.home_pos)
        time.sleep(2.5)  # Wait for arm to reach home (2.5s)

        # Pause at home position
        self.get_logger().info('Reached home position - Pausing')
        time.sleep(1.0)  # Pause for 1 second at home

        # Open gripper
        self.get_logger().info('Opening gripper')
        self.send_gripper_command(0.0)  # Open gripper
        time.sleep(0.5)  # Wait for gripper to open

        # Final pause before next cycle
        time.sleep(1.0)


def main(args=None):
    """
    Initialize and run the arm gripper control node.

    Args:
        args: Command-line arguments (default: None)
    """
    rclpy.init(args=args)
    controller = ArmGripperLoopController()

    try:
        rclpy.spin(controller)
    except KeyboardInterrupt:
        controller.get_logger().info('Shutting down arm gripper controller...')
    finally:
        controller.destroy_node()
        rclpy.shutdown()


if __name__ == '__main__':
    main()

Update to your CMakeLists.txt file with the new script.

build

Launch your arm in Gazebo:

robot

Now run your node:

ros2 run mycobot_system_tests arm_gripper_loop_controller.py

The robot will move from the home position to the target position in a loop until you press CTRL + C.

C++

Now let’s create the same node in C++.

cd ~/ros2_ws/src/mycobot_ros2/mycobot_system_tests/src

Add a file called arm_gripper_loop_controller.cpp.

Update your CMakeLists.txt file and package.xml file.

build

Launch your arm in Gazebo:

robot

Now run your node:

ros2 run mycobot_system_tests  arm_gripper_loop_controller

Your robotic arm will go repeatedly from the home position to the target position.

Congratulations! You made it to the end. That’s it!

Keep building!