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ROSMASTER M1 PRO📖
0.Robot Configuration and Operation Guidelines
  • 0.Unboxing and Review
  • 1.Assembly Videos
  • 2.User Manual
  • 3.Enter Docker (For Raspberry Pi)
  • 4.FAQ
  • 5.RobotManager User Guide
1.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
2.Lidar Course
  • 1.Lidar Introduction And Use
  • 2.Lidar Obstacle Avoidance
  • 3.Lidar Following
  • 4.Lidar Guard
  • 5.Lidar Patrol
  • 6.GMapping-SLAM Mapping
  • 7.Cartographer-SLAM Mapping
  • 8.Slam-Toolbox Mapping
  • 9.Lifelong Mode Mapping
  • 10.Navigation2 Single Point Navigation
  • 11.Navigation2 Multi Point Navigation
  • 12.Cartographer Relocalization Navigation
  • 13.Slam-Toolbox Localization Navigation
  • 14.Synchronous Mapping And Navigation
  • 15.Aruco Visual Relocalization Navigation
  • 16.Mobile App Mapping And Navigation
3.USB Camera-Depth Camera Course
  • 1.USB Camera Introduction
  • 2.USB Camera Intrinsic Calibration
  • 3.Nuwa-HP60C Camera Introduction (Depth Camera Only)
  • 4.Depth Pseudo Color Image (Depth Camera Only)
  • 5.Depth Camera Distance Measurement (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)
4.Robotic Arm and 3D Space Gripping Course
  • 1.Robotic Arm Basic Usage
  • 2.Robotic Arm Kinematics
  • 3.Robotic Arm Chassis Coordination Control
  • 4.AprilTag ID Sorting
  • 5.AprilTag Height Anomaly Sorting
  • 6.AprilTag Tracking and Grasping
  • 7.Color Block Sorting
  • 8.Color Block Height Anomaly Sorting
  • 9.Color Block Tracking and Grasping
  • 10.Wood Block Shape Sorting
  • 11.KCF Tracking and Grasping Objects
  • 12.Mediapipe Gesture ID Sorting AprilTag
  • 13.Mediapipe Gesture Height Sorting AprilTag
  • 14.Desktop Tracking and Grasping AprilTag
  • 15.3D Spatial Tracking AprilTag
  • 16.Transformer Model Tracking Algorithm
  • 17.Line Following Obstacle Clearing
5.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
6.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
7.OpenClaw Interaction Method
  • 1.OpenClaw Webchat Interaction
  • 2.OpenClaw Tui Interaction
  • 3.OpenClaw Voice Dialogue Interaction
  • 4.OpenClaw WhatsApp Interaction
8.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
9.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 Props Placement
  • 2.Building the Sandbox Map
  • 3.Visual Relocalization Marker
  • 4.Map Mapping Marker
  • 5.Sandbox Scenario Comprehensive Case
11.AI Large 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 large Model Development
  • 1.Register a Model Service Provider Account
  • 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 - Voice Version
  • 1.Semantic Understanding and Command Following
  • 2.Multimodal Visual Understanding
  • 3.Multimodal Visual Understanding and Robotic Arm Gripping
  • 4.Multimodal Visual Understanding and SLAM Navigation
  • 5.Robotic arm gripping+Multimodal visual understand+SLAM navigation
  • 6.Intention Understanding
14.AI Model - Text Version
  • 1.Semantic Understanding and Command Following
  • 2.Multimodal Visual Understanding
  • 3.Multimodal Visual Understanding and Robotic Arm Gripping
  • 4.Multimodal Visual Understanding and 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 robotic arm
  • 13.Gesture grabbing and releasing objects
  • 14.Finger control robotic arm
  • 15.Medipipe gesture control robotic arm action 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.Trajectory Planning
  • 8.Collision Detection
  • 9.Scene Design
  • 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
  • System File
  • Code
  • 3D Model File
  • Software Tools
  • Hardware_Info
  • Deb function package
  • Dify AI Agent
Download ZIP

