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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

3.Keyboard control

Keyboard Control

Keyboard Control1. Course Content2. Preparation2.1 Content Description2.2 Starting the Agent3. Running the Example3.1 Starting Keyboard Control3.2 Key Control Instructions3.2.1 Direction Control3.2.2 Speed Control4. Source Code Analysis4.1 View the Node Relationship Graph4.2 Viewing Topic Messages and Message Types4.3 Program Flowchart4.4 Source Code Analysis4.41 Published Topic: cmd_vel4.42 Movement Dictionary and Speed Dictionary

1. Course Content

Learn how to control robot movement using the keyboard and its principles.

After running the program, use keyboard keys to publish speed topics to control the robot chassis' movement.

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 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, refer to the product tutorial [Configuration and Operation Guide] - [Enter the Docker (Jetson Nano and Raspberry Pi 5 users see here)]. 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 examples. If it's already started, you don't need to restart it.

Enter the command in the vehicle terminal:

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sh start_agent.sh

The terminal prints the following message, indicating a successful connection.

image-20250613104101795

3. Running the Example

3.1 Starting Keyboard Control

Note:

  • The Jetson Nano and Raspberry Pi series controllers must first enter the Docker container (for steps, see the [Docker Course Section - Entering the Robot's Docker Container]).

Run the keyboard control node on the vehicle terminal or in the virtual machine:

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ros2 run yahboomcar_ctrl yahboom_keyboard

image-20250616142158970

3.2 Key Control Instructions

3.2.1 Direction Control

[i] or [I][linear, 0][u] or [U][linear, angular]
[,][-linear, 0][o] or [O][linear, -angular]
[j] or [J][0, angular][m] or [M][-linear, -angular]
[l] or [L][0, -angular][.][-linear, angular]

3.2.2 Speed Control

KeySpeed ChangeKeySpeed Change
【q】Increase both linear and angular velocities by 10%【z】Decrease both linear and angular velocities by 10%
【w】Increase only linear velocity by 10%【x】Decrease only linear velocity by 10%
【e】Increase only angular velocity by 10%【c】Decrease only angular velocity by 10%
【t】Switch linear velocity between X-axis and Y-axis【s】Stop keyboard control

4. Source Code Analysis

Source code path:

jetson orin nano, jetson orin NX:

/home/jetson/yahboomcar_ws/src/yahboomcar_ctrl/yahboomcar_ctrl/yahboom_keyboard.py

Jetson Orin Nano, Raspberry Pi:

You need to enter Docker first.

xxxxxxxxxx
root/yahboomcar_ws/src/yahboomcar_ctrl/yahboomcar_ctrl/yahboom_keyboard.py

4.1 View the Node Relationship Graph

Open a terminal and enter the command:

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ros2 run rqt_graph rqt_graph

image-20250616143401077

From the node relationship diagram, we can see:

yahboom_keyboard_ctrl: Controls the robot chassis by publishing the /cmd_vel topic

/YB_Node: The robot chassis node subscribes to the /cmd_vel topic and uses the inverse kinematic solution to calculate the speed of each wheel, thereby controlling the robot's movement.

4.2 Viewing Topic Messages and Message Types

Open a terminal and enter the command:

xxxxxxxxxx
ros2 topic echo /cmd_vel

When controlling the robot chassis' movements using the keyboard, data is published to the /cmd_vel topic by printing messages.

image-20250616144001600

Enter the following command to view the message type of the /cmd_vel topic:

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ros2 topic info /cmd_vel

image-20250616144619887

The Type column indicates that the message type of the /cmd_vel topic is geometry_msgs/msg/Twist. Enter the following command to view the composition of the geometry_msgs/msg/Twist message type:

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ros2 interface show geometry_msgs/msg/Twist

image-20250616144910112

From the composition of the above message types, we can see that the robot chassis movement is controlled by two vector groups: linear (linear velocity) and angular (angular velocity). Each data element is a float64 floating-point number. The following explains the meaning of each data element.

  • linear float64 x: x-axis velocity float64 y: y-axis velocity float64 z: z-axis velocity
  • angular float64 x: x-axis angular velocity float64 y: y-axis angular velocity float64 z: z-axis velocity : z-axis angular velocity

Because the robot chassis can only move within a two-dimensional plane, only linear-x (x-axis velocity), linear-y (y-axis velocity), and angular-z (z-axis angular velocity) are published when controlling the robot via the keyboard.

