yahboom
HomeLearn
Solution
Blog
Online Store
About Us
EN/中文
ROSMASTER R2📖
1.Preparation and First Trial
  • 1.1 Accessories introduction
  • 1.2 Precautions for battery
  • 1.3 First Trial
2.Assembly steps
  • Installaction Video
3.ROS1-Remote control course
  • 3.1 APP remote control
  • 3.2 Model aircraft remote control
  • 3.3 Handle remote control
4.ROS1-Hardware course
  • 4.1 About expansion board_V3.0
  • 4.1 About expansion board_V1.0
  • 4.2 STM32 Development environment
  • 4.3 Button to control the buzzer to whistle
  • 4.4 FreeRTOS application
  • 4.5 Serial communication
  • 4.6 SBUS model aircraft remote control
  • 4.7 CAN bus communication
  • 4.8 RGB colorful light bar
  • 4.9 Timer interrupt to control PWM servo
  • 4.10 Control serial port servos
  • 4.11 Nine-axis attitude sensor to obtain data
  • 4.12 Control motor
  • 4.13 Timer captures the encoder data
  • 4.14.1 Kinematic Analysis of Mecanum Wheel
  • 4.14.2 Kinematics Analysis of Ackermann Car
  • 4.15 PID control robot movement
5.ROS1-Basic course
  • 5.1 Update the firmware
  • 5.2 Turn off the self-starting process at startup
  • 5.3 Install the Rosmaster driver library
  • 5.4 Buzzer whistle
  • 5.5 Control PWM servo
  • 5.6 RGB colorful light bar special effects display
  • 5.7 Control motor
  • 5.8 Control robot movement
  • 5.9 Control Serial Servo
6.ROS1-Linux operating system
  • 6.1 Virtual machine installation and use
  • 6.2 Linux basics
  • 6.3 Remote control
  • 6.4 Multi-machine communication configuration
  • 6.5 Static IP and hotspot mode
  • 6.6 Bind the device ID
  • 6.7 Web page real-time monitoring
  • 6.8 Expansion tutorial
  • 6.9.1 Jetson Nano write sytem
  • 6.9.2 Jetson Xavier NX write system
  • 6.9.3 Jetson TX2 NX write system
  • 6.9.4 Raspberry Pi write system
7.ROS1-Docker-pi5
  • 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
  • 7、How customers can update docker images in the future
8.ROS1-ROS basic course
  • 1.ROS introduction
  • 2.ROS installation
  • 3.ROS common command tools
  • 4.ROS workspace
  • 5.ROS function package
  • 6.ROS node
  • 7.ROS topic publisher
  • 8.ROS topic subscribers
  • 9.ROS service client
  • 10.ROS service server
  • 11.ROS action client
  • 12.ROS action server
  • 13.ROS custom message reception
  • 14.ROS-launch file
  • 15.ROS-TF transformation
  • 16.ROS parameter service
  • 17.ROS-rviz use
  • 18.ROS-rqt tool usage
  • 19.Topic message recording and playback
  • 20.urdf model introduction
  • 21.gazebo introduction
  • 22.ROS distributed communication
9.ROS1-OpenCV courses
  • 9.1 Getting started with Open Source CV
  • 9.2 Geometric transformation
  • 9.3 Image processing and drawing text line segments
  • 9.4 Image beautification
  • 9.5 Opencv application
  • 9.6 AR vision
  • 9.7 AR QR code
  • 9.8 ROS+Opencv foundation
  • 9.9 ROS+Opencv application
  • 9.10 Data transformation and point cloud
  • 9.11 MediaPipe development
10.ROS1-Robot control course
  • 10.1 PID algorithm theory
  • 10.2 Robot PID debugging
  • 10.3 Robot information release
  • 10.4 Robot keyboard control
  • 10.5 Robot handle control
  • 10.6 Robot state estimation
  • 10.7 Robot calibration
  • 10.8 Robot URDF model
11.ROS1-Depth camera course
  • 11.1 How to use the Astra camera
  • 11.2 Astra camera calibration
  • 11.3 Astra Color Tracking
  • 11.4 Astra Object Tracking
  • 11.5 Visual tracking autopilot
  • 11.6 Pure visual 2D mapping and navigation
