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Raspbot V2📖
1.About Raspbot V2
  • 1. First trial
  • 2. Expansion board interface distribution
  • 3. About battery and charging
  • 4. Install servo PTZ
  • 5.Servo Gimbal Installation
  • 6. Important Notes (Read Before Starting)
2.Assembly
  • Installation Video
3.Car basic course
  • 0. Preparation before development
  • 1.Buzzer control
  • 2.Key reading
  • 3.RGB control
  • 4.Servo control (PTZ control)
  • 5.Motor control
  • 6.Printing ultrasonic data
  • 7.Tracking module status printing
  • 8.IR control key value printing
4.Car motion control course
  • 0.Mecanum wheel motion principle
  • 1.Car vertical movement
  • 2.Car diagonal movement
  • 3.Car sideways movement
  • 4.Car rotation movement
  • 5.Car patrol
5.Car advanced courses
  • 1.Infrared patrol car
  • 2.Ultrasonic avoid
  • 3.Ultrasonic follow
  • 4.Infrared tracking+ ultrasonic avoid
  • 5.Restricting
  • 6.Infrared remote control car
6.OpenCV courses
A. Getting Started with OpenCV
  • 1. Introduction to OpenCV
  • 2.OpenCV image reading and display
  • 3. OpenCV image writing
  • 4. OpenCV Image Quality
  • 5.OpenCV pixel operations
B. OpenCV geometric transformation
  • 1. Image scaling
  • 2. Image cutting
  • 3. Image translation
  • 4. Image mirroring
  • 5. Affine Transformation
  • 6. Image Rotation
  • 7. Perspective Transformation
C. OpenCV image processing and text line drawing
  • 1. Grayscale processing
  • 2. Image Binarization
  • 3. Edge Detection
  • 4. Line drawing
  • 5. Rectangle and circle drawing
  • 6. Text and image drawing
D. Image beautification
  • 1. Color Image Histogram
  • 2. Histogram Equalization
  • 3. Image repair
  • 4. Brightness enhancement
  • 5. Smooth and whiten
  • 6. Gaussian mean filtering
  • 7. Median Filter
E. Machine Learning
  • 1. KNN
  • 2. SVM
7.AI vision recognition course
  • 1.Camera driver tutorial
  • 2.Color recognition
  • 3.HSV value test
  • 4.Object Recognition
  • 5.QR code recognition
  • 6.Face recognition
  • 7.License Plate Recognition
  • 8. Human Pose Estimation
  • 9. Target detection
  • 10.yolov5-lite
  • 11. Gesture Recognition
  • 12. Face Detection
  • 13. Face effects
  • 14. 3D Object Recognition
  • 15. Paintbrush
  • 16. Finger control
8.AI vision interaction module
  • 1. Color tracking
  • 2. Color follows
  • 3. QR code recognition to control movement
  • 4. Face tracking
  • 5. Face following
  • 6. Visual tracking
  • 7. Garbage identification
  • 8. Track map Autopilot(purchased separately)
  • 9. Gesture following
9.Voice control basic course(For Superior Kit)new
  • 1.Voice control car movement
  • 2.Voice control RGB light
  • 3.Voice control color recognition
  • 4.Voice control autonomous driving
  • 5.Voice control car tracking
10.AI large model knowledge(For Superior Kit)new
  • 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
  • 5.Configure AI large model(Required)
11.AI Large Model Development(For Superior Kit & Reference)new
  • 1.Register a model service provider account
  • 2. Configuring API-KEY(Optional)
  • 3. Introduction to Dify
  • 4. Basic Dify Features
  • 5. Deploy the RAG knowledge base
  • 6. AI Large Model Development - chatbot
  • 7. RAG knowledge base + chatbot
  • 8. AI agent workflow
  • 9. Custom wake-up response
  • 10. Core module testing tools
12.AI large basic course(For Superior Kit)new
  • 1.Free conversation
  • 2.Text-to-picture
  • 3.Scene description
  • 4.Video description
  • 5.Intelligent action choreography
  • 6.Dual-model agent application
13.ROS2-Robot chassis control course
  • 1. Robot information release
  • 2. Robot keyboard control
  • 3. URDF Model
14.ROS2-OpenCV course
  • 1.ROS+Opencv application
  • 2. AR Vision
  • 3. Mediapipe fun gameplay
  • 4. Gesture control car movement
  • 5. Gesture control car actions
  • 6. Palm control car movement
  • 7. Palm control servo PTZ
  • 8. Visual tracking
  • 9. AprilTag code recognition
  • 10. AprilTag tag code tracking
  • 11. AprilTag tag code follow
15.Development environment course
  • 1. Introduction to Raspberry Pi 5
  • 2. Image writing and backup
  • 3. Start the Raspberry Pi 5
  • 4. Remote Access
  • 5. Remote file transfer
  • 6. Common Linux commands and use of vim editor
  • 7. Install Raspbot V2 driver library
  • 8. Jupyter Lab environment construction
  • 9. Jupyter Lab plugin installation
  • 10. Basic use of Jupyter Widgets
16.Raspberry Pi basic settings
  • 1.Update and upgrade the operating system
  • 2. Introduction to raspi-config tool
  • 3. config.txt file description
  • 4. Network Configuration
  • 5. Set display resolution and rotation
  • 6. Set screen sleep
  • 7. Get real-time temperature of RPi
  • 8. Play audio and video
  • 9. Use USB Camera
  • 10.Use MIPI camera
17.Docker course
  • 1. Overview and installation
  • 2. Common commands
  • 3. Understand and publish images
  • 4. Docker data processing
  • 5. Enter docker container
18.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
Download
  • APP(iOS/Android)
  • Code
  • System_File
  • Instruction Manual
  • Hardware_Info
  • 3D_Model_File
  • ROS2_Basic_VM
Download ZIP

Welcome to Raspbot V2 repository

当製品の日本語版マニュアル資料は、こちらからご取得ください。

8. ROS2 service communication

8. ROS2 Service Communication

1. Introduction to Service Communication

Service communication is a request-response communication model. On both sides of the communication chain, the client sends a request to the server, and the server responds to the client.

