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ROSMASTER M3📖
00.Configuration and Operation Guide
  • 1.Quick start handle to control the car
  • 2.Log in to the car and view the code
  • 3.Enter the Docker (For RPI5)
  • 4.Camera and Radar Configuration (Must Read)
  • 5.Assembly video
  • 6.Modify Control Board Firmware Parameters
01.Chassis Control Course
  • 01.ROS control
  • 02.Handle control
  • 03.Keyboard control
  • 04.Robot state estimation
  • 05.Data remote visualization
  • 06.Line velocity calibration
  • 07.Angular velocity calibration
  • 08.Robot URDF model
  • 09.Line patrol automatic driving
  • 10.Patrol
02.Lidar Course
  • 01.Lidar introduction and use
  • 02.Lidar point cloud fusion and filtering
  • 03.Lidar obstacle avoidance
  • 04.Lidar tracking
  • 05.Lidar guard
  • 06.Gmapping-SLAM mapping
  • 07.Cartographer-SLAM mapping
  • 08.slam_toolbox mapping
  • 09.Lifelong mapping
  • 10.Navigation2 single-point navigation avoid
  • 11.Navigation2 multi-point navigation avoid
  • 12.Cartographer relocalization navigation
  • 13.slam_toolbox localization and navigation
  • 14.Synchronous mapping and navigation
  • 15.RTAB-Map mapping
  • 16.RTAB-Map navigation
  • 17.APP mapping and navigation
03.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
04.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
05.AI Model - Voice Version
  • 1.Semantic understand and command follow
  • 2.Multimodal visual understanding
  • 3.Multimodal visual understanding+SLAM navigation
  • 4.Intention estimation
06.AI Model - Text Version
  • 1.Semantic understand and command follow
  • 2.Multimodal visual understanding
  • 3.Multimodal visual understanding+SLAM navigation
  • 4.Intention estimation
07.Road Network Planning and Navigation
  • 1.Introduction and Quick Start
  • 2.Constructing a Pose Map
  • 3.Road Network Labelling
  • 4.Inter-Road Network Planning and Navigation
  • 5.Free-Pose Road Network Navigation
  • 6.Path Replanning
08.Autonomous Driving expand(Need purchase track map)
  • 01.Environment Setup & Precautions
  • 02.YOLO Environment Configuration
  • 03.Data Collection
  • 04.Data Annotation
  • 05.YOLOv11 Model Training
  • 06.Model Format Conversion
  • 07.Vehicle Centerline Calibration
  • 08.Lane Detection
  • 09.Lane-Keeping Autonomous Driving
  • 10.Traffic Sign Recognition
  • 11.Comprehensive Autonomous Driving Applications
  • 12.Autonomous Driving Debugging Module
  • 13.Road Network Planning with Track Map
  • 14.Road Network Planning with Traffic Sign Recognition
  • 15.AI Model with Road Network Planning
  • 16.AI Model with Track Map and SLAM Navigation
  • 17.AI Model with Road Network Planning and Autonomous Driving
09.Depth Camera Course
  • 01.Dabai_DCW2 Camera Introduction
  • 02.Nuwa-HP60C Camera Introduction
  • 03.Depth Pseudo-Color Image
  • 04.Depth Camera Distance Measurement
  • 05.Wood Block Volume Measurement
  • 06.Edge Detection
  • 07.YOLOv11 Object Detection
  • 08.YOLOv11 Object Tracking
  • 09.Color Following
  • 10.Face Following
  • 11.QR Code Following
  • 12.Machine Code Following
  • 13.KCF Object Tracking
  • 14.QR Code Motion Control
  • 15.AR Vision
10.Mediapipe Visual Course
  • 01.Hand Detection
  • 02.Posture Detection
  • 03.Overall Detection
  • 04.Facial Landmark Detection
  • 05.3D Object Recognition
  • 06.Face Detection
  • 07.Gesture Recognition
  • 08.Face Special Effects
  • 09.Brush
  • 10.Finger Control
  • 11.Palm Target Positioning
  • 12.Fingertip Trajectory Recognition
  • 13.Gesture Following
  • 14.Posture Following
  • 15.Gesture Motion Control
11.Multi-vehicle Course
  • 1.Multi-vehicle Control
  • 2.Multi-vehicle Navigation
  • 3.Multi-vehicle Platoon
12.AI Large Model Basic Course
Offline large model (Text Interaction)
  • 0. AI Large Model Mirroring Explanation
  • 1. Deployment of large-scale AI models
  • 2. Installation of the large model dialogue platform
  • 3. Meta AI Llama 3.2 model
  • 4. Alibaba Cloud Qwen3 Model
  • 5. DeepSeek DeepSeek-R1 model
  • 6. Microsoft Phi-4 mini model
  • 7. Alibaba Cloud Qwen2.5vl Visual Multimodal Large Model
  • 8. Google Gemma3 Visual Multimodal Large Model
