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ROSMASTER X3📖
1.About ROSMASTER X3
  • 1.1 Wiring Introduction
  • 1.2 Precautions for battery
  • 1.3 First Trial
2.Assembly steps
  • Installation Video(1-10)
  • Installation Video(11-18)
  • Installation Video(20-28)
  • Installation Video(29-30)
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
  • 12.1 Lidar basic-SLAM
  • 12.1 Lidar basic-4ROS
  • 12.2 Lidar avoiding
  • 12.3 Lidar guard
  • 12.4 Lidar follow
  • 12.5 Patrol game
  • 12.6 gmapping mapping algorithm
  • 12.7 hector mapping algorithm
  • 12.8 karto mapping algorithm
  • 12.9 cartographer mapping algorithm
  • 12.10 rrt_exploration mapping algorithm
  • 12.11 AMCL
  • 12.12 Navigation and avoiding
  • 12.13 APP mapping and navigation
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 control
  • 2. Model aircraft control
  • 3. Wireless Handle Control Tutorial
18.ROS2- Hardware course
  • 1. About expansion board_V1.0
  • 1. About expansion board_V3.0
  • 2. STM32 Development environment
  • 3. Button control
  • 4. FreeRTOS application
  • 5. Serial communication
  • 6. SBUS model aircraft remote control
  • 7. CAN bus communication
  • 8. RGB colorful light bar
  • 9. Timer interrupt to control PWM servo
  • 10. Control serial port servos
  • 11. Nine-axis attitude sensor to obtain data
  • 12. Control motor
  • 13. Timer captures the encoder data
  • 14. Robot kinematics analysis theory
  • 15. PID control robot movement
19.ROS2- ROSMASTER basic course
  • 1. Update the firmware
  • 2. Turn off the self-starting process at startup
  • 3. Install the Rosmaster driver library
  • 4. Buzzer whistle
  • 5. Control PWM servo
  • 6. RGB colorful light bar special effects display
  • 7. Control motor
  • 8. Control robot movement
  • 9. Control Serial Servo
20.ROS2- Linux operating systemnew
  • 1. Virtual machine installation and use
  • 2. Linux basics
  • 3. Remote control
  • 4. Multi-machine communication configuration
  • 5. Static IP and hotspot mode
  • 6. Bind the device ID
  • 7. Web page real-time monitoring
  • 8. Expansion tutorial
  • 9.1 Jetson Nano write sytem
  • 9.2 Raspberry Pi write system
  • 9.3 Orin series write system
  • 10.Jetpack old system upgraded to SUPER systemnew
21.ROS2- Docker(Nano Pi)
  • 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. Entering the Docker Container of the Robot
  • 6. Building a Robot Development Environment in Docker
  • 7. Method for customers to update 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- Depth camera course
  • 1.Depth camera usage
  • 2. Camera internal reference 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
25.ROS2- Lidar course
  • 1. Introduction and Use of Lidar
  • 2. Lidar avoiding
  • 3. Lidar follow
  • 4. Lidar guard
  • 5. Patrol game
  • 6. Gmapping mapping algorithm
  • 7. Cartographer mapping algorithm
  • 8. Navigation and obstacle avoidance
  • 9. Rosmaster_ X3 conducts mapping through the APP
  • 10. Rosmaster_ X3 Navigation through APP
26.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、line patrol automatic driving
27.ROS2- Voice control courses
  • 0.How to use old voice module in new image
  • 1. Introduction of voice module-new
  • 2. Voice control module port binding-new
  • 1. Introduction of voice module and port binding-old
  • 3. Voice control car movement
  • 4. Voice control Autopilot
  • 5. Voice control color recognition
  • 6. Voice control color tracking
  • 7. 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, ROSMASTER X3 cannot start normally
Download
  • RemoteCtrl_APP(Android/iOS)
  • Mapping_APP(iOS_Android)
  • Instruction Manual
  • SystemFile_ROS2
  • SystemFile_ROS1
  • SystemFile_ROS2_OrinNANOSUPER
  • SystemFile_ROS2_OrinNXSUPER
  • Code
  • Jetson_Boot_USB.tar.gz
  • VM software
  • Autopilot Annex
  • Other_Annex_File
  • LLM_SystemFile
  • ROS2_Basic_VM
Download ZIP
FAQ
  • 1、How to connect OLED?

Welcome to ROSMASTER X3 repository

10.5 Robot handle control

  • 5. Robot handle control

    According to different models, just set the purchased model in [.bashrc], X1 (normal four-wheel drive) X3 (Mailun) X3plus (Mailun robotic arm) R2 (Ackerman differential) etc. , this section takes X3 as an example

    ​x
    #Raspberry Pi 5 master needs to enter docker first, please perform this step
    #If running the script into docker fails, please refer to ROS/07, Docker tutorial
    ~/run_docker.sh
    #Multiple ros commands require multiple terminals to be executed in the same docker container. Please refer to the tutorials in Sections 07/5 and 5.8.