Welcome to ROSMASTER M1 PRO repository

2.Robot Handle Control

Robot Handle Control

Robot Handle Control1. Course Content2. Preparation3. Button Control4. Node Communication5. Source Code Analysis

1. Course Content

  1. After running the program, use the PS2 handle to control the robot chassis and control the robotic arm's movement.

  2. Master the key operations of handle control

2. Preparation

  • Insert the wireless handle's USB receiver into the mainboard's USB port

  • Start the handle control function

xxxxxxxxxx
ros2 launch yahboomcar_bringup joy_contoller_launch.py

image-20260622170656294

 

3. Button Control

  • After the program starts, the handle is disabled by default and in a safe state; moving the joystick and pressing buttons will not actually send commands. Press START to enable it, and you can then begin control, with a buzzer prompt tone (beep—beep—beep)

image-20260622181457245

Tip

Handle unlock (enable) prompt tone: beep—beep—beep

Handle lock (disable) prompt tone: beep————

 

  • Key operation table

Handle ActionFunction
Left stick up/downChassis x-axis forward/backward
Left stick left/rightChassis z-axis rotate left/right
Right stick left/rightChassis translate left/right
"START" buttonHandle enable/disable
Left button 1Adjust X, Y-axis linear velocity
Left button 2Adjust Z-axis angular velocity
D-pad left/rightIncrease/decrease servo 1 angle (increase/decrease servo 5 angle)
D-pad up/downIncrease/decrease servo 2 angle (increase/decrease servo 5 angle)
Button X/Button BIncrease/decrease servo 3 angle
Button Y/Button AIncrease/decrease servo 4 angle
Right button 2Switch the joint controlled by D-pad left/right and up/down (robotic arm joint 1/2, robotic arm joint 5/6)
Right button 1Reset the robotic arm to the initial position
  • Key layout diagram

image-20260918160348977

 

4. Node Communication

xxxxxxxxxx
rqt_graph

 

image-20260827101806136

 

 

5. Source Code Analysis

  • Source code path:

xxxxxxxxxx
$HOME/yahboomcar_ros2_ws/yahboomcar_ws/src/common_demo/common_demo/control/joy_control.py

 

​x
    def joy_callback(self, msg):
        """Process joystick messages"""
        with self.lock:
            # On first message, print joystick info and initialize button state
            if not hasattr(self, 'joy_info_printed'):
                self.joy_info_printed = True
                self.get_logger().info(f"Joystick connected: {len(msg.buttons)} buttons, {len(msg.axes)} axes")
                self.get_logger().info(f"Button indices: {list(range(len(msg.buttons)))}")
                self.get_logger().info(f"Axis indices: {list(range(len(msg.axes)))}")
                # Initialize last button states for edge detection
                if len(msg.buttons) > self.enable_button:
                    self.last_enable_button_state = msg.buttons[self.enable_button]
                    self.get_logger().info(f"Initial enable button {self.enable_button} state: {self.last_enable_button_state}")
                if len(msg.buttons) > self.arm_mode_button:
                    self.last_arm_mode_button_state = msg.buttons[self.arm_mode_button]
                    self.get_logger().info(f"Initial arm mode button {self.arm_mode_button} state: {self.last_arm_mode_button_state}")
                if len(msg.buttons) > self.button_reset_arm:
                    self.last_reset_arm_button_state = msg.buttons[self.button_reset_arm]
                    self.get_logger().info(f"Initial reset arm button {self.button_reset_arm} state: {self.last_reset_arm_button_state}")
            