  • 11.7 RTAB-Map 3D mapping navigation
  • 11.8 ORB_SLAM2 basics
  • 11.9 ORB_SLAM2_Octomap
12.ROS1-Lidar course
  • 11.1 Lidar basic-SLAM
  • 11.1 Lidar basic-EAI
  • 11.2 Lidar avoiding
  • 11.3 Lidar guard
  • 11.4 Lidar follow
  • 11.5 Patrol game
  • 11.6 gmapping mapping
  • 11.7 hector mapping
  • 11.8 karto mapping
  • 11.9 cartographer mapping
  • 11.10 rrt_exploration mappin
  • 11.11 AMCL
  • 11.12 Navigation and avoiding
  • 11.13 APP mapping and navigation
  • 11.14 TEB path planning algorithm
13.ROS1-Multi-robot control course
  • 13.1 Multi-machine handle control
  • 13.2 Multi-machine navigation
  • 13.3 Multi-machine formation
  • 13.4 Multi-machine surround
14.ROS1-Deep learning courses
  • 14.1 KNN recognizes handwritten digits
  • 14.2 Basic use of TensorFlow
  • 14.3 Basic use of PyTorch(jetson)
  • 14.4 yolov5 model training(jetson)
  • 14.5 yolov5+tensorrt acceleration(jetson)
  • 14.6 yolov4-tiny
15.ROS1-Voice control courses
  • 15.0 How to use old voice module in new image
  • 15.1 Introduction of voice control module-NEW
  • 15.2 Voice control module port binding-NEW
  • 15.1 Introduction of voice control module-Old
  • 15.2 Voice control module port binding-Old
  • 15.3 Voice control car movement
  • 15.4 Voice control Autopilot
  • 14.5 Voice control color recognition
  • 15.6 Voice control color tracking
  • 15.7 Voice control multi-point navigation
16.ROS1-Model training Autopilot
  • 16.0 ReadMe
  • 16.1 yolov5 to train traffic signs
  • 16.2 TensorRt acceleration identification mark
  • 16.3 Road sign indication function description
  • 16.4 Collect data
  • 16.5 Training model
  • 16.6 Model transformation and application
  • 16.7 AI Autopilot
17. ROS2-Remote control course
  • 1. APP remote control
  • 2. Model aircraft remote control
  • 3. Handle remote control
18.ROS2-Hardware course
  • 1. Expansion board introduction_V3.0
  • 1. Expansion board introduction_V1.0
  • 2. STM32 development environment build
  • 3. Key control buzzer sounding
  • 4. FreeRTOS applications
  • 5. Serial communication
  • 6. SBUS model airplane remote control
  • 7. CAN bus communication
  • 8. RGB colorful light bar
  • 9. Timer interrupt control PWM servos
  • 10. Control serial servos
  • 11. Nine-axis attitude sensor acquires data
  • 12. Control motor forward and reverse
  • 13. Timer Capture Encoder Data
  • 14. Theory of Robot Kinematics Analysis
  • 14.1.Mecanum wheel
  • 14.2.Ackerman
  • 14.3.4WD
  • 15. PID control of robot motion
19. ROS2-Basic course
  • 1. Update the firmware of the expansion board
  • 2.Close the large self-starting program at boot
  • 3. Install Rosmaster driver library
  • 4. Buzzer sounding
  • 5. Control PWM servo
  • 6. RGB colorful light bar special effects show
  • 7. Control motor forward and reverse
  • 8. Controlling robot motion
  • 9. Control serial servos
20. ROS2-Linux operating systemnew
  • 01. Virtual Machines
  • 02. Linux Basics
  • 03. Remote control
  • 04. Multi-computer communication configuration
  • 05. Static ip and hotspot mode
  • 06. Bind device ID
  • 07.Webpage real-time monitoring
  • 08. Expansion Tutorial
  • 09-1.Jetson Nano write system file
  • 09-2. Raspberry Pi write system file
  • 09-3.Orin write system
  • 10.Jetpack old system upgraded to SUPER systemnew
21.ROS2 -Docker(Nano Pi)
  • 1. docker overview and docker installation
  • 2. docker image container common command