    Open the [.bashrc] file

    xxxxxxxxxx
    sudo vim .bashrc

    Find the [ROBOT_TYPE] parameter and modify the corresponding model

    xxxxxxxxxx
    export ROBOT_TYPE=X3 # ROBOT_TYPE: X1 X3 X3plus R2 X7

     

    5.1. Operating environment

    Operating system: Ubuntu 18.04 LTS

    ROS version: melodic

    Equipment: jetson nano/Raspberry Pi, PC, wireless controller (USB receiver)

    Controller function code path: ~/yahboomcar _ws/src/yahboomcar_ctrl/scripts

    5.2. Install driver

    ROS driver for universal Linux controllers. The Joy package contains Joy_node, a node that connects a generic Linux controller to ROS. This node publishes a "/Joy" message containing the current state of each button and axis of the controller.

    xxxxxxxxxx
    sudo apt install ros-melodic-joy ros-melodic-joystick-drivers

    5.3. Usage steps

    5.3.1. Device connection

    First, connect the USB end of the wireless controller to the device (jetson, Raspberry Pi, PC). This lesson takes connecting the USB end of the wireless controller to Jetson as an example. Connect the mouse, keyboard, and monitor; or you can also connect remotely via VNC.

    5.3.2. View device

    Open the terminal and enter the following command. [js0] is displayed. This is the wireless controller. In special cases, you can also view the changes in the device list through the two states of accessing and not accessing the USB end of the wireless controller. If there is a change, the changed device will be the same; otherwise, the connection will be unsuccessful or unrecognized.

    xxxxxxxxxx
    ls /dev/input

    image-20220302120317676

    Note: If a keyboard or mouse or other device is connected to ROSMASTER first, the remote control receiver will be recognized as other devices. Therefore, if you need to connect a keyboard or mouse, you can connect the remote control receiver first and then connect it. into other devices.

    5.3.3. Test handle

    Open the terminal and enter the following command. As shown in the picture, the wireless handle has 8 axial inputs and 15 key inputs. You can press the keys individually to test the numbers corresponding to the keys.

    xxxxxxxxxx
    sudo jstest /dev/input/js0

    image-20220302121526295

    If jstest is not installed, run the following command:

    xxxxxxxxxx
    sudo apt-get install joystick

    5.3.4. Run the handle node

    Open three terminals and enter the following commands in order to view detailed information, which is the same as [Test Controller]. Depending on the device (Raspberry Pi, Jetson Nano, PC) and the system, the controller status will be different.

    xxxxxxxxxx
    roscore
    rosrun joy joy_node
    rostopic echo joy #Print released information

    image-20220302120815104

    5.4. Control the little turtle with the handle

    5.4.1. Start

    xxxxxxxxxx
    roslaunch yahboomcar_ctrl twist_joy.launch

    image-20220302122239082

    1), view nodes

    xxxxxxxxxx
    rostopic list

    image-20220328175003554

    1. View speed topic information

    image-20220328175136329

    1. Correspondence between the handle and the operation of the little turtle

    handlelittle turtle
    On the left joystickForward
    Left joystick downBackward
    Right joystick leftTurn left
    Right joystick rightTurn right
    1. View the node graph

    【/joy_node】:Node of controller information

    【/twist_joy】:Nodes controlled by the handle

    【/turtlesim_node】:The node of the little turtle

    The node [/joy_node] publishes the topic [/joy] so that the node [/twist_joy] subscribes. After processing, it publishes the topic [/turtle1/cmd_vel] so that the node [/turtlesim_node] subscribes to drive the movement of the little turtle.

    image-20220302122408394

    5.5. Handle control ROSMASTER

    Controlling ROSMASTER with a handle is similar to controlling a little turtle with a handle; let the handle control node establish contact with the underlying drive node of ROSMASTER, change the current state of the handle, send different information to ROSMASTER, and drive ROSMASTER to make different reactions. Corresponding to different models of ROSMASTER, what we need to control is also different.

    For the ROSMASTER-X3 (Mecanum wheel), what we can control through the handle are the buzzer, the light strip, the linear speed of the car's movement (x-axis and y-axis), and the angular speed of the car's movement.

    5.5.1. Start handle control

    1. Reference path of handle control yahboom_joy.launch file

    xxxxxxxxxx
    ~/yahboomcar_ws/src/yahboomcar_ctrl/launch/

    2), start

    xxxxxxxxxx
    roslaunch yahboomcar_bringup bringup.launch #Start chassis and handle control, the launch of handle control is yahboom_joy.launch

    After turning it on, press the "START" button and hear the buzzer sound to start remote control. The remote control will enter sleep mode after being turned on for a period of time. You need to press the "START" button to end sleep.

    3), remote control effect description

    HandleEffect
    Left joystick up/downCar forward/backward to go straight
    Left joystick left/rightThe car goes straight left/right
    Right joystick left/rightRotate car left/right
    Right "1" keyControl light strip effect
    "2" key on the rightEnd/start other functions
    "START" buttonControl buzzer/end sleep
    Press the left joystickAdjust the X/Y axis speed
    Press the right joystickAdjust the angular velocity

     

    1. View the node graph

    xxxxxxxxxx
    rqt_graph

    image-20220302150953183

    The red box part is the topic communication between the handle control node/yahboom_joy and the underlying node/driver_node.

