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ROSMASTER X3 Plus📖
1.Preparation and First Trial
  • 1.1 Wiring Introduction
  • 1.2 Precautions for battery
  • 1.3 First Trial
  • 1.4 Precautions for DIY Robotic Arm
2. Assembly steps
  • Installation Video
3.Remote control course
  • 3.1 APP remote control
  • 3.2 Model aircraft remote control
  • 3.3 Handle remote control
4.Hardware course
  • 4.1 About expansion board_V3.0
  • 4.1 About expansion board_V1.0
  • 4.2 STM32 Development
  • 4.3 Button to control the buzzer
  • 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
  • 4.10 Control serial port servos
  • 4.11 Nine-axis attitude sensor
  • 4.12 Control motor
  • 4.13 Timer captures the encoder data
  • 4.14 Kinematic Analysis
  • 4.15 PID control robot movement
5.Basic course
  • 5.1 Update the firmware
  • 5.2 Turn off the self-starting process
  • 5.3 Install the Rosmaster driver
  • 5.4 Buzzer whistle
  • 5.5 Control PWM servo
  • 5.6 RGB colorful light bar
  • 5.7 Control motor
  • 5.8 Control robot movement
  • 5.9 Control Serial Servo
6.Linux operating system
  • 6.1 Virtual machine installation
  • 6.2 Linux basics
  • 6.3 Remote control
  • 6.4 Multi-machine communication
  • 6.5 Static IP and hotspot mode
  • 6.6 Bind the device ID
  • 6.7 Web page real-time monitor
  • 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.Docker-Just for pi5
  • 7.1 Docker overview and docker installation
  • 7.2 Common commands for docker image containers
  • 7.3 Docker images deeply understand and publish images
  • 7.4 Docker hardware interaction and data processing
  • 7.5 Enter the bot's docker container
  • 7.6 Robot development environment construction in Docker
  • 7.7 How customers can update docker images in the future
8.ROS basic course
  • 8.1 ROS introduction
  • 8.2 ROS installation
  • 8.3 ROS common command tools
  • 8.4 ROS workspace
  • 8.5 ROS function package
  • 8.6 ROS node
  • 8.7 ROS topic publisher
  • 8.8 ROS topic subscribers
  • 8.9 ROS service client
  • 8.10 ROS service server
  • 8.11 ROS action client
  • 8.12 ROS action server
  • 8.13 ROS custom message reception
  • 8.14 ROS-launch file
  • 8.15 ROS-TF transformation
  • 8.16 ROS parameter service
  • 8.17 ROS-rviz use
  • 8.18 ROS-rqt tool usage
  • 8.19 Topic message recording and playback
  • 8.20 urdf model introduction
  • 8.21 gazebo introduction
  • 8.22 ROS distributed communication
9.OpenCV courses
  • 9.1 Getting started with Open Source CV
  • 9.2 Geometric transformation
  • 9.3 Image processing and draw
  • 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
  • 9.11 MediaPipe development
10.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.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
  • 11.7 RTAB-Map 3D mapping
  • 11.8 ORB_SLAM2 basics
  • 11.9 ORB_SLAM2_Octomap
12.Lidar course
  • 12.1 Lidar basic-SLAM
  • 12.1 Lidar basic-EAI
  • 12.2 Lidar avoiding
  • 12.3 Lidar guard
  • 12.4 Lidar follow
  • 12.5 Patrol game
  • 12.6 gmapping mapping algoritm
  • 12.7 hector mapping algorithm
  • 12.8 karto mapping algorithm
  • 12.9 cartographer mapping
  • 12.10 rrt_exploration mapping
  • 12.11 AMCL
  • 12.12 Navigation and avoiding
  • 12.13 APP mapping and navigation
13.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.Deep learning courses
  • 14.1 KNN recognizes handwritten
  • 14.2 Basic use of TensorFlow
  • 14.3 Basic use of PyTorch(jetson)
  • 14.4 yolov5 model training(jetson)
  • 14.5 yolov5+tensorrt acceleration
  • 14.6 yolov4-tiny
15.Voice control courses
  • 0. How to use old voice module in new image
  • 15.1 Introduction of voice control-new
  • 15.2 Voice control module port-new
  • 15.3.Introduction of voice module-old
  • 15.4.Voice control module port binding-old
  • 15.5 Voice control car movement
  • 15.6 Voice control Autopilot
  • 15.7 Voice control color recogzition
  • 15.8 Voice control color tracking
  • 15.9 Voice control multi-point nagavation
16.Robotic arm control course
  • 16.1 MoveIt configuration
  • 16.2 MoveIt control the real machine
  • 16.3 MoveIt moves randomly
  • 16.4 MoveIt kinematics design
  • 16.5 MoveIt cartesian path
  • 16.6 MoveIt avoiding
  • 16.7 MoveIt scene design
  • 16.8 MoveIt trajectory planning
  • 16.9 Mediapipe palm control car
  • 16.10 Mediapipe gesture control robotic arm
  • 16.11 Mediapipe gesture control car
  • 16.12 Mediapipe arm attitude control robotic arm
  • 16.13 Mediapipe recognizes and tracks palm control robotic arm
  • 16.14 Recognizes color block and handling
  • 16.15 Autopilot to clear obstacles
17.Voice control robotic arm course
  • 17.1 Voice control robotic arm movement
  • 17.2 Voice control robotic arm learning
  • 17.3 Voice control color block transport
  • 17.4 Voice control robotic arm grip objects
  • 17.5 Voice control robotic arm garbage sorting
18.Model training Autopilot
  • 18.0 ReadMe
  • 18.1 yolov5 to train traffic signs
