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RDK X5 Robot📖
01. RDK-X5-Robot Introduction
  • 1.Introduction
  • 2.Common Problem Analysis
  • 3.Battery and charger usage precautions
  • 4.TF card expand capacity
02. Assembly Tutorial
  • Assembly Tutorial
  • Assembly Video-1
  • Assembly Video-2
  • Assembly Video-3
  • Assembly Video-4
03. Remote Control Course
  • 1.Mobile APP remote control
  • 2.USB Wireless Controller Remote Control
04. ROS Driver Board Course
  • 1. Introduction of extension board
  • 2. Set up STM32 development environment
  • 3. Key control buzzer sound
  • 4. FreeRTOS application
  • 5. Serial communication
  • 6. SBUS model remote control
  • 7. CAN bus communication
  • 8. RGB color light strip
  • 9. Timer interrupt control PWM servo
  • 10. Control serial steering gear
  • 11. Nine-axis attitude sensor to obtain data
  • 12. Control motor forward and reverse
  • 13. The timer captures encoder data
  • 14. Theory of robot kinematics analysis
  • 15. PID control robot motion
05. Basic Control Course
  • 1.Update expansion board firmware
  • 2.Install Python driver library
  • 3.Set the car type
  • 4.Open and close APP program control
  • 5.Turn hotspot mode on and off
  • 6.Buzzer sound
  • 7.Control the motor to rotate forward and reverse
  • 8.Controlling robot movement
  • 9.OLED display
  • 10.Control fans and lighting effects
06. Development Environment
  • 1. Virtual machine installation and use
  • 2. Linux Basics
  • 3. Remote connection
  • 4. Multi-machine communication configuration
  • 5. Bind device ID
  • 6. Image installation and backup
07. ROS2 Basic Course
  • 1. Introduction to ROS2
  • 2. ROS2 install Humble
  • 3. ROS2 development environment
  • 4. ROS2 workspace
  • 5. ROS2 function package
  • 6. ROS2 node
  • 7. ROS2 topic communication
  • 8. ROS2 service communication
  • 9. ROS2 action communication
  • 10. ROS2 custom interface message
  • 11. ROS2 parameter service case
  • 12. ROS2 meta-function package
  • 13. ROS2 distributed communication
  • 14. ROS2 DDS
  • 15. ROS2 time related API
  • 16. ROS2 common command tools
  • 17. ROS2 rviz2 use
  • 18. ROS2 rqt toolbox
  • 19. ROS2 Launch startup file configuration
  • 20. ROS2 recording and playback tool
  • 21. ROS2 URDF model
  • 22. ROS2 Gazebo simulation platform
  • 23. ROS2 TF2 coordinate transformation
08. Robot Chassis Control Course
  • 1. PID algorithm theory
  • 2. Robot information release
  • 3. Robot control
  • 4. Robot state estimation
  • 5. Robot calibration
  • 6. Robot trajectory tracking
  • 7. URDF Model
09. LiDAR Course
  • 1. Introduction and use of lidar
  • 2. Lidar obstacle avoidance
  • 3. Lidar tracking
  • 4. Lidar guard
  • 5. Lidar patrol
  • 6. gmapping mapping algorithm
  • 7. Cartographer mapping algorithm
  • 8. Navigation and obstacle avoidance
  • 9. App Mapping and Navigation
10. OpenCV Course
  • 1. Getting started with OpenCV
  • 2. OpenCV geometric transformation
  • 3. OpenCV Image Processing
  • 4. OpenCV image beautification
  • 5. QR code creation and recognition
11. Mipi Camera Course
  • 1. Camera driver
  • 2. Adjust the color HSV value
  • 3. Color recognition
  • 4. Color Tracking
  • 5. Color Follow
  • 6. QR code instructions
  • 7. Face Detection
  • 8. Object Detection
  • 9. Visual line patrol-OpenCV
  • 10. Visual line patrol-deep learning
  • 11. Human body tracking
  • 12. Gesture control
12. Depth Camera Course
  • 1. Use of Depth Camera
  • 2. Camera intrinsic calibration
  • 3. ROS+OpenCV Basics
  • 4. AR Vision
  • 5. Color Tracking
  • 6. Object Tracking
  • 7. RTAB-Map 3D Mapping Navigation
13. Multi-robot Synchronous Control
  • Multi-vehicle synchronous control
Remote login control
  • 1. VNC and SSH remote login
  • 2. Jupyter lab login and case code running
Download
  • System_File
  • Code
  • VM_File
  • Software_Tools
  • Hardware_Info
  • Firmware
  • Instruction_Manual
  • ROS2_Basic_VM
Download ZIP

Welcome to RDK X5 Robot repository

22. ROS2 Gazebo simulation platform

22. ROS2 Gazebo Simulation Platform

1. Introduction to Gazebo

Gazebo is the most commonly used 3D physics simulation platform in the ROS system. It supports a dynamics engine and enables high-quality graphics rendering. It not only simulates the robot and its surrounding environment, but also incorporates physical properties such as friction and elasticity.

