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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

5.Compile the microros driver library

Compile the microros driver library

Compile the microros driver library1. Install the cross-compiler2. Get the STM32-microros library file3. Modify parameters4. Add environment variables5. Start compiling6. Solve the include problem7. The final file8. Import STM32CUBEIDE project

Note: You must use Ubuntu to compile the microros driver library. Ubuntu 22.04 is recommended.

1. Install the cross-compiler

Open the download address and download the Linux version of the cross-compiler.

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https://developer.arm.com/downloads/-/gnu-rm

image-20241111105344406

After decompression, put the file in the following path

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/opt/gcc-arm-none-eabi

And add the executable file path to the .bashrc environment variable in the user directory.

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export PATH=$PATH:/opt/gcc-arm-none-eabi/bin

2. Get the STM32-microros library file

Download and compile the microros setup tool

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mkdir uros_ws && cd uros_ws
git clone -b humble https://github.com/micro-ROS/micro_ros_setup.git src/micro_ros_setup
rosdep update && rosdep install --from-paths src --ignore-src -y
colcon build
source install/local_setup.bash

Use the microros setup tool to generate the STM32-microros library file.

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ros2 run micro_ros_setup create_firmware_ws.sh generate_lib

image-20241119212537670

Check the workspace. We should now have five folders, among which the firmware folder contains the STM32-microros library files. build firmware install log src

image-20241111114344529

3. Modify parameters

Open the toolchain.cmake file

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vim ~/uros_ws/firmware/toolchain.cmake

Copy the following content into

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set(CMAKE_SYSTEM_NAME Generic)
set(CMAKE_CROSSCOMPILING 1)
set(CMAKE_TRY_COMPILE_TARGET_TYPE STATIC_LIBRARY)
​
# SET HERE THE PATH TO YOUR C99 AND C++ COMPILERS
# Add the compiler path here
set(PIX /opt/gcc-arm-none-eabi/bin)
set(CMAKE_C_COMPILER ${PIX}/arm-none-eabi-gcc)
set(CMAKE_CXX_COMPILER ${PIX}/arm-none-eabi-g++)
​
set(CMAKE_C_COMPILER_WORKS 1 CACHE INTERNAL "")
set(CMAKE_CXX_COMPILER_WORKS 1 CACHE INTERNAL "")
​
# SET HERE YOUR BUILDING FLAGS
set(FLAGS "-O2 -ffunction-sections -fdata-sections -fno-exceptions -mcpu=cortex-m7 -mfpu=fpv5-d16 -mfloat-abi=hard -nostdlib -mthumb --param max-inline-insns-single=500 -D'RCUTILS_LOG_MIN_SEVERITY=RCUTILS_LOG_MIN_SEVERITY_NONE'" CACHE STRING "" FORCE)
# -mcpu=cortex-m7 indicates the microcontroller architecture
# -mfpu=fpv5-d16 -mfloat-abi=hard indicates support for hardware floating-point compilation
set(CMAKE_C_FLAGS_INIT "-std=c11 ${FLAGS} -DCLOCK_MONOTONIC=0 -D'__attribute__(x)='" CACHE STRING "" FORCE)
set(CMAKE_CXX_FLAGS_INIT "-std=c++11 ${FLAGS} -fno-rtti -DCLOCK_MONOTONIC=0 -D'__attribute__(x)='" CACHE STRING "" FORCE)
​
set(__BIG_ENDIAN__ 0)

Save and exit.

Open the colcon.meta file

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vim ~/uros_ws/firmware/colcon.meta

