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ROSMASTER M3 PRO📖
0.Configuration and Operation Guide
  • 1. Quick start handle to control the car
  • 2. Log in to the car and view the code
  • 3. Robotic Arm Calibration
  • 4. Enter the Docker (Jetson-Nano and Raspberry Pi 5 users, see here)
  • 5. Assembly video
  • 6. Modify the firmware parameters of the car control board
  • 7. Frequently Asked Questions and Precautions
  • 8. Precautions for DIY Robotic Arm
1.Chassis Control Course
  • 1.ROS control
  • 2.Handle control
  • 3.Keyboard control
  • 4.Angular velocity calibration
  • 5.Line velocity calibration
  • 6.Line patrol automatic driving
  • 7.Patrol
2.Lidar Course
  • 1.Lidar introduction and use
  • 2.Dual Lidar fusion
  • 3.Lidar obstacle avoidance
  • 4.Lidar tracking
  • 5.Lidar guard
  • 6.Gmapping-SLAM mapping
  • 7.Cartographer-SLAM mapping
  • 8.slam_toolbox mapping
  • 9.Navigation2 single-point navigation avoid
  • 10.Navigation2 multi-point navigation avoid
  • 11.Repositioning navigation
  • 12.RTAB-Map mapping
  • 13.RTAB-Map navigation
  • 14.APP mapping navigation
  • 15.Machine code handling
  • 16.Color block transport
  • 17.Navigation via Pose-Constrained Visual Relocalizationnew
3.Depth Camera Course
  • 1.Dabai_DCW2 camera introduction
  • 2.Depth pseudo-color image
  • 3.Depth camera distance measurement
  • 4.Wood block volume measurement
  • 5.Mediapipe gesture recognition
  • 6.Edge detection
  • 7.YOLOv8 object detection
  • 8.Deep learning object tracking
  • 9. Transformer Model Tracking Algorithmnew
4.Robotic Arm and 3D Space Gripping Course
  • 1.Robotic arm solution
  • 2.Robotic arm chassis linkage control
  • 3.Machine code ID sorting
  • 4.Sorting height abnormality machine code
  • 5.Tracking and gripping machine code
  • 6.Color block color sorting
  • 7.Sorting height abnormality color block
  • 8.Tracking and gripping color block
  • 9.Wood block shape sorting
  • 10.KCF tracking and gripping objects
  • 11.Medipipe gesture ID sorting machine code
  • 12.Mediapipe gesture height sorting machine code
  • 13.Desktop tracking and gripping machine code
  • 14.3D tracking machine code
  • 15.Line patrol and obstacle removal
5.Road network planning and navigationnew
  • 1. Introduction To Road Network Planning
  • 2. Build A Pose Map
  • 3. Road Network Annotation
  • 4. Planning And Navigation Between Waypoints
  • 5. Road Network Navigation In Any Pose
  • 6. Path Re-planning
6.OpenClaw Basic Coursenew
  • 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 Methodnew
  • 1. OpenClaw Webchat Interaction
  • 2. OpenClaw Tui Interaction
  • 3. OpenClaw Voice Dialogue Interaction
  • 4. OpenClaw WhatsApp Interaction
8.OpenClaw Developmentnew
  • 1. OpenClaw connects to the MCP interface of the robot
  • 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 timed tasks
  • 10. OpenClaw multi-agent intelligent agent
  • 11. OpenClaw active interaction
  • 12. OpenClaw vector memory
9.OpenClaw Embodied intelligent applicationnew
  • 1. OpenClaw target tracking
  • 2. OpenClaw robotic arm tracking and grasping
  • 3. OpenClaw robotic arm fixed-point placement
  • 4. OpenClaw garbage sorting
  • 5. OpenClaw slam mapping and navigation
  • 6. OpenClaw navigation transfer
  • 7. OpenClaw machine code clip
  • 8. OpenClaw color line patrol
  • 9. OpenClaw visual distance measurement
10.OpenClaw scenario sandboxnew
  • 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
  • 01.Register a model service provider account
  • 02. Configuring API-KEY
  • 03. Introduction to Dify
  • 04. Basic Dify Features
  • 05. AI Large Model Development - chatbot
  • 06. Deploy the RAG knowledge base
  • 07. RAG knowledge base + chatbot
  • 08. AI agent workflow
  • 09. Custom wake-up response
  • 10. Core module testing tools
13.AI Large Model (Text Version)
  • 1.Semantic understand instruction following
  • 2.Multimodal visual understand
  • 3.Multimodal visual understand+robotic arm grab
  • 4.Multimodal visual understand+SLAM navigation
  • 5.Robotic arm grab+Multimodal visual understand+SLAM navigation
  • 6.Intention estimation
14.AI Large Model(Voice Version)
  • 1.Semantic understand instruction following
  • 2.Multimodal visual understand
  • 3.Multimodal visual understand+robotic arm grab
  • 4.Multimodal visual understand+SLAM navigation
  • 5.Robotic arm grab+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
17.Multi-vehicle Course
  • 1.Multi-vehicle chassis control
  • 2.Multi-vehicle robotic arm control
  • 3.Multi-vehicle navigation
  • 4.Multi-vehicle formation
18.Control Board Course
  • 1.Development environment setup
  • 2.Control board STM32 basic routine
  • 3.Control board micro_ros basic routine
19.Docker Course
  • 1、Docker overview and docker installation
  • 2、Common commands for docker image containers
  • 3、Docker images deeply understand and publish images
  • 4、Docker hardware interaction and data processing
  • 5、Enter the bot's docker container
  • 6、Robot development environment construction in Docker
20.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
21.Main Control Course
Jetson Nano B01
  • 1. Introduction to the Jetson Nano B01 SUB Board
  • 2. Burn the system image
  • 3. Re-read the memory card or USB drive that has been burned
  • 4. Startup system
  • 5. Jetson Nano B01 System and Desktop Introduction
  • 6. Memory card or USB flash drive expansion
  • 7. Network Configuration
  • 8. SSH remote login & file transfer
  • 9. VNC Remote Login
  • 10. Jetson Nano B01 system backup
  • 11. Jetson Nano Swap space increased
  • 12. Installation and use of Jtop
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
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
Download
  • Mapping_APP(iOS_Android)
  • Robot_Image_System_File
  • Code-Firmware
  • Instruction_Manual
  • VM_File
  • Software_Tools
  • Firmware_DriverFile
  • 3D_Model_File
  • ROS2_Basic_VM
  • Other_Annex
Download ZIP