  • 3. docker image in-depth understanding and publishing images
  • 4. docker hardware interaction and data processing
  • 5. Enter the docker container of the robot
  • 6. docker in the robot development environment build
  • 7. Customer's method of updating docker images in the future
22.ROS2- ROS2 Basic Tutorial
  • 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
23. ROS2-Robot control course
  • 1. PID algorithm theory
  • 2. Robot information release
  • 3. Robot control
  • 4. Robot state estimation
  • 5. Robot calibration
  • 6. URDF model
24. ROS2-Lidar course
  • 1-1. Introduction and use of SLAM lidar
  • 1-2. Introduction and use of 4ROS lidar
  • 2. Lidar obstacle avoidance fun gameplay
  • 3. Lidar tracking fun gameplay
  • 4. Patrol function play
  • 5. gmapping map building algorithm
  • 6. cartographer building algorithm
  • 7. Navigation and obstacle avoidance
  • 8. Rosmaster_R2 using the app to build maps
  • 9. Rosmaster_R2 navigating with the app
25. ROS2-OpenCV courses
  • 1. opencv basic course
  • 2. ROS+opencv application
  • 3. QR code creation and recognition
  • 4. AR Vision
  • 5. mediapipe fun gameplay
  • 6. Patrol line autopilot
26. ROS2-Depth camera courses
  • 1. Depth camera use
  • 2. Camera calibration
  • 3. Color tracking
  • 4. KCF object tracking
  • 5. ORB_SLAM2 Basics
  • 6. ORB_SLAM2 PCL mapping
  • 7. ORB_SLAM2 Octomap mapping
  • 8. RTAB-Map 3D mapping navigation
27.ROS2- Voice control courses
  • 0. How to use old voice module in new image
  • 1.1 Introduction to the module-New
  • 1.2 Voice Control Module Port Binding-New
  • 1.3 Introduction to the module-Old
  • 2. Voice control car movement
  • 3. Voice control autopilot
  • 4. Voice control color recognition
  • 5. Voice control color tracking
  • 6. Voice control multi-point navigation
28.Deep learning courses(SUPER)
  • 1.KNN recognizes handwritten digitsnew
  • 2.Basic use of TensorFlownew
  • 3.Basic use of PyTorch(jetson)new
  • 4.YOLOv11Model conversion(SUPER)new
  • 5.YOLOv11Dataset annotation(SUPER)new
  • 6.YOLOv11Model conversion + tensorrt acceleration(SUPER)new
  • 7.YOLOv11Object recognition(SUPER)new
29. ROS2-Multi-robot control
  • 1. Multi-robot control
  • 2. Multi-robot navigation
LLM tutorial
1.Development environment
  • 0. Model usage instructions
  • 1.Environments deployment
  • 2.Dialogue platform installation
2.Jetson Nano B01
  • 1.Qwen2 model
  • 2.TinyLlama model
  • 3.Phi-3 model
  • 4.Gemma model
  • 5.Orca Mini model
  • 6.StarCoder2 model
  • 7.DeepSeek-R1 model
  • 8.Expand LLaVA-Phi3
3.Jetson Orin NXNANO
  • 1.Llama3 model
  • 2.Qwen2 model
  • 3.Phi-3 model
  • 4.Gemma model
  • 5.WizardLM2 model
  • 6.Codellama model
  • 7.DeepSeek-R1 model
  • 8.Orca Mini model
  • 9.StarCoder2 model
  • 10.TinyLlama model
  • 11.Expand LLaVA
  • 12.Expand LLaVA-Phi3
4.Raspberry Pi 5B
  • 1.Meta AI Llama3 model
  • 2.Qwen2 model
  • 3.Phi-3 model
  • 4.Gemma model
  • 5.WizardLM2 model
  • 6.Meta AI Codellama model
  • 7.DeepSeek-R1 model
  • 8.Expand LLaVA
FAQ
  • 1.Using your own Jetson board, car cannot start normally
Download
  • RemoteCtrl_APP(iOS/Android)
  • Mapping_APP(iOS_Android)
  • Instruction Manual
  • SystemFile_ROS1
  • SystemFile_ROS2
  • SystemFile_ROS2_OrinNANOSUPER
  • SystemFile_ROS2_OrinNXSUPER
  • VM software
  • Code
  • Jetson_Boot_USB.tar.gz
  • Autopilot Annex
  • Other_Annex_File
  • LLM_SystemFile
  • ROS2_Basic_VM
Download ZIP

