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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

6.OpenClaw Chassis Control

OpenClaw Chassis Control

OpenClaw Chassis Control1. Course ContentCourse OverviewLearning Objectives2. Preparation3. Case Demonstration3.1 Start OpenClaw Interaction3.2 Chassis Movement Control3.3 Chassis Omnidirectional Movement Control3.4 Chassis In-Place Steering4. Source Code Analysis4.1 set_cmdvel — Set Chassis Motion Velocity (Underlying Implementation of MoveWithSpeed)4.2 move_by_odom

1. Course Content

Course Overview

  • OpenClaw chassis control is the basic feature of robot motion control. It provides 2 chassis control tools through the MCP interface: MoveWithSpeed (velocity control) and Move (odometry closed-loop control movement)

  • Supports omnidirectional chassis control, capable of controlling the X/Y direction linear velocities and Z-axis angular velocity simultaneously, achieving forward/backward movement, left/right translation, and in-place rotation

  • Achieves precise distance control and angle control through odometry (Odom) feedback, ensuring motion accuracy

Learning Objectives

  1. Understand the functions and uses of the 3 chassis control interfaces provided by OpenClaw

  2. Master the interaction methods for chassis movement, omnidirectional movement, and steering through WebChat

2. Preparation

  • Start the MCP service

ros2 launch yahboomcar_bringup mcp_service.launch.py
  • If you need voice replies, you need to add the use_tts parameter: use_tts:=true, otherwise it can be omitted

 

No.Tool NameFunction Description
1MoveWithSpeedControl the robot's omnidirectional chassis velocity
2MoveControl the robot chassis to move a specified distance

3. Case Demonstration

3.1 Start OpenClaw Interaction

  • Use any interaction method to converse with OpenClaw, here demonstrating with Web Chat

image-20260430152349337

Tip

  • You can write the conversation statements according to your own needs; following is the case demonstration

3.2 Chassis Movement Control

  • Move forward 0.2 meters, then translate right 0.2 meters

image-20260430152927178

3.3 Chassis Omnidirectional Movement Control

  • The MoveWithSpeed tool provides lower-level velocity control, capable of completing complex movements through vector composition of velocities, for example:

  • Please move for 2 seconds at an x-axis velocity of 0.1 m/s and a y-axis velocity of 0.15 m/s

image-20260430153538629

3.4 Chassis In-Place Steering

  • Rotate right 35 degrees, rotate counterclockwise 40 degrees

image-20260430155400453

4. Source Code Analysis

  • Source code path

xxxxxxxxxx
~/yahboomcar_ros2_ws/yahboomcar_ws/src/multi_brains_pre/multi_brains_pre/action_controller.py

4.1 set_cmdvel — Set Chassis Motion Velocity (Underlying Implementation of MoveWithSpeed)

Code Description:

  • set_cmdvel: Sets the chassis motion velocity and automatically stops after the specified duration; this is the underlying implementation of the MoveWithSpeed tool

  • Twist(): Creates a ROS2 velocity message object, containing linear velocity linear (x/y/z) and angular velocity angular (x/y/z)

  • twist.linear.x: Forward/backward linear velocity, unit: m/s; positive values forward, negative values backward

  • twist.linear.y: Left/right linear velocity, unit: m/s; positive values to the left, negative values to the right (exclusive to omnidirectional chassis)

  • twist.angular.z: Angular velocity, unit: rad/s; positive values rotate counterclockwise, negative values rotate clockwise

  • self.cmd_pub.publish(twist): Publishes the velocity command to the cmd_vel topic, driving the chassis to move at the set velocity

  • time.sleep(duration): Continues moving for the specified time (seconds)

  • self.cmd_pub.publish(Twist()): Publishes an empty velocity message (all components zeroed), stopping the chassis

  1. Message construction: Creates a Twist() velocity message, setting linear.x (forward/backward linear velocity), linear.y (left/right linear velocity), and angular.z (angular velocity)

  2. Publish and stop: Publishes to the cmd_vel topic through cmd_pub, continues for the specified time via time.sleep(duration), then publishes an empty Twist() to stop

  3. Omnidirectional control: Sets the x/y linear velocities and z angular velocity simultaneously, achieving movement in any direction through velocity vector composition

xxxxxxxxxx
def set_cmdvel(self, linear_x:float, linear_y:float, angular_z:float, duration:float)->bool:
    """
    Set robot movement speed and duration
    """
    twist = Twist()
    twist.linear.x = linear_x
    twist.linear.y = linear_y
    twist.angular.z = angular_z
    self.cmd_pub.publish(twist)
    time.sleep(duration)
    self.cmd_pub.publish(Twist())
    return True

 


4.2 move_by_odom

  • The server-side program is provided by the chassis driver; program path: ~/yahboomcar_ros2_ws/yahboomcar_ws/src/yahboomcar_bringup/yahboomcar_bringup/mcnamu_driver.py

Code Description:

  • _request_move_by_odom: Client function that sends an odometry movement request to the mcnamu_driver MoveByOdom Action server and waits for the execution result

  • wait_for_server: Waits for the MoveByOdom Action server to come online; the timeout is 10 seconds, and it returns False if it times out

  • MoveByOdom.Goal(): Constructs the Action goal message, setting three parameters: distance (movement distance), angle (target angle), and direction (movement direction)

  • send_goal_async: Asynchronously sends the goal to the Action server, waiting for the send result via _wait_future with a 10-second timeout

  • goal_handle.accepted: Checks whether the server accepted the goal request; if rejected, logs an error and returns False

  • get_result_async: Asynchronously obtains the Action execution result; timeout=None means relying on the server's own timeout limit

  • result.success: Success flag of the execution result; True means the movement is complete, False means failure

  • result.message: Detailed information of the execution result, containing a description of the specific reason for success or failure

  • _wait_future: An internally encapsulated Future waiting method that supports timeout control, avoiding infinite blocking

xxxxxxxxxx
    def _request_move_by_odom(self, distance: float, angle: float, direction: str) -> bool:
        '''Request the mcnamu_driver move_by_odom action service and wait for the result'''
        if not self.move_by_odom_client.wait_for_server(timeout_sec=10.0):
            self.get_logger().error("MoveByOdom action server not available")
            return False
    
        goal = MoveByOdom.Goal()
        goal.distance = float(distance)
        goal.angle = float(angle)
        goal.direction = direction
    
        send_goal_future = self.move_by_odom_client.send_goal_async(goal)
        if not self._wait_future(send_goal_future, timeout=10.0):
            self.get_logger().error("Failed to send MoveByOdom goal")
            return False
    
        goal_handle = send_goal_future.result()
        if not goal_handle.accepted:
            self.get_logger().error("MoveByOdom goal rejected by action server")
            return False
    
        result_future = goal_handle.get_result_async()
        # node is spinning in a background thread, timeout None relies on server side limits
        if not self._wait_future(result_future, timeout=None):
            self.get_logger().error("MoveByOdom action result timeout")
            return False
    
        result = result_future.result().result
        if result.success:
            self.get_logger().info(f"MoveByOdom succeeded: {result.message}")
            return True
        self.get_logger().warn(f"MoveByOdom failed: {result.message}")
        return False

Tip

  • For more detailed chassis control operations, refer to the navigation-transport and waste-sorting cases in 【OpenClaw Embodied intelligent application】

 

 

OpenClaw Multimodal Vision
OpenClaw Robotic Arm Control

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