  • 9. Llava Visual Multimodal Large Model
  • 10. Multimodal Visual Understanding Applications
  • 11.MiniCPM-V Visual Multimodal Large Model
  • 12. Multimodal Text-Based Image Application
  • 13. Multimodal Video Analysis Application
  • 14. Multimodal table scanning application
  • 15. Multimodal visual positioning applications
  • 16. Multimodal Autonomous Agent Application
Offline large model (Voice Interaction)
  • 0. Voice Interaction Hardware Connection (Must Read)
  • 1. Offline speech-to-text (ASR)
  • 2. Offline Text-to-Speech (TTS)
  • 3. AI large model voice interaction
  • 4. Multimodal visual understanding and voice interaction
  • 5. Multimodal Text-Based Image Application
  • 6. Multimodal Video Analysis Application
  • 7. Multimodal visual positioning applications
  • 8. Multimodal table scanning application
  • 9. Multimodal Autonomous Agent Applications
  • 10. AI large model offline voice assistant
Online large model (Text Interaction)
  • 1. OpenRouter Large Model API Aggregation Platform
  • 2. Multimodal visual understanding applications
  • 3. Multimodal visual positioning applications
  • 4. Multimodal table scanning application
  • 5. Multimodal Autonomous Agent Applications
Online large model (Voice Interaction)
  • 0. Voice Interaction Hardware Connection (Must Read)
  • 1. Online speech-to-text (ASR)
  • 2. Online Text-to-Speech (TTS)
  • 3. AI large model voice interaction
  • 4. Multimodal visual and voice interaction
  • 5. Multimodal visual positioning applications
  • 6. Multimodal table scanning application
  • 7. Multimodal Autonomous Agent Applications
  • 8. AI large model online voice assistant
13.Control Board Course
1.Development environment setup
  • 1.Introduction to the Control Board
  • 2.Set up the STM32CUBEIDE development environment
  • 3.Burning STM32 firmware using SWD
  • 4.Burning STM32 firmware using serial port
  • 5.Compile the microros driver library
  • 6.Install and start the microros agent
  • 7.Import Project
2.Control board STM32 basic routine
  • 1.Turn on the LED light
  • 2.Button functions
  • 3.Drive the buzzer
  • 4.Serial communication
  • 5.Battery voltage detection
  • 6.Driving PWM Servo
  • 7.Drive motor
  • 8.Read motor encoder data
  • 9.PID control of motor speed
  • 10.Robot kinematics analysis theory
  • 11.Read IMU data
  • 12.Read Lidar data
  • 13.Flash access data
  • 14.Driving OLED Displays
  • 15.Driving RGB light strip
  • 16.SBUS model aircraft remote control
  • 17.USB controller remote control
  • 18.CAN bus communication
3.Control board micro_ros basic routine
  • 1.Post a topic
  • 2.Subscribe to a topic
  • 3.Multi-topic subscription and publishing
  • 4.Subscribe to the buzzer topic
  • 5.Subscribe to the bus servo topic
  • 6.Subscribe to the rate control topic
  • 7.Release Speed Topic
  • 8.Publish IMU data topic
  • 9.Publish radar data topic
14.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
15.YOLOv11 Development (ORIN)
  • 1.YOLO environment construction
  • 2.CLI use
  • 3.Object detection
  • 4.Instance segmentation
  • 5.Pose estimation
  • 6.Image classification
  • 7.Oriented object detection
  • 8.Model conversion
  • 9.Dataset annotation
  • 10.Model Training_Conversion
  • 11.Model prediction
16.YOLOv11 Development(RDKX5)
  • 1.YOLO environment construction
  • 2.CLI use
  • 3.Object detection
  • 4.Instance segmentation
  • 5.Pose estimation
  • 6.Image classification
  • 7.Oriented object detection
  • 8.Model prediction
  • 9.Model Quantization
17.YOLOv11 Development (RPI)
  • 1.YOLO environment construction
  • 2.CLI use
  • 3.Object detection
  • 4.Instance segmentation
  • 5.Pose estimation
  • 6.Image classification
  • 7.Oriented object detection
  • 8.Model conversion
  • 9.Model prediction
18.Linux Operating System
  • 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
19.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
20.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
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
Download
  • Mapping_APP(iOS_Android)
  • MainBoard_AI_Pure_System
  • 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 repository