Welcome to ROSMASTER R2 repository

1.3 Introduction to the module-Old

1. Introduction of voice module

1. Module introduction and port binding usage

1.1. Introduction to voice control module

1.1.1, CSK4002 chip

The voice control module on ROSMASTER is developed based on the CSK4002 chip. CSK4002 is a high-performance, powerful computing power, low power consumption, and resource-rich AISoC developed and designed for the AloT field. It can be widely used in smart homes, smart appliances, and emerging consumer electronics industries.

  • CSK4002 uses the Andes D1088 core. Its AI/DSP acceleration module MVA supports a variety of Neural Network operators and vector operations. It is deeply adapted to the iFlytek AI algorithm of HKUST and has a computing power of up to 128GOPS.

  • Comes with 8M Flash, 8M PSRAM, 1M SRAM.

  • Supports 8 channels of PDM audio input and 16 channels of I2S Audio Input data processing.

  • Integrate rich mainstream peripheral interfaces: GPIO/UART/I2C/SPI/QSPI/SDIO/USB1.1/SDIO, etc.

  • Equipped with low-latency embedded operating system Free RTOS, complete BSP driver, and comprehensive development tool resources.

1.1.2. Module features

  • Far-field sound pickup: The front end adopts iFlytek's dual-microphone array algorithm, which can achieve 360-degree far-field 5m user sound pickup. Equipped with automatic gain for vocals, which can be adaptively adjusted according to the user's volume to ensure that the overall audio experience is consistent after noise reduction.

  • Echo cancellation: During user interaction, when the device is broadcasting content or music, the user can wake up and interrupt the broadcast process for the next round of interaction, making the interaction experience more natural.

  • Voice broadcast: Voice broadcast means that the user wakes up the device and speaks command words, and the device performs corresponding reply broadcast responses; or active prompts. The purpose of voice broadcast is to give feedback to the user by broadcasting a reply when the user issues a voice command or in an appropriate scenario.

  • Offline command: When the device is awake, the user speaks a command word (instruction) within a specified range. After receiving the information, the voice module performs related processing based on the content of the command word, or transmits the content information to the host computer for related processing.

  • Peripheral communication: The module receives input from the microphone for processing, and then communicates with other devices through USB, I2S, SDIO and other interfaces. There is also general programmable IO to communicate with other devices.

  • Environmental noise reduction: It is widely used for environmental noise reduction in homes, cars, offices and other scenes. It can reduce noise while retaining human voice information to the greatest extent.

1.2. Using modules

1.2.1. Wiring

The module is connected to the ROSMASTER main control (or HUB board) through a universal Type-c data cable, and the speaker and module are connected through a PH2.0 data cable.

  • As shown in the picture below, one end of the Micro-USB data cable is connected to the USB-connet port of the module, and the other end is connected to the port of the ROSMASTER motherboard (After this is plugged in, it cannot be modified after the later ports are bound. , please refer to the next section for details)

image-20230423095309183

  • As shown in the figure below, the PH2.0 data line port is connected to the Speaker port on the module.

    image-20230423095344921

1.2.2. Wake-up word

The wake-up word is "Hello, Xiaoya". When waking up, the speaking speed needs to be slowed down. If it is too fast, the module will not recognize it. After waking up the module, other command words can be recognized later. Within 20 seconds of waking up, there is no need to wake up again, just say the command word.

1.2.3. Command words

  1. Voice control car movement

image-20230423095636151

  1. Voice control RGB light strip effect

image-20230423095713637

  1. Voice control color recognition

image-20230423095752738

  1. Voice control color tracking

image-20230423095833711

  1. Voice-controlled autonomous driving (line patrol)

image-20230423095916558

6), Voice control multi-point navigation

image-20230423095959503

1.3. Voice control module port binding

Preface: Because the ID device numbers of the ROS expansion board and the voice control module are the same, they cannot be modified according to the method in the previous tutorial.