  • 18.2 TensorRt acceleration identification mark
  • 18.3 Road sign indication function description
  • 18.4 Collect data
  • 18.5 Training model
  • 18.6 Model transformation and application
  • 18.7 AI Autopilot
19.For Orin-Remote control course
1. APP control
  • 1. APP control
  • 2. Model aircraft control
  • 3. Handle control
2. Model aircraft control
3. Handle control
20.Orin-Hardware course
  • 1. About expansion board_V1.0
  • 1. About expansion board_V2.0
  • 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
21.Orin-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
22.Orin-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 Jetson Xavier NX write system
  • 9.3 Jetson TX2 NX-Orin series write system
  • 9.4 Raspberry Pi write system
  • 10.Jetpack old system upgraded to SUPER system
23.Orin-Dockernew
SUPER image uses ros environment in docker
  • 1、Docker overview and docker installationnew
  • 2、Common commands for docker image containersnew
  • 3、Docker images deeply understand and publish imagesnew
  • 4、Docker hardware interaction and data processingnew
  • 5、Enter the bot's docker containernew
  • 6、Robot development environment construction in Dockernew
23.Orin-ROS basic course
  • 1.ROS introduction
  • 2.Project file structure
  • 3.Common commands and tools
  • 4.Publisher
  • 5.Subscribers
  • 6.Customize topic messages and use
  • 7.Client
  • 8.Server
  • 9.Custom service messages and usage
  • 10.TF release and monitoring
24.Orin-OpenCV courses
  • 1. Getting started with Open Source CV
  • 2. Open Source CV geometric transformation
  • 3. Open Source CV image processing and drawing text line segments
  • 4. Open Source CV image beautification
  • 5. Opencv application
  • 6. AR vision
  • 7. AR QR code
  • 8. ROS+Opencv foundation
  • 9. ROS+Opencv application
  • 10. Data transformation and point cloud
  • 11. MediaPipe development
25.Orin-Robot control course
  • 1.PID algorithm theory
  • 2.Robot PID debugging
  • 3.Robot information release
  • 4.Robot keyboard control
  • 5.Robot handle control
  • 6.Robot state estimation
  • 7.Robot calibration
  • 8.Robot URDF model
26.Orin-Depth camera course
  • 01.How to use the Astra camera
  • 02.Astra camera calibration
  • 03.Astra Color Tracking
  • 04.Astra Object Tracking
  • 05.Visual tracking autopilot
  • 06.Pure visual 2D mapping and navigation
  • 07.RTAB-Map 3D mapping navigation
  • 08.ORB_SLAM2 basics
  • 09.ORB_SLAM2_Octomap
27.Orin-Lidar course
  • 1.Lidar basic-4ROS-EAI
  • 1.Lidar basic-SLAM
  • 2.Lidar avoiding
  • 3.Lidar guard
  • 4.Lidar follow
  • 5.Patrol game
  • 6.gmapping mapping algorithm
  • 7.hector mapping algorithm
  • 8.karto mapping algorithm
  • 9.cartographer mapping algorithm
  • 10.rrt_exploration mapping algorithm
  • 11.AMCL
  • 12.Navigation and avoiding
  • 13.APP mapping and navigation
28.Orin-Multi-robot control course
  • 1.Multi-machine handle control
  • 2.Multi-machine navigation
  • 3.Multi-machine formation
  • 4.Multi-machine surround
29.Orin-Deep learning courses
  • 1.KNN recognizes handwritten digits
  • 2.Basic use of TensorFlow
  • 3.Basic use of PyTorch(jetson)
  • 4.YOLOv11Model conversion(SUPER)new
  • 5.YOLOv11Dataset annotation(SUPER)new
  • 6.YOLOv11Model conversion + tensorrt acceleration(SUPER)new
  • 7.YOLOv11Object recognition(SUPER)new
30.Orin-Voice control courses
  • 0. How to use old voice module in new image
  • 1.1 Introduction of voice module-new
  • 1.2 Introduction of voice module-old
  • 2.1 Voice control module port binding-new
  • 2.2 Voice control module 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
31.Orin-Robotic arm control course
  • 1.MoveIt configuration(VM)
  • 2.MoveIt control the real machine(VM)
  • 3.MoveIt moves randomly(VM)
  • 4.MoveIt kinematics design(VM)
  • 5.MoveIt cartesian path(VM)
  • 6.MoveIt avoiding(VM)
  • 7.MoveIt scene design(VM)
  • 8.MoveIt trajectory planning(VM)
  • 9.Mediapipe palm control car
  • 10.Mediapipe gesture control robotic arm
  • 11.Mediapipe gesture control car
  • 12.Mediapipe arm attitude control robotic arm
  • 13.Mediapipe recognizes and tracks palm control robotic arm
  • 14.Recognizes color block and handling
  • 15.Autopilot to clear obstacles
32.Orin-Voice control robotic arm course
  • 1.Voice control robotic arm movement
  • 2.Voice control robotic arm learning
  • 3.Voice control color block transport
  • 4.Voice control robotic arm grip objects
  • 5.Voice control robotic arm garbage sorting
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
  • Using your own Jetson board, car cannot start normally
Download
  • RemoteCtrl_APP(iOS/Android)
  • Mapping_APP(iOS_Android)
  • SystemFile_OrinNANOSUPER
  • SystemFile_OrinNXSUPER
  • SystemFile_RPi_NANO
  • Instruction Manual
  • Code
  • Autopilot Annex
  • VM software
  • Jetson_Boot_USB.tar.gz
  • Other_Annex_File
Download ZIP
FAQ
  • 1、How to connect OLED?
  • 2、Precautions for DIY Robotic Arm

