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DOFBOT-Ultra📖
1. Get Started Quickly
  • 0.Unboxing Video
  • 1. Get Started Quickly
  • 2. Access the Terminal
  • 3. Calibration offset(Depth Camera)
  • 4. Calibration offset(USB Camera)
2. Assembly Course
  • 1. Installation Steps
  • 2. Calibrate the Robotic Arm
  • 3. Install the Map
3. Remote Control Course
  • 1. Mobile Phone Control
  • 2. USB Handle Control
  • 3. PC Web Page Programming
4. Preparation
  • 1. Manage Web control services
  • 2. Manage JupyterLab services
  • 3. Manage OLED services
5. 2D Visual Tracking Course
  • 1. Color block positioning
  • 2. Color block tracking
  • 3. Face positioning
  • 4. Face tracking
  • 5. Label code positioning
  • 6. Label code tracking
6. 2D Visual Grasping Course
  • 1. Identify grab color block
  • 2. Catch game
  • 3. Color sorting
  • 4. Color stacking
  • 5. Label code sorting
  • 6. Label code stacking
  • 7. Gesture grasping color blocks
  • 8. Gesture stacking color blocks
  • 9. Single garbage sorting
  • 10. Garbage sorting
  • 11. Tracking game
7. 2D Mediapipe Course
  • 1. Hand detection
  • 2. Posture detection
  • 3. Overall detection
  • 4. Facial Detection
  • 5. Face Detection
  • 6. Face effects
  • 7. 3D Object Recognition
  • 8. Paintbrush
  • 9. Finger control
  • 10. Gesture Recognition
  • 11. Gesture control robotic arm action group
  • 12. Arm posture control robotic arm
  • 13. Palm Targeting
  • 14. Robotic arm tracks the palm
  • 15. Fingertip trajectory recognition
  • 16. Fingertip trajectory control robotic arm
  • 17. Gesture Grasp and Release Objects
  • 18. Finger Control Robot Arm
8. AI Large Model Voice Module (Must Read)
  • 1. Introduction to AI Large Model Voice Module
  • 2. Flash the firmware (Must read)
  • 3. Modify the wake-up word and command word
9. 2D Voice Control Course
  • 1. Simple Voice Control
  • 2. Smart Voice Control
  • 3. Voice Action Control
  • 4. Memory Learning Mode
  • 5. Color Recognition with Voice Broadcast
  • 6. Color Recognition and Grasping with Voice Broadcast
  • 7. Color Recognition and Sorting with Voice Broadcast
  • 8. Voice Recognition Target Tracking
  • 9. Voice Control Stacking
  • 10. Voice Control Sorting
  • 11. Garbage Recognition with Voice Broadcast
  • 12. Garbage Sorting with Voice Broadcast
10. 3D Depth Camera Course
  • 1. Dabai_DCW2 camera
  • 2. Deep pseudo-color image
  • 3. Depth camera ranging
  • 4. Color block volume measurement
11. 3D Robotic Arm Control and Inverse Kinematics
  • 1. Robotic arm ROS control
  • 2. Inverse solution
12. 3D Sorting and Grasping Course
  • 1. AprilTag ID sorting
  • 2. AprilTag abnormal height sorting
  • 3. MediaPipe Gesture-AprilTag ID sorting
  • 4. MediaPipe Gesture-AprilTag height sorting
  • 5. MediaPipe Gesture-AprilTag distance sorting
  • 6. Block color sorting
  • 7. Block abnormal height sorting
  • 8. Block different shape sorting
  • 9. Block shape abnormal height sorting
  • 10. Yolov26 garbage sorting
13. 3D Tracking and Grasping Course
  • 1. AprilTag Tracking and Grasping
  • 2. Color Block Tracking and Grasping
  • 3. KCF Object Tracking and Grasping
14. 3D Voice Control for Grasping Course (Sorting & Tracking)
  • 1. Voice Control AprilTag ID Sorting
  • 2. Voice Control Remove Height Abnormal AprilTag
  • 3. Voice Control Tracking and Grasping AprilTag
  • 4. Voice Control Color Block Sorting
  • 5. Voice Control Remove Height Abnormal Color Block
  • 6. Voice Control Tracking and Grasping Color Block
  • 7. Voice Control Yolov26 Garbage Recognition Sorting
  • 8. Voice Control Object Tracking and Grasping
15. AI Model Basics
  • 1. AI Large Model Types and Principles
  • 2. RAG Retrieval Enhancement and Model Training Samples
  • 3. Embodied Intelligent Robot System Architecture
