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ROSMASTER A1 PRO📖
00.Configuration and Operation Guide
  • 0. Unboxing and Review
  • 1.Assembly Videos
  • 2.User Manual
  • 3.Enter Docker (For Raspberry Pi)
  • 4.A1Pro Front Wheel Servo Calibration
  • 5.USB Camera Calibration
  • 6.Depth Camera Calibration
  • 7.FAQ
  • 8.Desktop Configuration Center and Remote Control Guide
01.Chassis Control Course
  • 1.Robot Information Publishing
  • 2.Robot Handle Control
  • 3.Robot Keyboard Control
  • 4.Linear Velocity Calibration
  • 5.Angular Velocity Calibration
  • 6.Robot URDF Model
  • 7.Robot EKF State Estimation
02.Lidar Course
  • 1.Lidar Introduction and Use
  • 2.Lidar Obstacle Avoidance
  • 3.Lidar Following
  • 4.Lidar Patrol
  • 5.GMapping-SLAM Mapping
  • 6.Cartographer-SLAM Mapping
  • 7.Slam-Toolbox Mapping
  • 8.Lifelong Mode Mapping
  • 9.Navigation2 Single Point Navigation
  • 10.Navigation2 Multi Point Navigation
  • 11.Cartographer Relocalization Navigation
  • 12.Slam-Toolbox Localization Navigation
  • 13.Synchronous Mapping And Navigation
  • 14.Aruco Visual Relocalization Navigation
  • 15.Mobile App Mapping And Navigation
  • 16.AprilTag Transport
  • 17.Color Block Transport
03.USB Camera-Depth Camera Course
  • 1.USB Camera Introduction
  • 2.USB Camera Intrinsic Calibration
  • 3.Nuwa-HP60C Camera Introduction (Depth Camera Only)
  • 4.Depth Camera Distance Measurement (Depth Camera Only)
  • 5.Depth Pseudo Color Image (Depth Camera Only)
  • 6.Block Volume Calculation (Depth Camera Only)
  • 7.Edge Detection (Depth Camera Only)
  • 8.RTAB-Map SLAM Mapping (Depth Camera Only)
  • 9.RTAB-Map Navigation (Depth Camera Only)
04.Robotic Arm and 3D Space Gripping Course
  • 0.Robotic Arm Basic Usage
  • 1.Robotic Arm Kinematics
  • 2.Robotic Arm Chassis Coordination Control
  • 3.AprilTag ID Sorting
  • 4.AprilTag Height Anomaly Sorting
  • 5.AprilTag Tracking and Grasping
  • 6.Color Block Sorting
  • 7.Color Block Height Anomaly Sorting
  • 8.Color Block Tracking and Grasping
  • 9.Wood Block Shape Sorting
  • 10.KCF Tracking and Grasping Objects
  • 11.Mediapipe Gesture ID Sorting AprilTag
  • 12.Mediapipe Gesture Height Sorting AprilTag
  • 13.Desktop Tracking and Grasping AprilTag
  • 14.3D Spatial Tracking AprilTag
  • 15.Line Following Obstacle Clearing
  • 16.Transformer Model Tracking Algorithm
05.Road Network Planning and Navigation
  • 1.Introduction To Road Network Planning
  • 2.Road Network Annotation
  • 3.Planning And Navigation Between Waypoints
  • 4.Road Network Navigation In Any Pose
  • 5.Path Re-planning
06.OpenClaw Basic Course
  • 1.Introduction to OpenClaw
  • 2.OpenClaw Core Concepts
  • 3.OpenClaw API-KEY Configuration
  • 4.OpenClaw Switch Models
  • 5.OpenClaw System Prompt Words
  • 6.OpenClaw Common CLI Commands
07.OpenClaw Interaction Method
  • 1.OpenClaw Webchat Interaction
  • 2.OpenClaw Tui Interaction
  • 3.OpenClaw Voice Dialogue Interaction
  • 4.OpenClaw WhatsApp Interaction
08.OpenClaw Development
  • 1.OpenClaw Connecting to Robot MCP Service
  • 2.Robot CLI Command Tool
  • 3.robot-control plugin tool
  • 4.reply-bridge plugin tool
  • 5.OpenClaw Multimodal Vision
  • 6.OpenClaw Chassis Control
  • 7.OpenClaw Robotic Arm Control
  • 8.OpenClaw Skills Development
  • 9.OpenClaw Scheduled Tasks
  • 10.OpenClaw Multi-Agent Intelligent Agent
  • 11.OpenClaw Active Interaction
  • 12.OpenClaw Vector Memory
09.OpenClaw Embodied Intelligent Application
  • 1.OpenClaw Target Tracking
  • 2.OpenClaw Arm Tracking And Grasping
  • 3.OpenClaw Arm Fixed-point Placement
  • 4.OpenClaw Waste Sorting
  • 5.OpenClaw SLAM Mapping And Navigation
  • 6.OpenClaw Navigation Transport
  • 7.OpenClaw AprilTag Grasping
  • 8.OpenClaw Color Line Patrol
  • 9.OpenClaw Visual Distance Measurement
10.OpenClaw Scenario Sandbox
  • 1.Map Description and Prop Placement
  • 2.Build Sand Table Map
  • 3.Visual Relocation Markers
  • 4.Map Mapping Markers
  • 5.OpenClaw Scenario Sandbox Comprehensive Case
11.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
12.AI Model Development
  • 1.Register a Model Service Provider Aaccount
  • 2.Configuring 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
  • 9.Custom Wake-up Response
13.AI Model - Text Version
  • 1.Semantic Understand and Command Follow
  • 2.Multimodal Visual Understand
  • 3.Multimodal Visual Understand + Robotic Arm Gripping
  • 4.Multimodal Visual Understand+SLAM Navigation
  • 5.Robotic Arm Gripping+Multimodal Visual Understand+SLAM Navigation
  • 6.Intention Estimation
14.AI Model - Voice Version
  • 1.Semantic Understand and Command Follow
  • 2.Multimodal Visual Understand