Row ID device number binding. Not binding ports may cause port conflicts or device identification errors, and the bound ports cannot be changed at will

Change position, otherwise the binding will be invalid. This course is completed on the host machine. There is no need to bind it in the dock. This section uses the Raspberry Pi as the host machine to demonstrate. Before binding, you need to annotate the part involving myserial in the original host rule file. off, otherwise the voice board and the ROS expansion board will be recognized as the same device, and the terminal input will

x
sudo gedit /etc/udev/rules.d/serial.rules

image-20230523173336251

As shown in the figure above, annotate the binding content related to myserial, save and exit, enter the following command in the terminal to reload the rules,

xxxxxxxxxx
sudo udevadm trigger
sudo service udev reload
sudo service udev restart

1.3.1. Bind the ROS expansion board device number

x
ll /dev/ttyUSB*
ll /dev/rplidar
  • First, without connecting to the voice control board, you can get ttyUSB0 and ttyUSB1

    image-20230523173630409

    Here ttyUSB0 is the device number recognized by the radar, then ttyUSB1 is the device number of the ROS expansion board.

  • Then, we first check the port information of the ROS expansion board, mainly to check the device path information and terminal input.

    x
    udevadm info --attribute-walk --name=/dev/ttyUSB1 |grep devpath

    The following information is obtained (the actual situation shall prevail here). The red box illustrates the path information of the device.

    image-20230423101504052

  • Then, we modify the /etc/udev/rules.d/serial.rules file, first bind the port number of the ROS expansion board, and enter it in the terminal.

    x
    sudo gedit /etc/udev/rules.d/serial.rules 

    As shown below, replace the content

    Before replacement

    x
    KERNEL=="ttyUSB*",ATTRS{idVendor}=="1a86",ATTRS{idProduct}=="7523",MODE:="0777",SYMLINK+="myserial"

    After replacement

    x
    KERNEL=="ttyUSB*",ATTRS{devpath}=="1.4.3",ATTRS{idVendor}=="1a86",ATTRS{idProduct}=="7523",MODE:="0777",SYMLINK+=" myserial"
  • Exit after saving, enter the following three commands in the terminal to reload the device,

    xxxxxxxxxx
    sudo udevadm trigger
    sudo service udev reload
    sudo service udev restart

1.3.2. Bind the voice board port number

  • Connect to the voice board and enter the following command on the terminal to view the device number.

    x
    ll /dev/ttyUSB*

image-20230423102111038

Here we find that the system recognizes the voice board as /dev/ttyUSB2, then we enter the following command to view the device path

information,

x
udevadm info --attribute-walk --name=/dev/ttyUSB2 |grep devpath

Get the following picture,

image-20230423102546485

  • Then, we modify the /etc/udev/rules.d/myspeech.rules file, bind the port number of the voice board, and enter it in the terminal,

    xxxxxxxxxx
    sudo gedit /etc/udev/rules.d/myspeech.rules

    Add content as shown in the picture below,

    x
    KERNEL=="ttyUSB*",ATTRS{devpath}=="1.4.2",ATTRS{idVendor}=="1a86",ATTRS{idProduct}=="7523",MODE:="0777",SYMLINK+=" myspeech"
  • Exit after saving, enter the following statement in the terminal to reload the system device

    xxxxxxxxxx
    sudo udevadm trigger
    sudo service udev reload
    sudo service udev restart
    Voice Control Module Port Binding-New
    Voice control car movement

COMPANY

  • About us
  • Team Style
  • Blog

LEARNING & EXPLORATION

  • Tutorials
  • Edge AI hardware
  • Educational robots
  • Embedded intelligent hardware

WHERE TO BUY

  • Yahboom Online Store
  • Amazon
  • Alibaba
  • AliExpress
  • Mercado

TECHNOLOGY SUPPORT

  • Email: support@yahboom.com

BE A DISTRIBUTOR

  • Email: sales@yahboom.com
QR Code
QR Code

Copyright © 2017-2026 Yahboom. All Rights Reserved.

EN/中文