4.3 Program Flowchart

按键为 't' 或 'T'
Key is 't' or 'T'
按键为's'或 'S'
Key is 's' or 'S'
按键为空格
Key is space
按键在 moveBindings 中
Key in moveBindings
其他按键
Other keys
是
Yes
否
No
按键在 speedBindings 中
Key in speedBindings
是
Yes
否
No
按键为 Ctrl+C
Key is Ctrl+C
开始
Start
初始化ROS节点和参数
Initialize ROS node and parameters
设置初始参数
Set initial parameters
打印控制说明
Print control instructions
获取按键输入
Get key input
切换速度模式
Toggle speed mode
切换键盘控制状态
Toggle keyboard control
强制停止
Force stop
设置运动方向
Set movement direction
计数增加
Increase counter
计数 > 4?
Counter > 4?
平滑停止
Smooth stop
调整速度
Adjust speed
速度是否超过限制?
Is speed over limit?
设置为限制值
Set to limit
发布当前速度
Publish current speed
结束程序
Exit program
发布停止消息
Publish stop message
恢复终端设置
Restore terminal settings
销毁节点并关闭ROS
Destroy node and shutdown ROS
结束
End

4.4 Source Code Analysis

Source Code Path:

Jetson Orin Nano, Jetson Orin NX:

xxxxxxxxxx
/home/jetson/yahboomcar_ws/src/yahboomcar_ctrl/yahboomcar_ctrl/yahboom_keyboard.py

Jetson Orin Nano, Raspberry Pi:

You need to first enter Docker.

xxxxxxxxxx
root/yahboomcar_ws/src/yahboomcar_ctrl/yahboomcar_ctrl/yahboom_keyboard.py

4.41 Published Topic: cmd_vel

xxxxxxxxxx
pub = rospy.Publisher('cmd_vel', Twist, queue_size=1)

Just package the speed and publish it via pub.publish(twist). The chassis' speed subscriber will receive the speed data and then drive the car.

4.42 Movement Dictionary and Speed Dictionary

  • The movement dictionary mainly stores characters related to direction control

    xxxxxxxxxx
    moveBindings = {
        'i': (1, 0),
        'o': (1, -1),
        'j': (0, 1),
        'l': (0, -1),
        'u': (1, 1),
        ',': (-1, 0),
        '.': (-1, 1),
        'm': (-1, -1),
        'I': (1, 0),
        'O': (1, -1),
        'J': (0, 1),
        'L': (0, -1),
        'U': (1, 1),
        'M': (-1, -1),
    }
  • The speed dictionary mainly stores the characters related to speed control

    xxxxxxxxxx
    speedBindings = {
        'Q': (1.1, 1.1),
        'Z': (.9, .9),
        'W': (1.1, 1),
        'X': (.9, 1),
        'E': (1, 1.1),
        'C': (1, .9),
        'q': (1.1, 1.1),
        'z': (.9, .9),
        'w': (1.1, 1),
        'x': (.9, 1),
        'e': (1, 1.1),
        'c': (1, .9),
    }

    4.43 Get the current key information

    xxxxxxxxxx
        def getKey(self):
            tty.setraw(sys.stdin.fileno())
            rlist, _, _ = select.select([sys.stdin], [], [], 0.1)
            if rlist: key = sys.stdin.read(1)
            else: key = ''
            termios.tcsetattr(sys.stdin, termios.TCSADRAIN, self.settings)
            return key

    4.44 Determine the key value and publish the /cmd_vel speed topic

    xxxxxxxxxx
    while (1):
        key = yahboom_keyboard.getKey()
        if key=="t" or key == "T": xspeed_switch = not xspeed_switch
        elif key == "s" or key == "S":
            print ("stop keyboard control: {}".format(not stop))
            stop = not stop
        if key in moveBindings.keys():
            x = moveBindings[key][0]
            th = moveBindings[key][1]
            count = 0   
        elif key in speedBindings.keys():
            speed = speed * speedBindings[key][0]
            turn = turn * speedBindings[key][1]
            count = 0
            if speed > yahboom_keyboard.linenar_speed_limit: 
                speed = yahboom_keyboard.linenar_speed_limit
                print("Linear speed limit reached!")
            if turn > yahboom_keyboard.angular_speed_limit: 
                turn = yahboom_keyboard.angular_speed_limit
                print("Angular speed limit reached!")
            print(yahboom_keyboard.vels(speed, turn))
            if (status == 14): print(msg)
            status = (status + 1) % 15
        elif key == ' ': (x, th) = (0, 0)
        else:
            count = count + 1
            if count > 4: (x, th) = (0, 0)
            if (key == '\x03'): break
        if xspeed_switch: twist.linear.x = speed * x
        else: twist.linear.y = speed * x
        twist.angular.z = turn * th
        if not stop: yahboom_keyboard.pub.publish(twist)
        if stop:yahboom_keyboard.pub.publish(Twist())

     

Handle control
Angular velocity calibration

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