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RDK X5 MagicBox📖
1.RDK MagicBox
  • 1. RDK MagicBox Official Materials
  • 2. Troubleshooting boot failure
  • 3. Linux memory query
2.RDK MagicBox Introduction
  • 1. Introduction to RDK MagicBox
  • 2. Write System File
  • 3. Hardware Interface Description
3.RDK MagicBox User Guide
1. Quick Start
  • Quick Start
2. Basic Peripheral Usage
  • Basic Peripheral Usage
3. Algorithm Development
  • 1. Stereo Depth Estimation
  • 2. Gesture Interaction
  • 3. Voice Interaction
4.RDK MagicBox Basic Settings
  • 1.Network configuration
  • 2.Remote login
  • 3.Update system
  • 4.srpi-config user guide
  • 5.config. txt configuration file
  • 6.Self-startup setting
  • 7.RDK exclusive command usage
  • 8.Linux command usage
  • 9.GPIO readwrite operation
  • 10.Image classification algorithm
  • 11.Use USB camera
  • 12.MIPI Camera Usage
5.RDKX5 Magicbox Basic Development Course
For C language
  • 1. Camera Image Acquisition and Display
  • 2. Camera Image Local Saving
  • 3. Camera Image Acquisition and Encoding
  • 4. Video File Decoding and Display
  • 5. RTSP Stream Decoding
  • 6. VPS Scaling Example
  • 7. Target Detection Algorithm — focs
  • 8. Target Detection Algorithm — YOLOv5s
  • 9. Using CAN
For Python language
  • 1. Prerequisites Before Using Pin Functions
  • 2. Using GPIO
  • 3. Using PWM
  • 4. Use serial port
  • 5. Using I2C
  • 6. Using SPI
For Linux Development
  • Linux Development Guide
6.Online AI Model Course
Online AI Model Course(Text Interaction)
  • 0. Preparation before use
  • 1. OpenRouter Large Model API Aggregation Platform
  • 2. Multimodal Visual Understanding Application
  • 3. Multimodal Visual Positioning Application
  • 4. Multimodal Table Scanning Application
  • 5. Multimodal Autonomous Agent Application
Online AI Model Course(Voice Interaction)
  • 1. Online Speech‑to‑Text (ASR)
  • 2. Online Text‑to‑Speech (TTS)
  • 3. AI Large Model Voice Interaction
  • 4. Multimodal Visual Voice Interaction
  • 5. Multimodal Visual Positioning Application
  • 6. Multimodal Table Scanning Application
  • 7. Multimodal Autonomous Agent Application
  • 8. AI Large Model Online Voice Assistant
7.OpenClaw Embodied AI Development
  • 1. Introduction to OpenClaw
  • 2. OpenClaw Deployment
  • 3. OpenClaw Whatsapp Plugin Application
  • 4. OpenClaw WebChat Interaction
  • 5. OpenClaw TUI Interaction
  • 6. OpenClaw Tool Introduction
  • 7. OpenClawGate Gateway User Manual
  • 8. OpenClaw Plugin Feature Introduction
  • 9. OpenClaw ClawHub Introduction (skill installation)
  • 10. OpenClaw Application - File Management
  • 11. OpenClaw Application - Camera
  • 12. OpenClaw Application - Browser Control
  • 13. OpenClaw Application - Script Execution
  • 14. OpenClaw Application - AI‑programmed Status Light Control
  • 15. OpenClaw Application - AI‑programmed Servo Control
  • 16. OpenClaw Application - Dedicated AI Assistant
8.ROS2 Basic Tutorial
  • 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
Download
  • Code
  • Software_tools
  • SystemFile
Download ZIP

Welcome to RDK X5 MagicBox repository

7.ROS2 topic communication

7. ROS2 Topic Communication

1. Introduction to Topic Communication

Topic communication is the most frequently used communication method in ROS2. A publisher publishes data on a specified topic, and subscribers who subscribe to that topic receive the data.

Topic communication is based on the publish/subscribe model, as shown in the figure:

image8

Topic data transmission is a process where the data is transmitted from one node to another. The object sending data is called a publisher, and the object receiving data is called a subscriber. Each topic must have a name, and the data transmitted must have a fixed data type.

Next, we will explain how to implement topic communication between nodes using Python.