            # Update current axes for base control (always update, even when disabled)
            required_axes_count = max(self.axis_linear_x, self.axis_linear_y, self.axis_angular_z) + 1
            if len(msg.axes) >= required_axes_count:
                self.current_axes = {
                    'linear_x': msg.axes[self.axis_linear_x],
                    'linear_y': msg.axes[self.axis_linear_y],
                    'angular_z': msg.axes[self.axis_angular_z]
                }
                self.get_logger().debug(f"Updated current_axes: {self.current_axes}")
            else:
                self.get_logger().warn(f"Not enough axes ({len(msg.axes)} < {required_axes_count}), using zeros")
                self.current_axes = {'linear_x': 0.0, 'linear_y': 0.0, 'angular_z': 0.0}

            if len(msg.buttons) > self.enable_button:
                button_state = msg.buttons[self.enable_button]
                self.get_logger().debug(f"Enable button {self.enable_button} state: {button_state}, last_state: {self.last_enable_button_state}")
                
                # Only detect rising edge (0 -> 1): toggle enable/disable on button press
                if button_state == 1 and self.last_enable_button_state == 0:
                    # Toggle the enabled state
                    self.enabled = not self.enabled
                    if self.enabled:
                        self.get_logger().info(f"Joystick ENABLED")
                    else:
                        self.get_logger().info(f"Joystick DISABLED")
                    
                    # Play buzzer pattern as toggle feedback
                    if self.enabled:
                        pattern = [(0.1, 0.08), (0.1, 0.08), (0.1, 0.0)]
                    else:
                        pattern = [(0.9, 0.0)]
                    threading.Thread(
                        target=self._play_buzzer_pattern,
                        args=(pattern,),
                        daemon=True
                    ).start()
                
                # Update last state (only after processing)
                self.last_enable_button_state = button_state
            else:
                self.get_logger().warn(f"Button index {self.enable_button} out of range (buttons count: {len(msg.buttons)})")
            
            if not self.enabled:
                return
            
            # Process arm mode toggle button (button 9) with edge detection
            if len(msg.buttons) > self.arm_mode_button:
                arm_mode_button_state = msg.buttons[self.arm_mode_button]
                
                # Only toggle on rising edge (0 -> 1)
                if arm_mode_button_state == 1 and self.last_arm_mode_button_state == 0:
                    self.arm_mode = 1 - self.arm_mode  # Toggle between 0 and 1
                    mode_str = "joint1/2" if self.arm_mode == 0 else "joint5/6"
                    self.get_logger().info(f"Arm control mode switched to: {mode_str}")
                
                # Update last state
                self.last_arm_mode_button_state = arm_mode_button_state
            
            # Process arm reset button (button 7) with edge detection
            if len(msg.buttons) > self.button_reset_arm:
                reset_button_state = msg.buttons[self.button_reset_arm]
                
                # Only trigger on rising edge (0 -> 1)
                if reset_button_state == 1 and self.last_reset_arm_button_state == 0:
                    # Reset joint positions to initial pose
                    init_pose_raw = self.get_parameter('init_pose').value
                    self.joint_positions = [int(x) for x in init_pose_raw]
                    # Publish reset command via ArmJoints message
                    self._pubSix_Arm(self.joint_positions, runtime=2000)
                    time.sleep(2.0)
                    self.get_logger().info(f"Arm reset to initial pose: {self.joint_positions}")
                # Update last state
                self.last_reset_arm_button_state = reset_button_state
            
            # Process linear speed toggle button
            if len(msg.buttons) > self.button_linear_speed_toggle:
                if msg.buttons[self.button_linear_speed_toggle] == 1 and not self.speed_toggle_buttons['linear']:
                    self.speed_toggle_buttons['linear'] = True
                    self.current_linear_speed += self.linear_speed_step
                    if self.current_linear_speed > self.max_linear_speed:
                        self.current_linear_speed = self.linear_speed_step
                    self.get_logger().info(f"Linear speed set to: {self.current_linear_speed:.2f} m/s")
                elif msg.buttons[self.button_linear_speed_toggle] == 0:
                    self.speed_toggle_buttons['linear'] = False
            
