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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

7.OpenClaw Robotic Arm Control

OpenClaw Robotic Arm Control

OpenClaw Robotic Arm Control1. Course ContentCourse OverviewLearning Objectives2. Preparation3. Robotic Arm-Related Control Interfaces4. Case Demonstration4.1 Start OpenClaw Interaction4.2 Get the Current Joint Angles of the Robotic Arm4.3 Control the 6 Joints of the Robotic Arm Simultaneously4.4 Control a Single Robotic Arm Joint4.5 Restore the Robotic Arm to the Preset Initial Pose4.6 Adjust the Camera Observation View5. Source Code AnalysisControlArmJointAngles() — Control 6 Joints SimultaneouslyAdjustCameraView() — Adjust the Camera ViewInitArmPose() — Initialize the Robotic Arm PoseControlSingleArmJointAngle() — Control a Single Joint Angle

1. Course Content

Course Overview

  • OpenClaw robotic arm control is one of the core features of the OpenClaw platform, converting AI natural language instructions into robotic arm control operations through the MCP protocol

  • Covers multiple robotic arm control interfaces: joint angle retrieval, end-effector pose retrieval, simultaneous multi-joint control, single-joint control, camera view adjustment, and initial pose restoration

Learning Objectives

  1. Understand the interface features of OpenClaw controlling the robotic arm

  2. Master the practical operation methods and use cases of each robotic arm control interface

  3. Be able to optimize grasping and placement accuracy by adjusting configuration file parameters

2. Preparation

  • Start the MCP service

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

image-20260908115148000

3. Robotic Arm-Related Control Interfaces

No.Tool NameFunction Description
1GetCurrentArmJointAnglesGet the current joint angles of the robotic arm
2ControlSixArmJointControl the 6 joints of the robotic arm simultaneously
3ControlSingleArmJointControl a single robotic arm joint to a specified angle
4AdjustCameraViewAdjust the camera view
5InitArmPoseRestore the robotic arm to the preset initial pose

 

4. Case Demonstration

4.1 Start OpenClaw Interaction

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

image-20260429173005222

Tip

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

4.2 Get the Current Joint Angles of the Robotic Arm

  • What are the current angles of each joint of the robotic arm?

image-20260429173210914

 

4.3 Control the 6 Joints of the Robotic Arm Simultaneously

  • Use the robotic arm to perform a dance for me

  • OpenClaw autonomously decides and choreographs the robotic arm dance movements; the actual effect shall prevail, and different models output different content

image-20260429173705440

 

4.4 Control a Single Robotic Arm Joint

  • Set the first joint of the robotic arm to 0 degrees

image-20260429174028622

 

4.5 Restore the Robotic Arm to the Preset Initial Pose

  • Restore the robotic arm to the initial pose

image-20260429174131512

  • The initial pose can be changed through the configuration file

xxxxxxxxxx
~/yahboomcar_ros2_ws/yahboomcar_ws/src/yahboomcar_bringup/param/common.yaml

image-20260908115831694

 

4.6 Adjust the Camera Observation View

  • Look a bit to the left

  • This feature is used to conveniently adjust the observation view to find targets during subsequent robotic arm operations

image-20260429174713146

 

 

5. Source Code Analysis

  • Source code path

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

ControlArmJointAngles() — Control 6 Joints Simultaneously

Code Description:

  • Constructs an ArmJoints ROS2 message, setting the target angles of the 6 joints at once and publishing to the arm6_joints topic

  • Joint 6 (the gripper) has an 180 - angle conversion, because the gripper's mechanical zero point and the angle definition direction are opposite

  • The runtime parameter controls the movement time (milliseconds); the larger the value, the slower and smoother the movement

xxxxxxxxxx
def ControlArmJointAngles(self, arm_joint_1:int, arm_joint_2:int, arm_joint_3:int,
                          arm_joint_4:int, arm_joint_5:int, arm_joint_6:int,
                          runtime:int=2000) -> bool:
    arm_joint = ArmJoints()
    arm_joint.joint1 = arm_joint_1
    arm_joint.joint2 = arm_joint_2
    arm_joint.joint3 = arm_joint_3
    arm_joint.joint4 = arm_joint_4
    arm_joint.joint5 = arm_joint_5
    arm_joint.joint6 = 180 - arm_joint_6  # Special handling for joint 6
    arm_joint.time = runtime               # Movement time (ms)
    self.SixJoint_pub.publish(arm_joint)
    return True

AdjustCameraView() — Adjust the Camera View

Code Description:

  • yaw: Adjusts joint 1 to rotate the camera left and right; positive values turn right, negative values turn left

  • pitch: Preferentially adjusts joint 4 to achieve up/down tilt; when joint 4 reaches its lower limit (-5°), it automatically switches to joint 2 for pitch compensation