2. Create a New Package

  • Switch to the src directory of the workspace
  • Create a new pkg_topic package
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ros2 pkg create pkg_topic --build-type ament_python --dependencies rclpy --node-name publisher_demo

After executing the above command, the pkg_topic package will be created, along with a publisher_demo node and the relevant configuration files.

image-20231023170921392

3. Publisher Implementation

3.1 Create a Publisher

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

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#Import the rclpy library
import rclpy
from rclpy.node import Node
#Import String messages
from std_msgs.msg import String 
#Create a Topic_Pub node subclass that inherits from the Node base
class Topic_Pub(Node):
    def __init__(self,name):
        super().__init__(name)
        #Create a publisher using the create_publisher function. The passed parameters are:
        #Topic data type, topic name, and queue length for storing messages
        self.pub = self.create_publisher(String,"/topic_demo",1) 
        #Create a timer that enters the interrupt handler every 1 second. The passed parameters are:
        #Interval between interrupt executions, interrupt handler function
        self.timer = self.create_timer(1,self.pub_msg)
    #Define the interrupt handler function
    def pub_msg(self):
        msg = String()  #Create a String variable, msg
        msg.data = "Hi,I send a message." #Assign data to msg
        self.pub.publish(msg) #Publish topic data
        
#Main function
def main():
    rclpy.init() #Initialization
    pub_demo = Topic_Pub("publisher_node") #Create a Topic_Pub class object, passing in the node name as a parameter
    rclpy.spin(pub_demo)     #Execute the rclpy.spin function, passing in the Topic_Pub class object just created as a parameter
    pub_demo.destroy_node()  #Destroy the node object
    rclpy.shutdown()         #Shut down the ROS2 Python interface

 

3.2 Editing the Configuration File

image-20231023173312172

 

3.3 Compiling the Package

  • Compiling the Package
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colcon build --packages-select pkg_topic
  • Refresh the environment variables in the workspace

image-20250905115606561

3.4 Running the Program

  • After refreshing the environment variables, run the command
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ros2 run pkg_topic publisher_demo

After the program successfully runs, nothing is printed. We can use the ros2 topic tool to view the data. First, check if there are any topics being published. Open another terminal and enter:

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ros2 topic list

image-20231023173728019

This topic_demo is the topic data defined in the program. Next, we'll use ros2 topic echo to print this data. In the terminal, enter:

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ros2 topic echo /topic_demo

image-20231023173821223

As you can see, the output "Hi, I send a message." from the terminal matches the line msg.data = "Hi, I send a message." in our code.

4. Subscriber Implementation

4.1 Creating a Subscriber

Create a new file, [subscriber_demo.py], in the same directory as [publisher_demo.py].

image-20231023174819565

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

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#Import related libraries
import rclpy
from rclpy.node import Node
from std_msgs.msg import String
​
class Topic_Sub(Node):
    def __init__(self,name):
        super().__init__(name)  
        #Create a subscriber using create_subscription. The passed parameters are: topic data type, topic name, callback function name, and queue length.
        self.sub = self.create_subscription(String,"/topic_demo",self.sub_callback,1) 
    #Callback function executes the program: prints the received message.
    def sub_callback(self,msg):
        # print(msg.data,flush=True)
        self.get_logger().info(msg.data)
​
​
​
def main():
    rclpy.init() #Initialize the ROS2 Python interface.
    sub_demo = Topic_Sub("subscriber_node")#Create the object and initialize it.
    rclpy.spin(sub_demo)
    sub_demo.destroy_node()  #Destroy the node object
    rclpy.shutdown()         #Shut down the ROS2 Python interface

 

4.2 Editing the Configuration File

image-20231023175338754

 

4.3 Compile the Workspace

  • Compile the package
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colcon build --packages-select pkg_topic
  • Refresh the environment variables in the workspace

image-20250905115606561

4.4 Run the Program

Execute the following command in a separate terminal:

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# Start the publisher node
ros2 run pkg_topic publisher_demo
# Start the subscriber node
ros2 run pkg_topic subscriber_demo

image-20250905120356726

As shown in the figure above, the terminal running the subscriber node will print the information published by the publisher, /topic_demo.

ROS2 node
ROS2 service communication

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