Welcome to ROSMASTER X3 Plus repository

5.Robot handle control

5 Robot handle control

5 Robot handle control 5.1 Operating environment 5.2 install the driver 5.3 Use steps 5.3.1 Device connection 5.3.2 View device 5.3.3 Test handle 5.3.4 Running the handle node 5.4 The handle controls the little turtle 5.4.1 Start 5.5, handle control ROSMASTER 5.5.1 Start handle control 5.6、Precautions for using the handle

According to different models, you only need to set the purchased model in [.bashrc], X1(ordinary four-wheel drive) X3(Mike wheel) X3plus(Mike wheel mechanical arm) R2(Ackerman differential) and so on. Section takes X3 as an example

Open the [.bashrc] file

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#You need to enter docker first, perform this step more
#If running the script to enter docker fails, please refer to Jetson Orin-Docker/05, Enter the robot's docker container
~/run_docker.sh
#Multiple ros commands require multiple terminals to enter the same docker container for execution, please refer to Jetson Orin-Docker/05, Section 5.8 tutorial
sudo vim .bashrc 

Find the [ROBOT_TYPE] parameter and modify the corresponding model

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

 

5.1 Operating environment

OS: Ubuntu 18.04 LTS

ROS version: melodic

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

Handle control function code path: ~/yahboomcar _ws/src/yahboomcar_ctrl/scripts

5.2 install the driver

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

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

5.3 Use 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 the jetson as an example, connecting the mouse, keyboard, and monitor;

5.3.2 View device

Open the terminal, enter the following command, it shows [js0], this is the wireless controller. In special cases, it can also be viewed through the two states of connecting and not connecting to the USB terminal of the wireless handle. The device list changes, if there is a change, the device is changed; otherwise, the connection is unsuccessful or cannot be recognized.