  • 3. Multimodal Large Model+Robotic Arm Gripping
  • 4.Multimodal Visual Understand+SLAM Navigation
  • 5.Robotic Arm Gripping+Multimodal Visual Understand+SLAM Navigation
  • 6.Intention Estimation
15.Mediapipe Visual Course
  • 1.Hand Detection
  • 2.Posture Detection
  • 3.Overall Detection
  • 4.Facial Landmark Detection
  • 5.Face Detection
  • 6.Face Special Effects
  • 7.3D Object Recognition
  • 8.Brush
  • 9.Finger Control
  • 10.Palm Target Positioning
  • 11.Fingertip Trajectory Recognition
  • 12.Fingertip Gesture Control Cobotic Arm
  • 13.Gesture Grabbing and Releasing Objects
  • 14.Finger Control Robotic Arm
  • 15.Medipipe Gesture Control Robotic arm Cction Group
16.MoveIt2 Simulation Course
  • 1.MovelT2 Configuration
  • 2.MovelT2 Simulation-Reality Linkage
  • 3.Random Movement
  • 4.Forward Kinematics Design
  • 5.Inverse Kinematics Design
  • 6.Cartesian Path
  • 7.Scene Design
  • 8.Trajectory Planning
  • 9.Collision Detection
  • 10.3D Perception Obstacle‑Avoidance
17.Multi-vehicle Course
  • 1.Multi-vehicle Control
  • 2.Multi-vehicle Navigation
  • 3.Multi-vehicle Formation
18.YOLO26 Development
  • 1.CLI Use
  • 2.Object Detection
  • 3.Instance Segmentation
  • 4.Pose Estimation
  • 5.Image Classification
  • 6.Oriented Object Detection
  • 7.YOLOv26 + DeepSORT Tracking
  • 8.Monocular Depth Estimation
19.Control Board STM32 Driver Course
  • 0.Notes (Must Read)
  • 1.About Expansion Board
  • 2.STM32 Development Environment
  • 3.Button Control
  • 4.FreeRTOS Application
  • 5.Serial Communication
  • 6.SBUS Model Aircraft Remote Control
  • 7.CAN Bus Communication
  • 8.RGB Colorful Light Bar
  • 9.Timer Interrupt to Control PWM Servo
  • 10.Control Serial Port Servos
  • 11.Nine-axis Attitude Sensor to Obtain Data
  • 12.Control Motor
  • 13.Timer Captures the Encoder Data
  • 14.1 Kinematic Analysis of Mecanum Wheel
  • 14.2 Kinematic Analysis of Ackerman
  • 14.3 Kinematic Analysis of 4WD
  • 15.PID Control Robot Movement
20.Docker Course
  • 1.Docker Introduction and Installation
  • 2.Docker Basic Commands
  • 3.Docker Submission and Multi-Terminal Access
  • 4. Docker Startup Script
  • 5.Docker-Vscode Environment Construction
21.Image Processing 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. Image cutting
  • 8. Image translation
  • 9. Image Mirroring
  • 10. Affine Transformation
  • 11. Image Rotation
  • 12. Perspective Transformation
  • 13. Grayscale processing
  • 14. Image Binarization
  • 15. Edge Detection
  • 16. Line drawing
  • 17. Rectangle and circle drawing
  • 18. Drawing text and pictures
22.Linux System Course
  • 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.Static IP and hotspot mode
  • 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
23.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
24.Main Control Course
Jetson Orin Nano_NX
  • 1.Jetson Orin board introduction
  • 2.Restore the factory image system
  • 3.Backup SSD system
  • 4.SSD expansion
  • 5.Network configuration
  • 6.SSH remote login
  • 7.VNC remote control
  • 8.Remote file transfer
  • 9.Jtop tool
  • 10.Exchange space expansion
Raspberry Pi
  • 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. Update and upgrade operating system
  • 6. Introduction to raspi-config tool
  • 7. config.txt file description
  • 8. Network Configuration
  • 9. remote access
  • 10. Transfer files remotely
  • 11. Set display resolution and rotation
  • 12. Set screen to sleep
  • 13. Play audio and video
  • 14. Using USB camera
  • 15. Using MIPI camera
  • 16. Get real-time temperature of Raspberry Pi
RDKX5
  • 1.Introduction to RDK X5 board
  • 2.Write system file
  • 3.Hardware interface description
  • 4.Install case and other accessories
  • 5.Network configuration
  • 6.Remote login
  • 7.Update system
  • 8.srpi-config user guide
  • 9.config. txt configuration file
  • 10.Self-startup setting
  • 11.RDK exclusive command usage
  • 12.Linux command usage
  • 13.GPIO readwrite operation
  • 14.Image classification algorithm
  • 15.Use USB camera
  • 16.Use MIPI camera
  • 17.Binocular camera depth algorithm
  • 18. Controlling RGB Cooling Fans
Download
  • SystemFile
  • Code
  • 3D_Model_File
  • Software_Tools
  • Hardware_Info
  • Introduction_Manual
  • Script_File
  • Dify AI Agent
Download ZIP

Welcome to ROSMASTER A1 PRO repository

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.
xxxxxxxxxx
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:

xxxxxxxxxx
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
xxxxxxxxxx
# 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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