2.Log in to the car and view the code

Log in to the Car and Viewing the Code

Log in to the Car and Viewing the Code0. Course Content1. How to Connect the Car to the Network1.1 Wired Connection1.2 Wireless Connection2. Connecting to the Car2.1 SSH Connection Method2.2 VNC Connection Method2.2.1 Orin Nano without a Screen2.2.2 Logging into the Car3. Viewing the Code3.1 Visual Studio Code3.2 jupyter-lab4. Source Code Workspace Explanation

0. Course Content

[!IMPORTANT]

The content of this section is very important. It covers the basic skills for editing program files and logging into the car, which are fundamental for subsequent tutorials.

  • Master several ways to log in to the car and view the code.
  • Recommended workflow for this chapter: Connect to the car's hotspot/insert a network cable to get an IP → Check the IP on the OLED screen → Log in via VNC → Disable the self-generated hotspot and connect to your own Wi-Fi (for running large models later) → Check the updated IP on the OLED → Reconnect via VNC → View the source code.
  • The default hotspot name for the factory image is: ROSMASTER-M3, the password is: 12345678, and the default IP is: 192.168.8.88.

 

1. How to Connect the Car to the Network

1.1 Wired Connection

  • Insert a network cable into the mainboard's network port (ensure the cable has internet access for the car to connect to the internet).

1.2 Wireless Connection

Note: Different mainboards only have different UI icons, but the method for connecting to Wi-Fi is basically the same. Click the Wi-Fi icon, then click to select a network, and enter your Wi-Fi password (ensure the Wi-Fi has internet access for the car to connect to the internet).

image-20260129165408736

 

 

2. Connecting to the Car

Regardless of the connection method, both the computer and the car need to be on the same local area network (LAN). The simplest way to achieve this is to connect to the same Wi-Fi or hotspot. First, connect to the car's default hotspot, ROSMASTER-M3, with the Wi-Fi password 12345678. After a successful connection, you can use the following methods to log in.

You can also directly connect a network cable to the mainboard. The OLED screen will automatically update the IP address after connecting. The following operations are demonstrated using the IP address obtained after connecting the network cable.

 

2.1 SSH Connection Method

[!TIP]

  • There are many SSH connection tools available. Here, we recommend tools for Windows systems. MacOS and Linux users can choose other SSH tools.

 

  • Use PuTTY, MobaXterm, or another SSH login tool to connect to the car. We will use PuTTY as an example. You can download PuTTY here: Download PuTTY: latest release (0.83)
  • Choose and install the version corresponding to your computer. After successful installation, double-click to open it. The PuTTY interface is shown below:

image-20250725102432201

Select SSH, and then enter the IP address displayed on the OLED screen in the Host Name (or IP address) field. My IP address here is 192.168.2.92, so I enter it as shown below:

image-20250725102719479

Next, click Open. A terminal interface and a pop-up window will appear. Click Accept, as shown below:

image-20250725102823043

The terminal will then display login as. Enter the username for the car's mainboard and press Enter. You will then be prompted for a password. Enter the password. The usernames and passwords for each mainboard are as follows:

MainboardUsernamePassword
Raspberry Pi 5piyahboom
RDK X5sunriseyahboom
Orin-Nanojetsonyahboom
Orin-NXjetsonyahboom

 

Assuming my mainboard is an Orin-Nano, I would enter jetson, press Enter, and then enter the password yahboom. Nothing will be displayed as you type the password. Press Enter.

image-20250725103109017

A successful connection to the car looks like this:

image-20250725103601663

This only opens a terminal and does not display a graphical interface. Therefore, SSH is suitable for logging in when you don't need to start graphical programs and is ideal for running non-GUI examples and operating the car via commands.

2.2 VNC Connection Method

2.2.1 Orin Nano without a Screen

[!IMPORTANT]

  • Orin Nano users without a screen should refer to this section. Other mainboard users can ignore this part.

 

  • Since the Orin mainboard uses Ubuntu 22.04, this system requires a screen to enter the graphical interface. Users who did not purchase a screen package may have trouble opening the visual interface. Here, we provide a method for displaying the visual interface using a virtual desktop, intended only for Orin mainboard users without a connected screen. Orin users with a screen, as well as Jetson Nano and Raspberry Pi users, can skip this step.

Open the Data-19.Attachments-Virtual Desktop Files. Copy xorg.conf.backup_dp and xorg.conf.backup_vnc to the /etc/X11 directory.

Install the virtual desktop environment xserver-xorg-video-dummy:

sudo apt-get install xserver-xorg-video-dummy

Open a terminal and enter the following command to open the virtual desktop and switch to VNC mode:

xxxxxxxxxx
sudo cp /etc/X11/xorg.conf.backup_vnc /etc/X11/xorg.conf

Reboot the system, and you will be able to enter the desktop without a screen (continue with the VNC connection tutorial in 2.2.2).

xxxxxxxxxx
sudo reboot

Note: After switching to VNC mode, the DP connection will be disabled (i.e., connecting a screen to the mainboard will not display anything). You need to revert the configuration to use the DP interface normally.