The client/server model is as follows:

image8

From the perspective of service implementation, this Q&A format is called the client/server model, or CS model for short. When a client needs certain data, it sends a request to a specific service. After receiving the request, the server processes the request and returns a response.

This communication mechanism is also very common in everyday life. For example, in the various web pages we frequently browse, your computer browser is the client. It sends a request to the website server using a domain name or various operations. The server then responds with the page data to be displayed.

2. Create a new package

  • In the src directory of the workspace:
xxxxxxxxxx
ros2 pkg create pkg_service --build-type ament_python --dependencies rclpy --node-name server_demo

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

3. Server Implementation

3.1 Creating the Server

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

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#Import related libraries
import rclpy
from rclpy.node import Node
from example_interfaces.srv import AddTwoInts
​
class Service_Server(Node):
    def __init__(self,name):
        super().__init__(name)
        #Create a server using the create_service function. The parameters passed in are:
        #Service data type, service name, service callback function (i.e., service content)
        self.srv = self.create_service(AddTwoInts, '/add_two_ints', self.Add2Ints_callback)
    #The service callback function here adds two integers and returns the result.   
    def Add2Ints_callback(self,request,response):
        response.sum = request.a + request.b
        print("response.sum = ",response.sum)
        return response
def main():
    rclpy.init()
    server_demo = Service_Server("publisher_node")
    rclpy.spin(server_demo)
    server_demo.destroy_node()                     #Destroy the node object
    rclpy.shutdown()                               #Shut down the ROS2 Python interface

Focus on the service callback function, Add2Ints_callback. Besides self, the required parameters here are request and response. Request is the parameter required by the service, and response is the service's feedback. Request.a and request.b are the contents of the request, and response.sum is the contents of the response. First, let's take a look at what the data type AddTwoInts looks like.

  • You can use the following command to view it:
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ros2 interface show example_interfaces/srv/AddTwoInts

image-20231023183333410

The "---" character divides the data type into two parts: the top part represents the request, and the bottom part represents the response. Each field then contains its own variable, such as int64 a and int64 b. When passing parameters, you must specify the values ​​of a and b. Similarly, the feedback result also needs to specify the sum value.

3.2 Editing the Configuration File

  • Open setup.py and add the following line to the console_scripts list:
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'server_demo = pkg_service.server_demo:main',

image-20231023183130612

3.3 Compiling the Package

  • Compiling the Package
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colcon build --packages-select pkg_service

image-20250905121820983

3.4 Running the Program

  • Refresh the environment variables and run the node.
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ros2 run pkg_service server_demo

image-20250905121914903

After running, since the service is not called, there is no feedback. You can call the service through the command line. First, query the current services. In another terminal, enter:

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ros2 service list

image-20231023183459015

/add_two_ints is the service we need to call. Call it with the following command. In the terminal, enter:

xxxxxxxxxx
ros2 service call /add_two_ints example_interfaces/srv/AddTwoInts "{a: 1, b: 4}"

Here, we assign the value of a to 1 and the value of b to 4, effectively calling the service to calculate the sum of 1 and 4:

image-20231023183636466

As shown in the image above, after calling the service, the result returned is 5, and the terminal running the server also prints the returned value.

4. Client Implementation

4.1 Creating the Client

Create a new file, [client_demo.py], in the same directory as [server_demo.py].

image-20231023184928672

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

xxxxxxxxxx
#Import related libraries
import rclpy
from rclpy.node import Node
from example_interfaces.srv import AddTwoInts
​
class Service_Client(Node):
    def __init__(self,name):
        super().__init__(name)
        #Create the client using the create_client function, passing in the service data type and service topic name as parameters.
        self.client = self.create_client(AddTwoInts,'/add_two_ints')
        #Loop waiting for the server to successfully start
        while not self.client.wait_for_service(timeout_sec=1.0):
            print("service not available, waiting again...")
        #Create the service request data object
        self.request = AddTwoInts.Request()
        
    def send_request(self): 
        self.request.a = 10
        self.request.b = 90
        #Send the service request
        self.future = self.client.call_async(self.request)
        
def main():
    rclpy.init() #Node initialization
    service_client = Service_Client("client_node") #Create object
    service_client.send_request() #Send service request
    while rclpy.ok():
        rclpy.spin_once(service_client)
        #Determine if data processing is complete
        if service_client.future.done():
            try:
                #Get service feedback and print it
                response = service_client.future.result()
                print("service_client.request.a = ",service_client.request.a)
                print("service_client.request.b = ",service_client.request.b)
                print("Result = ",response.sum)
            except Exception as e:
                service_client.get_logger().info('Service call failed %r' % (e,))
        break
    service_client.destroy_node()                    
    rclpy.shutdown()                              

 

4.2 Edit the Configuration File

  • Open setup.py and add the following line to the console_scripts list:
xxxxxxxxxx
'client_demo = pkg_service.client_demo:main'

image-20231023185118116

4.3 Compile the Package

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colcon build --packages-select pkg_service

image-20250905121820983

4.4 Run the Program

  • Refresh the environment variables and run the node
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# Start the server node
ros2 run pkg_service server_demo
# Start the client node
ros2 run pkg_service client_demo

image-20250905122940643

First run the server, then the client. The client provides a=10 and b=90. The server performs the sum and obtains 100. The result is printed on both terminals.

ROS2 topic communication
ROS2 action communication

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