Copy the following content into

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{
    "names": {
        "tracetools": {
            "cmake-args": [
                "-DTRACETOOLS_DISABLED=ON",
                "-DTRACETOOLS_STATUS_CHECKING_TOOL=OFF"
            ]
        },
        "rosidl_typesupport": {
            "cmake-args": [
                "-DROSIDL_TYPESUPPORT_SINGLE_TYPESUPPORT=ON"
            ]
        },
        "rcl": {
            "cmake-args": [
                "-DBUILD_TESTING=OFF",
                "-DRCL_COMMAND_LINE_ENABLED=OFF",
                "-DRCL_LOGGING_ENABLED=OFF"
            ]
        },
        "rcutils": {
            "cmake-args": [
                "-DENABLE_TESTING=OFF",
                "-DRCUTILS_NO_FILESYSTEM=ON",
                "-DRCUTILS_NO_THREAD_SUPPORT=ON",
                "-DRCUTILS_NO_64_ATOMIC=ON",
                "-DRCUTILS_AVOID_DYNAMIC_ALLOCATION=ON"
            ]
        },
        "microxrcedds_client": {
            "cmake-args": [
                "-DUCLIENT_PIC=OFF",
                "-DUCLIENT_PROFILE_UDP=OFF",
                "-DUCLIENT_PROFILE_TCP=OFF",
                "-DUCLIENT_PROFILE_DISCOVERY=OFF",
                "-DUCLIENT_PROFILE_SERIAL=OFF",
                "-UCLIENT_PROFILE_STREAM_FRAMING=ON",
                "-DUCLIENT_PROFILE_CUSTOM_TRANSPORT=ON",
                "-DUCLIENT_PROFILE_SHARED_MEMORY=ON",
                "-DUCLIENT_SHARED_MEMORY_MAX_ENTITIES=20"
            ]
        },
        "rmw_microxrcedds": {
            "cmake-args": [
                "-DRMW_UXRCE_MAX_NODES=1",
                "-DRMW_UXRCE_MAX_PUBLISHERS=10",
                "-DRMW_UXRCE_MAX_SUBSCRIPTIONS=10",
                "-DRMW_UXRCE_MAX_SERVICES=1",
                "-DRMW_UXRCE_MAX_CLIENTS=1",
                "-DRMW_UXRCE_MAX_HISTORY=10",       
                "-DRMW_UXRCE_TRANSPORT=custom"
            ]
        }
    }
}

"-DRMW_UXRCE_MAX_NODES=1", #maximum number of nodes;

"-DRMW_UXRCE_MAX_PUBLISHERS=10", #maximum number of publisher;

"-DRMW_UXRCE_MAX_SUBSCRIPTIONS=10", #maximum number of subscribers;

"-DRMW_UXRCE_MAX_SERVICES=1", #maximum number of servers;

"-DRMW_UXRCE_MAX_CLIENTS=1", #maximum number of clients;

"-DRMW_UXRCE_MAX_HISTORY=10", #history;

"-DRMW_UXRCE_TRANSPORT=custom" #custom transport interface

Save and exit.

4. Add environment variables

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export RMW_IMPLEMENTATION=rmw_microxrcedds

5. Start compiling

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cd ~/uros_ws/
ros2 run micro_ros_setup build_firmware.sh $(pwd)/firmware/toolchain.cmake $(pwd)/firmware/colcon.meta

Note: Since the compilation process requires downloading many files, and most file servers are located abroad, if there is a network anomaly, please solve the network download problem yourself.

View the generated static library and header files

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ls firmware/build

6. Solve the include problem

Since the generated include folder path is too long, you need to use a script to fix it.

Create a new fix_include.sh script in the firmware folder

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cd ~/uros_ws/firmware
vim fix_include.sh

Copy the following content into

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#!/bin/bash
######## Fix include paths ########
​
BASE_PATH=build
​
pushd mcu_ws > /dev/null
    INCLUDE_ROS2_PACKAGES=$(colcon list | awk '{print $1}' | awk -vd=" " '{s=(NR==1?s:sd)$0}END{print s}')
popd > /dev/null
​
for var in ${INCLUDE_ROS2_PACKAGES}; do
    if [ -d "${BASE_PATH}/include/${var}/${var}" ]; then
        rsync -r ${BASE_PATH}/include/${var}/${var}/* $BASE_PATH/include/${var}
        rm -rf ${BASE_PATH}/include/${var}/${var}
    fi
done
​
mkdir ${BASE_PATH}/libmicroros
mv ${BASE_PATH}/libmicroros.a ${BASE_PATH}/libmicroros

Save and exit.

Run the following command to fix the include folder problem.

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bash fix_include.sh

7. The final file

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ls ~/uros_ws/firmware/build
ls ~/uros_ws/firmware/build/libmicroros
ls ~/uros_ws/firmware/build/include

image-20250718175416103

8. Import STM32CUBEIDE project

Create a new Microros folder in the project, and then copy the include and libmicroros folders generated by the previous step into Microros.

image-20250718175519812

Right-click to open the project properties, then click [Settings]->[MCU/MPU GCC Compiler]->[include paths] to add the microros include directory path, and then click [Apply] to take effect.

image-20250718172816586

Add the microros folder as the project source code path.

image-20250718173605596

Import the microros library path

image-20250718173416595

Link the microros library file to the project. Make sure the name matches the libmicroros.a static library file name (excluding the prefix and suffix "microros").

image-20250718173332032

Burning STM32 firmware using serial port
Install and start the microros agent

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