  • 4. Embodied Intelligent Functions Core Source Code
16. AI Model Development
  • 0. DofbotUltra Large Model Development Quick Start Guide
  • 1. Register a Model Service Provider Account
  • 2. Configure API-KEY
  • 3. Introduction to Dify
  • 4. Basic Dify Features
  • 5. AI Large Model Development - chatbot
  • 6. Deploy the RAG knowledge base
  • 7. RAG knowledge base + chatbot
  • 8. AI agent workflow
17. AI Model – Text Version
  • 1. Semantic understand instruction following
  • 2. Multimodal visual understand
  • 3. Text Large Model + robotic arm control
  • 4. Multimodal Large Model + Video Understanding
  • 5. Multimodal Large Model + Robotic Arm Gripping
  • 6. Multimodal Large Model + Robotic Arm Tracking
  • 7. Multimodal Large Model + Robotic Arm Sorting
  • 8. Multimodal Large Model + Robotic Arm Handling
  • 9. Multimodal Large Model + Color Blocks Back In Place
  • 10. Multimodal Large Model + Intent Prediction + Robotic Arm Gripping
  • 11. Text Large Model + YOLOv26 + Intelligent Garbage Classification
18. AI Model – Voice Version
  • 1. Semantic understand instruction following
  • 2. Multimodal visual understand
  • 3. Text Large Model + robotic arm control
  • 4. Multimodal Large Model + Video Understanding
  • 5. Multimodal Large Model + Robotic Arm Gripping
  • 6. Multimodal Large Model + Robotic Arm Tracking
  • 7. Multimodal Large Model + Robotic Arm Sorting
  • 8. Multimodal Large Model + Robotic Arm Handling
  • 9. Multimodal Large Model + Color Blocks Back In Place
  • 10. Multimodal Large Model + Intent Prediction + Robotic Arm Gripping
  • 11. Text Large Model + YOLOv26 + Intelligent Garbage Classification
19. AI Model – Fun Applications
  • 1. AI Butler-Intent Inference
  • 2. AI Encyclopedia-Arithmetic Master
  • 3. AI Encyclopedia-You asked I Pointed
  • 4. AI Encyclopedia-Nutritional Analysis
  • 5. AI Encyclopedia-Problem Solving Expert
  • 6. AI Encyclopedia-English Spelling
  • 7. AI Butler-Garbage Sorting
  • 8. AI Top Chef
20. MoveIt Course
  • 1. MoveIt Configuration
  • 2. MoveIt Usage
  • 3. MoveIt Drive Real Robot
  • 4. MoveIt Random Movement
  • 5. MoveIt Forward Kinematics Design
  • 6. MoveIt Inverse Kinematics Design
  • 7. MoveIt Cartesian Path
  • 8. MoveIt Scene Design
  • 9. MoveIt Trajectory Planning
  • 10. MoveIt Collision Detection
21. YOLOv11 Development Course
PI 5
  • 1. YOLO Environment Setup
  • 2. CLI Usage
  • 3. Object Detection
  • 4. Instance Segmentation
  • 5. Pose Estimation
  • 6. Image Classification
  • 7. Oriented Bounding Boxes Object Detection
  • 8. Model Conversion
  • 9. Dataset Annotation
  • 10. Model Training and Conversion
  • 11. Model Prediction
RDK X5
  • 1. YOLO Environment Setup
  • 2. CLI Usage
  • 3. Object Detection
  • 4. Instance Segmentation
  • 5. Pose Estimation
  • 6. Image Classification
  • 7. Oriented Bounding Boxes Object Detection
  • 8. Model Prediction
  • 9. Model Conversion
22. YOLOv26 Development Course
PI 5
  • 6. Image Classification
  • 1. YOLO Environment Setup
  • 2. CLI Usage
  • 3. Object Detection
  • 4. Instance Segmentation
  • 5. Pose Estimation
  • 6. Image Classification
  • 7. Oriented Bounding Boxes Object Detection
  • 8. Model Conversion
  • 9. Dataset Annotation
  • 10. Model Training and Conversion
  • 11. Model Prediction
RDK X5
  • 1. YOLO Environment Setup
  • 2. CLI Usage
  • 3. Object Detection
  • 4. Instance Segmentation
  • 5. Pose Estimation
  • 7. Oriented Bounding Boxes Object Detection
  • 8. Model Conversion
  • 9. Dataset Annotation
  • 10. Model Training and Conversion
  • 11. Model Prediction
23.Linux Operating System
  • 1.Introduction to Linux system
  • 2.Ubuntu file system
  • 3.Ubuntu common commands
  • 4.Ubuntu common editors
  • 5.Ubuntu software operation commands