To disable the virtual desktop:

If you need to connect a DP display, open a terminal and enter the following command to switch to DP display mode:

xxxxxxxxxx
sudo cp /etc/X11/xorg.conf.backup_dp /etc/X11/xorg.conf

Reboot the system, and you can now use a DP cable to connect a display.

xxxxxxxxxx
sudo reboot

 

2.2.2 Logging into the Car

[!TIP]

There are many VNC connection tools. Here, we recommend a tool for Windows. MacOS and Linux users can choose other VNC tools.

  • VNC allows users to remotely access and control another computer's desktop environment over a network. So, when we need to access the car's desktop environment, for example, to start a graphical display, we can use VNC to connect. You can download VNC here: Download VNC Viewer by RealVNC®

Download and install the version for your computer. After installation, double-click to open it. The screen will look like this:

image-20250725105127650

Enter the car's IP address. My IP here is 192.168.2.92, as shown below:

image-20250725105232162

Then press Enter.

image-20250725105315827

  • Enter the username in the Username field and the password in the Password field (refer to the table in 2.1; the password for all mainboards is yahboom), then click OK to enter the desktop, as shown below:

image-20250725105510621

If you see an abnormal screen, such as the following:

image-20250725105612931

And it keeps disconnecting, you need to adjust the settings as shown below:

image-20250725105853102

Then reconnect. The Orin mainboard can only have one remote desktop connection at a time. If the connection fails, check if a remote desktop is already connected.

After connecting, since large AI models require an internet connection, and the self-generated hotspot is only a local network with no actual data, you need to switch networks to use the AI model features later.

 

3. Viewing the Code

[!IMPORTANT]

  • This part is very important for users who need to develop or view the source code.
  • If you only need to view and edit configuration files, the easiest way is to connect via SSH and use the nano tool.
  • The tools mentioned here are just recommendations. You can use any editing tool you prefer.

 

3.1 Visual Studio Code

  • Visual Studio Code is a lightweight, efficient, and extensible development tool with integrated core development tools, making it one of the most popular development tools in the world.

Official website: https://code.visualstudio.com/

  • If you don't have Visual Studio Code installed, you can download and install it from the link above.

 

  • Start Visual Studio Code, click on the Extensions icon on the left, and install the Remote-SSH, Remote - SSH: Editing Configuration Files, and Remote Explorer extensions.

image-20260107173441245

 

  • Then click the Remote Explorer icon on the left and click to create a new remote connection.

image-20260107174218199

 

  • In the pop-up input box, enter username@IP_address based on your mainboard, press Enter, and then enter the user password yahboom to log in to the car.

image-20260107174323437

 

  • Then click Open Folder. In the pop-up window, you can select the folder you want to view. Here, we use yahboomM3_ws (the core source code directory for ROSMASTER-M3) as an example, and then click OK.

image-20260107175055474

 

  • After that, you can see all the files in the folder in the Explorer on the left.

image-20260107175337260

 

Below are several methods for viewing code, which will be convenient for editing and modifying code later.

 

3.2 jupyter-lab

Jupyter-lab starts automatically on boot, so you just need to open a browser and enter ip_address:8888 to use Jupyter to view the code. My IP address is 192.168.2.92, so I enter the following in my browser:

image-20250725111737793

Then press Enter. If prompted for a password, enter yahboom, and you will enter the jupyter-lab interface, as shown below:

image-20250725112817507

You can view and edit the code by selecting the content in the folder on the left.

  • For Raspberry Pi 5 users:

You need to enter the Docker container, then enter the command jupyter-lab --allow-root. In your browser, enter car_ip:8888 to start jupyter-lab and view the car's code. As shown below, I enter the car's container, cd to the /root directory, and then enter jupyter-lab --allow-root in the terminal.

image-20250725113426816

Then in the browser, enter the car's ip_address:8888. My Raspberry Pi's IP is 192.168.2.22, so I enter 192.168.2.22:8888, as shown below:

image-20250725113602612

Press Enter. If a password is required, enter yahboom, and you can enter jupyter-lab to view the code.

 

4. Source Code Workspace Explanation

xxxxxxxxxx
├── code_ws
├── pyproject.toml
├── README.md
├── ros2_kilted
├── split_video.py
├── user_ws
├── uv.lock
└── yolo_train
  • code_ws: Workspace for storing core code.
  • README.md: File containing quick start instructions.
  • user_ws: User code workspace for storing all startup files and configuration files.
  • ros2_kilted: Code folder for road network planning and navigation.
  • yolo_train: Folder for storing YOLOv11 training datasets and program files.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Quick start handle to control the car
Enter the Docker (For RPI5)

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