For example, if we want to develop a Mars rover, we can simulate the Martian surface environment in Gazebo. Or, if we're developing a drone, battery life and flight restrictions prevent us from frequently experimenting with the actual drone. In these cases, we can use Gazebo to simulate first, then deploy to the actual drone once the algorithm is fully developed.

Simulation platforms like Gazebo can help us verify robotic algorithms, optimize robot designs, and test robot applications, providing more possibilities for robotics development.

Note: This section is for learning purposes only. The tutorial does not configure the environment because we are using real-device debugging

2. Installation and Operation

  • Install gazebo using the apt command
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sudo apt install ros-${ROS_DISTRO}-gazebo-*
  • Run gazebo
  • Launch gazebo using the following command or directly from the desktop icon
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gazebo --verbose -s libgazebo_ros_init.so -s libgazebo_ros_factory.so

image-20250905185527569

image-20250905185455271

After running, you should see the following page:

img

  • Optional: To ensure smooth model loading, you can download the offline model and place it in the ~/.gazebo/models directory. The download link is as follows: https://github.com/osrf/gazebo_models

3. Start the Gazebo Node and Service

  1. View the Node
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ros2 node list

image-20250905185639464

Correct return: /gazebo

  1. View the external services provided by the node:
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ros2 service list

You can see the following results:

image-20250905185658045

Excluding the last few regular services, we will only focus on the first three special services:

  • /spawn_entity, used to load models into gazebo
  • /get_model_list, used to obtain a model list
  • /delete_entity, used to delete loaded models in gazebo

4. Create a function package

  • Create a myrobot package to store our URDF model and launch files.
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ros2 pkg create myrobot --build-type ament_cmake
  • Go to the myrobot directory and create folders launch and urdf. Within the urdf folder, create a file called demo01_base.urdf. This file is a simple demonstration file containing only a basic cube.
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<robot name="myrobot">
    <link name="base_link">
        <visual>
            <geometry>
                <box size="0.2 0.2 0.2"/>
            </geometry>
            <origin xyz="0.0 0.0 0.0"/>
        </visual>
        <collision>
            <geometry>
                <box size="0.2 0.2 0.2"/>
            </geometry>
            <origin xyz="0.0 0.0 0.0"/>
        </collision>
        <inertial>
            <mass value="0.1"/>
            <inertia ixx="0.000190416666667" ixy="0" ixz="0" iyy="0.0001904" iyz="0" izz="0.00036"/>
        </inertial>
    </link>
    <gazebo reference="base_link">
        <material>Gazebo/Red</material>
    </gazebo>
</robot>

 

5. Writing the launch file

Writing a launch file consists of two main parts: launching the Gazebo file and then loading the robot model into Gazebo.

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start_gazebo_cmd =  ExecuteProcess(
        cmd=['gazebo', '--verbose','-s', 'libgazebo_ros_init.so', '-s', 'libgazebo_ros_factory.so'],
        output='screen')

This command starts Gazebo. It is a simple startup command and is not particularly complicated. Here is the command to load the model:

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 spawn_entity_cmd = Node(
        package='gazebo_ros', 
        executable='spawn_entity.py',
        arguments=['-entity', robot_name_in_model,  '-file', urdf_model_path ], output='screen')

Note the following two parameters in this command: -entity is the name of the model file, and -file is the parameter loaded through the urdf file. Later we can also see how the model is loaded through the topic. Create a bringup_model.launch.py ​​file in the launch directory. The complete startup file is as follows:

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import os
from launch import LaunchDescription
from launch.actions import ExecuteProcess
from launch_ros.actions import Node
from launch_ros.substitutions import FindPackageShare
from launch_ros.parameter_descriptions import ParameterValue
from launch.substitutions import Command
​
def generate_launch_description():
    robot_name_in_model = 'myrobot'
    package_name = 'myrobot'
    urdf_name = "demo01_base.urdf"
   
    ld = LaunchDescription()
    pkg_share = FindPackageShare(package=package_name).find(package_name) 
    urdf_model_path = os.path.join(pkg_share, f'urdf/{urdf_name}')
   
    # Start Gazebo server
    start_gazebo_cmd =  ExecuteProcess(
        cmd=['gazebo', '--verbose','-s', 'libgazebo_ros_init.so', '-s', 'libgazebo_ros_factory.so'],
        output='screen')
​
    # Launch the robot
    spawn_entity_cmd = Node(
        package='gazebo_ros', 
        executable='spawn_entity.py',
        arguments=['-entity', robot_name_in_model,  '-file', urdf_model_path ], output='screen')
​
    ld.add_action(start_gazebo_cmd)
    ld.add_action(spawn_entity_cmd)
​
    return ld
​
  • Fill in the following content in Cmakelist to install our urdf and launch folders into the install directory
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install(
    DIRECTORY urdf launch
    DESTINATION share/${PROJECT_NAME}
)

 

  • Then compile and run the function package
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colcon build --packages-select myrobot

image-20250905190216658

 

  • Refresh the environment variables and run the launch startup file
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ros2 launch myrobot bringup_model.launch.py

image-20250905190401459

 

After launching, you should see the following Gazebo model:

image-20250905190451228

You can see the red model because you added the Gazebo tag settings.

 

 

ROS2 URDF model
ROS2 TF2 coordinate transformation

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