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RDK X3 Robot📖
01. About RDK-X3-Robot
1. Instructions
  • 1. Introduction
  • 2. FAQ
  • 3. Battery and charger use precautions
  • 4.TF card expand capacity
2. Common problem analysis
02. Assembly video
  • Part1-Install Motor
  • Part2-Install Battert Fixing Column
  • Part3-Install Motor Coupling
  • Part4-Install Mecanum wheel
  • Part5-Install Expansion Board
  • Part6-Wiring Show
  • Part7-Install Main Control Board
  • Part8-Install Car Top Plate and Antenna
  • Part9-Install OLED Screen
  • Part10-Install Depth Camera(Optional)
  • Part11-Install OLED Screen
  • Part12-Install HD Camera
  • Part13-Install Top Plate
  • Part14-Install Right Side Plate
  • Part15-Motor Wiring Show
  • Part16-lnstall Car Body
  • Part17-Install Battery
  • Part18-Install Lidar
03. Remote control tutorial
  • 1. The phone APP remote tutorial
  • 2. USB wireless controller remote tutorial
04. ROS functional tutorial
  • 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 tutorial
  • 1. Update the firmware of the expansion module
  • 2. Install the Python driver library
  • 3. Set the type of bottom car
  • 4. Open and close the APP program control
  • 5. Turn hotspot mode on and off
  • 6. The buzzer blows
  • 7. Control the motor forward and reverse
  • 8. Control robot movement
  • 9. OLED display
  • 10. Control fan and lamp effect
06. Development environment setup
  • 1. Virtual Machine
  • 2. Linux Basics
  • 3. Remote connection
  • 4. Multi-computer communication configuration
  • 5. Bind the 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
  • 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 courses
  • 1. Introduction and use of lidar
  • 2. Lidar obstacle avoidance
  • 3. Lidar following
  • 4. Lidar guard
  • 5. Patrol
  • 6. gmapping algorithm
  • 7. cartographer algorithm
  • 8. Navigation and obstacle avoidance
  • 9. App mapping and navigation
10. OpenCV courses
  • 1. Introduction to OpenCV
  • 2. OpenCV geometric transformation
  • 3. OpenCV image processing
  • 4. OpenCV image beautification
  • 5. Qr code creation and identification
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 command
  • 7. Face detection
  • 8. Object detection
  • 9. Visual Inspection -OpenCV
  • 10. Visual inspection - Deep learning
  • 11. Human tracking
  • 12. Gesture control
12. Depth Camera courses
  • 1. Use depth camera
  • 2. Calibration of camera internal reference
  • 3. ROS+OpenCV Foundation
  • 4. AR vision
  • 5. Color tracking
  • 6. Object tracking
13. Multi vehicle control
  • 1. Multi-vehicle synchronous control
  • 2. Multi-vehicle navigation
Remote login control
  • 1. VNC and SSH remote login
  • 2. Jupyter lab login and case code running
Download
  • RemoteCtrl_APP(iOS/Android))
  • Mapping_APP(iOS_Android)
  • Code
  • System File
  • VM_File
  • Manual
  • Software_File
  • Hardware_File
  • ROS2_Basic_VM
Download ZIP

Welcome to RDK X3 Robot repository

11. ROS2 parameter service case

11. ROS2 parameter service case

1. Introduction to parameters

Similar to global variables in C++ programming, they facilitate sharing data across multiple programs. Parameters are global dictionaries in the ROS robot system, allowing data to be shared across multiple nodes.

In the ROS system, parameters exist in the form of a global dictionary. What is a dictionary? Just like a real dictionary, they consist of a name and a value, also known as a key and a value. Alternatively, we can think of them as being like parameters in programming: there's a parameter name, followed by an equals sign, and then the parameter value. To use it, you simply access the parameter name.

Parameters have a rich set of features. For example, if a node shares a parameter, other nodes can access it. If a node modifies a parameter, other nodes can immediately be notified and obtain the latest value.

2. Parameters in the Little Turtle Example

In the Little Turtle example, the emulator provides a number of parameters. Let's use this example to familiarize ourselves with the meaning of parameters and command line usage.

Since a GUI is displayed here, the following examples are demonstrated in the virtual machine that comes with the tutorial for ease of operation.

  1. Launch two terminals in the virtual machine, running the turtle simulator and the keyboard control node respectively:
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ros2 run turtlesim turtlesim_node
ros2 run turtlesim turtle_teleop_key

image-20231030182608893

  1. Launch a terminal in the virtual machine and use the following command to view the parameter list:
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ros2 param list

image-20231030182640039

  1. Querying and Modifying Parameters

To query or modify the value of a parameter, follow the param command with a get or set subcommand:

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ros2 param describe turtlesim background_b # View the description of a parameter
ros2 param get turtlesim background_b # Query the value of a parameter
ros2 param set turtlesim background_b 10 # Modify the value of a parameter
  1. Saving and Loading Parameter Files

Querying/modifying parameters one by one is too cumbersome. Why not try using a parameter file? Parameter files in ROS use the YAML format. You can follow the param command with the dump subcommand to save all the parameters for a node to a file, or use the load command to load all the contents of a parameter file at once:

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ros2 param dump turtlesim >> turtlesim.yaml # Save the parameters of a node to a parameter file
ros2 param load turtlesim turtlesim.yaml # Load all parameters from a file at once

3. Parameter Examples

3.1. Creating a New Function Package

  • Create a new function package in the src directory of the workspace
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ros2 pkg create pkg_param --build-type ament_python --dependencies rclpy --node-name param_demo

After executing the above command, the pkg_param package will be created, a param_demo node will be created, and the relevant configuration files will be configured.

image-20231030185328553

3.2 Code Implementation

Next, edit [param_demo.py] to implement the publisher functionality and add the following code:

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import rclpy                                     # ROS2 Python interface library
from rclpy.node import Node                    # ROS2 Node Class
​
class ParameterNode(Node):
    def __init__(self, name):
        super().__init__(name)                                    # ROS2 node parent class initialization
        self.timer = self.create_timer(2, self.timer_callback)    # Create a timer (a period in seconds, a callback function that is executed at a fixed time)
        self.declare_parameter('robot_name', 'muto')              # Create a parameter and set its default value
​
    def timer_callback(self):                                      # Create a callback function that is executed periodically by the timer
        robot_name_param = self.get_parameter('robot_name').get_parameter_value().string_value   # Read parameter values from the ROS2 system
        self.get_logger().info('Hello %s!' % robot_name_param)     # Output log information and print the parameter values read
​
def main(args=None):                                 # ROS2 node main entry main function
    rclpy.init(args=args)                            # ROS2 Python interface initialization
    node = ParameterNode("param_declare")            # Create a ROS2 node object and initialize it
    rclpy.spin(node)                                 # Loop waiting for ROS2 to exit
    node.destroy_node()                              # Destroy node object
    rclpy.shutdown()                                 # Close the ROS2 Python interface

 

3.3. Compile the package

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colcon build --packages-select pkg_param

image-20250905150404041

3.4. Run the program

  • Refresh the environment variables first, then run the node.
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ros2 run pkg_param param_demo

image-20250905150438440

Open another terminal and set robot_name to robot:

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ros2 param set param_declare robot_name Robot

You can see the log information being printed in a loop in the terminal. "muto" represents the default parameter value for "robot_name." Changing this parameter via the command line will also change the value in the terminal.

image-20231030190533095

ROS2 custom interface message
ROS2 meta-function package

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