    5), program analysis

    Underlying control program:

    xxxxxxxxxx
    Mcnamu_driver.py

    The code path is:

    xxxxxxxxxx
    ~/yahboomcar_ws/src/yahboomcar_bringup/scripts

    In Mcnamu_driver.py, the subscribers and their respective callback functions for the topic information of the buzzer, speed control, and light strip are defined,

    xxxxxxxxxx
    self.sub_cmd_vel = rospy.Subscriber('cmd_vel', Twist, self.cmd_vel_callback, queue_size=100) #Speed control
    self.sub_RGBLight = rospy.Subscriber("RGBLight", Int32, self.RGBLightcallback, queue_size=100) #Light strip control
    self.sub_Buzzer = rospy.Subscriber("Buzzer", Bool, self.Buzzercallback,
    queue_size=100) #Buzzer control
    
    
    def cmd_vel_callback(self, msg) #Speed callback function
    def RGBLightcallback(self, msg) #Light strip callback function
    def Buzzercallback(self, msg) #Buzzer callback function

    Handle control program:

    xxxxxxxxxx
    yahboom_joy.py

    The code path is:

    xxxxxxxxxx
    ~/yahboomcar_ws/src/yahboomcar_ctrl/scripts

    In yahboom_joy.py, define the publisher of the buzzer, speed control, and light strip topic information, and publish these messages

    xxxxxxxxxx
    self.pub_cmdVel = rospy.Publisher('cmd_vel', Twist, queue_size=10) #Speed control
    self.pub_RGBLight = rospy.Publisher("RGBLight", Int32, queue_size=10) #Light strip control
    self.pub_Buzzer = rospy.Publisher("Buzzer", Bool, queue_size=1) #Buzzer control
    
    
    self.pub_cmdVel.publish(twist) #Publish velocity data
    self.pub_RGBLight.publish(self.RGBLight_index) #Publish light strip data
    self.pub_Buzzer.publish(self.Buzzer_active) #Publish buzzer data

    6), code analysis

    • /joy topic data analysis

      Run the joy_node node and view the /joy topic information,

    xxxxxxxxxx
    rosrun joy joy_node
    rostopic echo joy

    In the printed information, there are two arrays: axes and buttons. The data they store is the behavior of the joystick and buttons on the remote control. You can press each button on the remote control one by one to correspond to the transformation of the array, and you can know what behavior will cause which variable in the array to change its value.

    • Knowing the changes in the /joy topic data corresponding to the keystroke behavior, then in yahboom_joy.py, we only need to make judgments on these values. There are also two categories in yahboom_joy.py. The first step is to determine the name of the system (the first step is to determine whether the handle receiver is plugged into a jetson or a Raspberry Pi/PC (here it refers to a virtual machine)),

    xxxxxxxxxx
    if self.user_name == "jetson": self.user_jetson(joy_data)
             else: self.user_pc(joy_data)
    • Value judgment: Take the jetson processor to judge the buzzer data as an example. Analysis shows that we use the "START" button to control the buzzer, and it corresponds to buttons[11]. When it is pressed At this time, buttons[11] will become 1. At this time, we can send the buzzer data,

      xxxxxxxxxx
       if joy_data.buttons[11] == 1:
       self.Buzzer_active=not self.Buzzer_active
          # print "self.Buzzer_active: ", self.Buzzer_active
          self.pub_Buzzer.publish(self.Buzzer_active)

      Other remote control behaviors are analyzed by analogy.

      Note: When judging the left and right of the left rocker, only the data of X3 (Mecanum wheel) and X3 Plus (Mecanum wheel + robotic arm) are valid, because of the characteristics of their wheels, they can move laterally. So there is speed on the Y axis.

      xxxxxxxxxx
       ylinear_speed = self.filter_data(joy_data.axes[0]) * self.yspeed_limit * self.linear_Gear

    5.6. Precautions when using the handle

    • When connecting the USB handle receiver, it is recommended to connect it to the outermost USB-HUB expansion board instead of directly connecting to the motherboard or the middle USB-HUB expansion board (X3plus). If it is directly connected to the motherboard or the middle USB-HUB expansion board (X3plus), due to the aluminum alloy blocks on the top and bottom, it will seriously interfere with the handle signal reception.

    • After plugging and unplugging the handle receiver, you need to restart the handle program, otherwise you will not be able to control the car.

    • After starting the handle control program, if the handle cannot control the car, it may be caused by the wrong handle control mode. You can press and hold the handle mode button for about 15 seconds to switch modes. After the green indicator light is always on, press the start button again, such as If a buzzer sounds, the switch is successful. If there is no response, you can press and hold the mode button on the handle again for 15 seconds.

      jetson series support mode: PC/PCS mode

      Raspberry Pi series support mode: X-BOX mode

    ECB7ADF3-824E-4cc6-AE49-5536DF2ACA27

    • After re-plugging or unplugging the handle receiver or restarting the motherboard, the handle will be reset to factory mode. If it cannot be controlled, the mode will need to be switched again every time it is plugged in, unplugged or restarted.

Robot keyboard control
Robot state estimation

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