  • After adjustment is complete, it automatically calls SeeWhat() to refresh the image and returns the new image path

xxxxxxxxxx
def AdjustCameraView(self, pitch:int=0, yaw:int=0) -> list[bool, str]:
    """Quickly adjust the camera view"""
    self._get_joints()  # Get the current angles of joints 1, 2, and 4
    
    if yaw != 0:  # Horizontal adjustment (joint 1 — left/right rotation)
        self.joint_1 += yaw
        self.SingleJoint_pub.publish(ArmJoint(id=1, joint=self.joint_1, time=200))
    
    if pitch != 0:  # Pitch adjustment (joint 4 — up/down tilt)
        temp_joint = self.joint_4 + pitch
        if temp_joint <= -5:  # Joint 4 reached its lower limit; use joint 2 for pitch compensation
            self.joint_2 += pitch
            self.SingleJoint_pub.publish(ArmJoint(id=2, joint=self.joint_2, time=200))
        else:
            self.SingleJoint_pub.publish(ArmJoint(id=4, joint=temp_joint, time=200))
    
    self._reset_joints()
    res = self.SeeWhat()  # Automatic image refresh
    return [True, res[1]] if res[0] else [False, res[1]]

 

InitArmPose() — Initialize the Robotic Arm Pose

Code Description:

  • InitArmPose: Restores the robotic arm to the preset safe initial pose, avoiding the robotic arm being in a dangerous or interfering position

  • ArmJoints(): Creates a 6-joint message object for simultaneously controlling all joints

  • self.init_arm_pose[0]~[5]: The initial pose angle array read from the configuration file common.yaml, assigned to joint1~joint6 in sequence

  • arm_joint.time = 2000: Sets the movement time to 2000 ms (2 seconds), ensuring the robotic arm transitions smoothly to the initial pose

  • self.SixJoint_pub.publish(arm_joint): Publishes the joint angles to the arm6_joints topic, driving the robotic arm

  • time.sleep(1.0): Blocks for 1 second, ensuring the robotic arm basically reaches the target position before returning

xxxxxxxxxx
def InitArmPose(self) -> bool:
    '''Initialize the robotic arm to a safe pose.'''
    # Step 1: Create the joint message object
    arm_joint = ArmJoints()
    
    # Step 2: Set the target angles of the 6 joints
    arm_joint.joint1 = self.init_arm_pose[0]
    arm_joint.joint2 = self.init_arm_pose[1]
    arm_joint.joint3 = self.init_arm_pose[2]
    arm_joint.joint4 = self.init_arm_pose[3]
    arm_joint.joint5 = self.init_arm_pose[4]
    arm_joint.joint6 = self.init_arm_pose[5]
    
    # Step 3: Set the movement time (2000 ms = 2 seconds)
    arm_joint.time = 2000
    
    # Step 4: Publish the joint angles to the topic
    self.SixJoint_pub.publish(arm_joint)
    
    # Step 5: Wait for the robotic arm movement to complete
    time.sleep(1.0)
    return True

Function Description:

  1. Safe pose initialization: Restores the robotic arm to the preset safe initial pose, avoiding the robotic arm being in a dangerous or interfering position

  2. 6-joint synchronous control: Simultaneously controls the 6 joints (joint1~joint6) of the robotic arm to move to the target angles

  3. Movement time control: Sets the movement duration to 2 seconds through time=2000, ensuring the robotic arm transitions smoothly to the initial pose

  4. Blocking wait: time.sleep(1.0) waits for the robotic arm to basically reach the target position before returning


ControlSingleArmJointAngle() — Control a Single Joint Angle

Code Description:

  • ControlSingleArmJointAngle: Individually controls a certain joint of the robotic arm to a specified angle, without affecting the state of other joints

  • arm_joint_id == 6 branch: The 6th joint is the gripper, which performs an angle = 180 - angle flip, because the gripper's mechanical zero point and the angle definition direction are opposite; after the flip it matches intuitive control (180 = fully open, 0 = fully closed)

  • ArmJoint(id=arm_joint_id, joint=angle, time=runtime): Constructs a single-joint control message, where id is the joint number (1~6), joint is the target angle, and time is the movement time (milliseconds)

  • self.SingleJoint_pub.publish(...): Publishes the single-joint control command to the topic, driving the corresponding joint

xxxxxxxxxx
def ControlSingleArmJointAngle(self, arm_joint_id: int, angle: int, runtime: int = 1500) -> bool:
    """ Control a single joint of the robotic arm"""
    # Step 1: Special handling for joint 6 (the gripper)
    if arm_joint_id == 6:
        angle = 180 - angle  # Gripper angle flip
    
    # Step 2: Publish the single-joint control command
    self.SingleJoint_pub.publish(
        ArmJoint(id=arm_joint_id, joint=angle, time=runtime)
    )
    return True

Function Description:

  1. Independent single-joint control: Allows controlling a single joint of the robotic arm independently, without affecting other joints

  2. Gripper angle flip: Joint 6 (the gripper) has special handling angle = 180 - angle, because 0° and 180° of the gripper correspond to the closed and open states respectively, requiring an angle flip to match intuitive control

  3. Configurable movement time: The runtime parameter defaults to 1500 ms (1.5 seconds) and can be adjusted as needed to change the movement speed

Parameter Description:

ParameterTypeDescriptionRange
arm_joint_idintJoint ID (1~6)-
angleintTarget angle (degrees)Depending on the joint type, the range is usually 0~180°
runtimeintMovement time (milliseconds)Default 1500, recommended range 500~3000

 

 

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