Welcome to ROSMASTER M3 PRO repository

1.ROS control

ROS Control

ROS Control1. Course Content2. Preparation2.1 Content Description2.2 Starting the Agent3. Startup Commands3.1 Functional Description3.2 Program Startup3.2.1 Connecting to the Agent3.2.2 Viewing Node Information3.3 Publishing Control Commands3.3.1 Controlling the Car's Speed3.3.2 Controlling the Car's Buzzer3.3.3 Controlling the Car's Light Strip3.3.4 Controlling Six Servos3.3.5 Controlling a Single Servo3.4 Subscribing to Car Data3.4.1 Subscribing to Radar Data3.4.2 Subscribing to Battery Level Data3.4.3 Subscribing to IMU Data3.4.4 Subscribing to Odometer Data

1. Course Content

  1. Learn the basics of robot control using ROS.

This function enables control of the robot's speed, buzzer, and robotic arm using ROS2 topic tools. It also enables reading low-level data, such as radar data, IMU data, and odometry data.

2. Preparation

2.1 Content Description

This course uses the Jetson Orin NX as an example. For Raspberry Pi and Jetson Nano boards, you need to open a terminal on the host computer and enter the command to enter the Docker container. Once inside the Docker container, enter the commands mentioned in this course in the terminal. For instructions on entering the Docker container from the host computer, refer to the [Configuration and Operation Guide] -- [Enter the Docker (Jetson Nano and Raspberry Pi 5 users see here)] section of this product tutorial. For Orin and NX boards, simply open a terminal and enter the commands mentioned in this course.