            # Process angular speed toggle button
            if len(msg.buttons) > self.button_angular_speed_toggle:
                if msg.buttons[self.button_angular_speed_toggle] == 1 and not self.speed_toggle_buttons['angular']:
                    self.speed_toggle_buttons['angular'] = True
                    self.current_angular_speed += self.angular_speed_step
                    if self.current_angular_speed > self.max_angular_speed:
                        self.current_angular_speed = self.angular_speed_step
                    self.get_logger().info(f"Angular speed set to: {self.current_angular_speed:.2f} rad/s")
                elif msg.buttons[self.button_angular_speed_toggle] == 0:
                    self.speed_toggle_buttons['angular'] = False
            
            # Process joint control buttons (continuous movement while held, like axes)
            # Joint 3 increment (button 1)
            if len(msg.buttons) > self.button_joint3_inc:
                self.joint_buttons['joint3_inc'] = (msg.buttons[self.button_joint3_inc] == 1)
                if self.joint_buttons['joint3_inc']:
                    self.joint_positions[2] = min(self.arm_bounds[2][1], self.joint_positions[2] + self.arm_joint_step * 0.1)
            
            # Joint 3 decrement (button 3)
            if len(msg.buttons) > self.button_joint3_dec:
                self.joint_buttons['joint3_dec'] = (msg.buttons[self.button_joint3_dec] == 1)
                if self.joint_buttons['joint3_dec']:
                    self.joint_positions[2] = max(self.arm_bounds[2][0], self.joint_positions[2] - self.arm_joint_step * 0.1)
            
            # Joint 4 increment (button 4)
            if len(msg.buttons) > self.button_joint4_inc:
                self.joint_buttons['joint4_inc'] = (msg.buttons[self.button_joint4_inc] == 1)
                if self.joint_buttons['joint4_inc']:
                    self.joint_positions[3] = min(self.arm_bounds[3][1], self.joint_positions[3] + self.arm_joint_step * 0.1)
            
            # Joint 4 decrement (button 0)
            if len(msg.buttons) > self.button_joint4_dec:
                self.joint_buttons['joint4_dec'] = (msg.buttons[self.button_joint4_dec] == 1)
                if self.joint_buttons['joint4_dec']:
                    self.joint_positions[3] = max(self.arm_bounds[3][0], self.joint_positions[3] - self.arm_joint_step * 0.1)
            
            # Process axis-controlled joints (joint1/5 and joint2/6)
            if len(msg.axes) > max(self.axis_joint1, self.axis_joint2):
                # Apply deadzone and scaling
                axis1_value = msg.axes[self.axis_joint1]
                axis2_value = msg.axes[self.axis_joint2]
                
                # Apply deadzone
                if abs(axis1_value) < self.deadzone:
                    axis1_value = 0.0
                if abs(axis2_value) < self.deadzone:
                    axis2_value = 0.0
                
                # Scale to joint movement (assuming axis range -1 to 1)
                joint1_delta = axis1_value * self.arm_joint_step * 0.1  # Scale factor
                joint2_delta = axis2_value * self.arm_joint_step * 0.1
                
                if self.arm_mode == 0:
                    # Mode 0: axis6 -> joint1, axis7 -> joint2
                    self.joint_positions[0] = max(self.arm_bounds[0][0], min(self.arm_bounds[0][1], self.joint_positions[0] + joint1_delta))
                    self.joint_positions[1] = max(self.arm_bounds[1][0], min(self.arm_bounds[1][1], self.joint_positions[1] + joint2_delta))
                else:
                    # Mode 1: axis6 -> joint5, axis7 -> joint6
                    self.joint_positions[4] = max(self.arm_bounds[4][0], min(self.arm_bounds[4][1], self.joint_positions[4] + joint1_delta))
                    self.joint_positions[5] = max(self.arm_bounds[5][0], min(self.arm_bounds[5][1], self.joint_positions[5] + joint2_delta))
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