  • 6.Virtual machine installation
  • 7.SSH remote control
  • 8.VNC remote control
  • 9.Transfer files remotely
  • 10.Driver library and communication
  • 11.Capacity expansion and resource allocation
  • 12.Bind device ID
  • 13.Capacity expansion and resource allocation
  • 14.Update system software sources
  • 15.Set root user password
  • 16.sudo free password
  • 17.Connect to WiFi network
  • 18.View system version
  • 19.Customized service management
  • 20.Back up system image
24. Basic Control Course
  • 1. Control RGB Light
  • 2. Control Buzzer
  • 3. Control Single Servo
  • 4. Read Servo Angle
  • 5. Control All Servos
  • 6. DOFBOT Up Down Left Right Movement
  • 7. DOFBOT Dancing
  • 8. DOFBOT Memory Actions
  • 9. DOFBOT Grab Blocks
  • 10. Porter
  • 11. Stack Blocks
  • 12. Two DOFBOT Synchronized Actions
25.RDKx5 Board Basic Course
  • 1.Introduction to RDK X5 board
  • 2.Write system file
  • 3.Hardware interface description
  • 4.Install case and other accessories
  • 5.Use 7-inch display
  • 6.SD card expansion
  • 7.Network configuration
  • 8.Remote login
  • 9.Update system
  • 10.srpi-config user guide
  • 11.config. txt configuration file
  • 12.Self-startup setting
  • 13.RDK exclusive command usage
  • 14.Linux command usage
  • 15.GPIO readwrite operation
  • 16.Image classification algorithm
  • 17.Use USB camera
  • 18.Use MIPI camera
  • 19.Binocular camera depth algorithm
26.PI5 Board Basic Course
  • 1.Introduction to Raspberry PI 5
  • 2.Raspberry PI system installation and backup
  • 3.Powering the Raspberry PI 5
  • 4.Startup of Raspberry PI 5
  • 5.Installation and introduction of shell and active radiator
  • 6.GPIO and 40-pin pins
  • 7.Tips for using Raspberry PI 5
  • 8.Raspberry PI PCIe connector
  • 9.MIPI CSI DSI connector
  • 10.UART connector
  • 11.Real-time clock
  • 12.Power over Ethernet (PoE) connector
  • 13.Update and upgrade operating system
  • 14.Introduction to raspi-config tool
  • 15.config.txt file description
  • 16.Network Configuration
  • 17.remote access
  • 18.Transfer files remotely
  • 19.Set display resolution and rotation
  • 20.Set screen to sleep
  • 21.Get real-time temperature of Raspberry Pi
  • 22.Play audio and video
  • 23.Using USB camera
  • 24.Using MIPI camera
27. Visual Basics Course
  • 1. Introduction to Open Source CV
  • 2. Image Reading and Display
  • 3. Image Writing
  • 4. Image Quality
  • 5. Pixel Operation
  • 6. Image Zoom
  • 7. Picture Cut
  • 8. Picture Pan
  • 9. Picture Mirroring
  • 10. Affine Transformation
  • 11. Picture Rotation
  • 12. Perspective Transformation
  • 13. Grayscale Processing
  • 14. Binary Image
  • 15. Edge Detection
  • 16. Line Segment Drawing
  • 17. Rectangular Circle Drawing
  • 18. Text and Picture Drawing
28. 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
29. Jupyter Lab Usage Course
  • 1. Read the document before operation
  • 2. Jupyter lab environment construction tutorial
  • 3. Basic tutorial of Jupyter lab
  • 4. Jupyter widgets configuration tutorial
  • 5. Getting Started Tutorial for JupyterWidgets Controls
Download
  • System_File
  • VM_File
  • Instruction Manual
  • Code
  • Software Tools
  • Communication_Protocols
  • Hardware_Info
Download ZIP

Welcome to DOFBOT-Ultra 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
xxxxxxxxxx
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
xxxxxxxxxx
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
xxxxxxxxxx
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:

xxxxxxxxxx
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:

xxxxxxxxxx
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:

xxxxxxxxxx
#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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