2.2 Starting the Agent

Note: The Docker agent must be started before testing all cases. If it's already started, you don't need to restart it.

Enter the following command in the vehicle terminal:

sh start_agent.sh

The terminal will print the following message, indicating a successful connection.

image-20250613104101795

3. Startup Commands

3.1 Functional Description

This function enables control of the vehicle's speed, buzzer, and robotic arm through ROS2 topic tools. It also enables reading low-level data, such as radar data, IMU data, and odometer data.

3.2 Program Startup

3.2.1 Connecting to the Agent

After booting up, open a terminal and enter the following command to connect to the agent:

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sh start_agent.sh

As shown below, after successfully starting the agent,

image-20250612171011374

If the startup fails, check for loose connections and verify that the serial port /dev/myserial is recognized by running ls /dev.myserial.

3.2.2 Viewing Node Information

After successfully connecting to the agent, you can use the ros2 node list command in the terminal to view the nodes.

Here, you need to open the terminal according to the motherboard. Users of Jetson-Nano and Raspberry Pi 5 need to enter Docker and enter the command. For the instructions for starting Docker, please refer to the content of [Entering Docker (Jetson-Nano and Raspberry Pi 5 users see here)] in [0. Instructions and Installation Steps] of this product tutorial; users of Orin motherboards can directly open the terminal and enter the command. Here, we use the Raspberry Pi 5's runtime interface as an example. After entering Docker, enter the command in the Docker terminal:

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ros2 node list

A screenshot is shown below.

image-20250612173550581

Here, there's a /YB_Node, indicating that the underlying control node has started. Enter the following command to query information about this node, also in the terminal:

xxxxxxxxxx
ros2 node info /YB_Node

A screenshot is shown below.

image-20250612173613881

A table is compiled here, showing which topics this node publishes and subscribes to, as well as the message data type for each topic.

Subscription Topic Table

Subscribed TopicsTopic Message TypeTopic Attributes
/arm6_jointsarm_msgs/msg/ArmJointsControls six servos
/arm_jointarm_msgs/msg/ArmJointControls a single servo
/beepstd_msgs/msg/UInt16Controls the buzzer
/cmd_velgeometry_msgs/msg/TwistControls the car's speed
/rgbstd_msgs/msg/ColorRGBAControls wait

Published topic table

Published topicTopic message typeTopic attributes
/batterystd_msgs/msg/Float32Publishes battery level data
/imu/data_rawsensor_msgs/msg/ImuPublish imu data
/odom_rawnav_msgs/msg/OdometryPublish odometry data
/scan0sensor_msgs/msg/LaserScanPublish left rear radar data
/rgbstd_msgs/msg/ColorRGBAPublish right front radar data

<<<<<<< HEAD

3.3 Publishing Control Commands

According to the table of subscribed topics, use the following command format: ros2 topic pub topic name topic message data type message data --once to publish a frame of control data.

3.3.1 Controlling the Car's Speed

  • Publishing Control Commands

According to the table of subscribed topics, use the following command format: ros2 topic pub topic name topic message data type message data --once to publish a frame of control data.

For the first test, it's recommended to set up the car and test it without its wheels touching the ground. Let's set the car to move forward at a linear velocity of 0.1 m/s. Enter the following command in the terminal:

xxxxxxxxxx
ros2 topic pub /cmd_vel geometry_msgs/msg/Twist "{linear: {x: 0.1, y: 0.0, z: 0.0}, angular: {x: 0.0, y: 0.0, z: 0.0}}" --once

After running, the car will move forward at a speed of 0.1 m/s. Similarly, to control the car to move at an angular velocity of 1.0 rad/s, assign the z value of angular_r to the following command:

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ros2 topic pub /cmd_vel geometry_msgs/msg/Twist "{linear: {x: 0.0, y: 0.0, z: 0.0}} 0.0}, angular: {x: 0.0, y: 0.0, z: 1.0}}" --once

After running, the robot will rotate. To stop, simply publish both the linear velocity and angular velocity to 0. The command is as follows:

xxxxxxxxxx
ros2 topic pub /cmd_vel geometry_msgs/msg/Twist "{linear: {x: 0.0, y: 0.0, z: 0.0}, angular: {x: 0.0, y: 0.0, z: 0.0}}" --once

The --once flag indicates that only one frame of message data will be sent. For other parameters for the ros2 topic pub command, please refer to [19. Common ROS2 Command Tools] in [15. ROS2 Basics] of this product course.

3.3.2 Controlling the Car's Buzzer

To turn on the buzzer, enter the following command in the terminal:

xxxxxxxxxx
ros2 topic pub /beep std_msgs/msg/UInt16 "data: 1" --once

To turn off the buzzer, enter the following command in the terminal:

xxxxxxxxxx
ros2 topic pub /beep std_msgs/msg/UInt16 "data: 0" --once

3.3.3 Controlling the Car's Light Strip

To publish red, enter the following command in the terminal:

xxxxxxxxxx
ros2 topic pub /rgb std_msgs/msg/ColorRGBA "{r: 1.0, g: 0.0, b: 0.0, a: 1.0}" --once

3.3.4 Controlling Six Servos

Set the angles of the six servos to 90 degrees, and the robotic arm to an upward, straight posture. Note: Stand clear of the robotic arm to avoid being hit. Enter the following command in the terminal:

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ros2 topic pub /arm6_joints arm_msgs/msg/ArmJoints {"joint1: 90, joint2: 90, joint3: 90, joint4: 90, joint5: 90, joint6: 90, time: 1500"} --once

The time value here represents the servo operation time, in milliseconds.

3.3.5 Controlling a Single Servo

Set the angle of servo #6 (gripper) to 150 degrees, indicating a gripping state. Enter the following command in the terminal:

xxxxxxxxxx
ros2 topic pub /arm_joint arm_msgs/msg/ArmJoint "{id: 6,joint: 150,time: 2000}" --once

3.4 Subscribing to Car Data

According to the published table, use the command ros2 topic exho topic-name in the following format to receive sensor data published by the car node.

3.4.1 Subscribing to Radar Data

According to the published table, use the command ros2 topic exho topic-name in the following format to receive sensor data published by the car node.

This product has two radars. The topic name for the left rear radar is /scan0, and the topic name for the right front radar is /scan1. For example, using the right front radar data, enter the following command in the terminal:

xxxxxxxxxx
ros2 topic echo /scan1

The subscribed data is shown in the figure below.

image-20250612185123429

For more information about radar data, please visit [6. LiDAR] in this course.

3.4.2 Subscribing to Battery Level Data

Theoretically, the battery voltage for normal operation of this product should be above 10.3V and below 12V. If it falls below 10.3V, the buzzer will beep, indicating that the battery voltage is too low and needs to be charged. You can enter the following command in the terminal to query the battery voltage:

xxxxxxxxxx
ros2 topic echo /battery

The subscribed data is shown in the figure below.

image-20250612185726290

Here, the battery voltage is 11.8V.

3.4.3 Subscribing to IMU Data

The control board has a 9-axis IMU that provides feedback on the car's attitude. Enter the following command in the terminal to retrieve IMU data:

xxxxxxxxxx
ros2 topic echo /imu/data_raw

The subscribed IMU data is shown in the figure below.

image-20250612190200979

3.4.4 Subscribing to Odometer Data

This product's four motors are equipped with encoders. The ROS control board reads the encoder information and publishes calculated odometer data. Enter the following command in the terminal to read the odometer data:

xxxxxxxxxx
ros2 topic echo /odom_raw

Subscribing to odometer data is shown below:

image-20250612190531906

Precautions for DIY Robotic Arm
Handle control

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