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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

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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