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ls /dev/input 

image-20220302120317676

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

5.3.3 Test handle

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

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sudo jstest /dev/input/js0  

image-20220302121526295

If jstest is not installed, run the following command:

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sudo apt-get install joystick 

5.3.4 Running the handle node

Open three terminals, and enter the following commands in turn to view the detailed information, which is the same as [Test Handle]. Different devices(Raspberry Pi, jetson nano, PC) and different systems will have different handle states.

​x
roscore   

image-20240408144126098

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rosrun joy joy_node   
rostopic echo joy published information 

image-20220302120815104

5.4 The handle controls the little turtle

5.4.1 Start

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roslaunch yahboomcar_ctrl twist_joy.launch 

image-20220302122239082

  1. view the node

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rostopic list 

image-20220328175003554

  1. view the speed topic information

image-20220328175136329

  1. The corresponding relationship between the handle and the operation of the little turtle

handlelittle turtle
left stickgo ahead
Left joystick downback
Right stick leftTurn left
right joystickTurn right
  1. view the node graph

[/joy_node]: Node of handle information

[/twist_joy]: The node 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, and after processing, publishes the topic [/turtle1/cmd_vel] for the node [/turtlesim_node] to subscribe, and drives the little turtle to move.

image-20220302122408394

5.5, handle control ROSMASTER

The handle to control ROSMASTER is similar to the handle to control the turtle; let the handle control node establish a connection with the ROSMASTER underlying driver node, change the current state of the handle, send different information to ROSMASTER, and drive ROSMASTER to respond differently. Corresponding to the ROSMASTER of different models, what we need to control is also different.

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

5.5.1 Start handle control

  1. handle control yahboom_joy.launch file reference path

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~/yahboomcar_ws/src/yahboomcar_ctrl/launch/ 
  1. start

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roslaunch yahboomcar_bringup bringup.launch             # start the 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 to start the remote control. If the remote control is turned on for a period of time, it will enter the sleep mode, and you need to press the "START" button to end the sleep mode.

  1. remote control effect description

handleEffect
Left stick up/downThe car goes straight forward/backward
Left joystick left/rightThe car goes straight left/right
Right stick left/rightCar turns left/right
Right "1" keyControl light strip effects
Right "2" keyEnd/open other functions
"START" buttonControl buzzer/end sleep
Left stick pressedAdjust the speed of X/Y axis
Right stick pressedAdjust the angular velocity

  1. view the node graph

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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.

  1. program analysis

Bottom control program:

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Mcnamu_driver.py 

The code path is:

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~/yahboomcar_ws/src/yahboomcar_bringup/scripts 

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

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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)  # strip control 
self.sub_Buzzer = rospy.Subscriber("Buzzer", Bool, self.Buzzercallback, queue_size=100)         # Buzzer control 

def cmd_vel_callback(self, msg)    # callback function 
def RGBLightcallback(self, msg)    # with callback function 
def Buzzercallback(self, msg)      # callback function 

Handle control program:

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yahboom_joy.py 

The code path is:

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~/yahboomcar_ws/src/yahboomcar_ctrl/scripts 

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

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self.pub_cmdVel = rospy.Publisher('cmd_vel', Twist, queue_size=10)       #speed control 
self.pub_RGBLight = rospy.Publisher("RGBLight", Int32, queue_size=10)    #strip control 
self.pub_Buzzer = rospy.Publisher("Buzzer", Bool, queue_size=1)          #buzzer control 

self.pub_cmdVel.publish(twist)                   # publish speed data 
self.pub_RGBLight.publish(self.RGBLight_index)   # publish light strip data 
self.pub_Buzzer.publish(self.Buzzer_active)      # publish buzzer data 
  1. code analysis

  • /joy topic data analysis

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

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rosrun joy joy_node 
rostopic echo joy 

In the print information, there are two arrays: axes and buttons, and 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, one by one corresponding to the transformation of the array, and you can know what behavior will cause which variable of the array will change its value.

  • Knowing the change of the /joy topic data corresponding to the button behavior, then in yahboom_joy.py, we need to make judgments on these values. There are also two categories in yahboom_joy.py. First, the name of the system will be judged(this is first to judge whether the handle receiver is plugged into the jetson or the Raspberry Pi/PC(referring to the virtual machine here)),

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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 Buzzer data as an example, analysis, we use the "START" button to control the buzzer, and it corresponds to buttons[11], when it is pressed, 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 joysticks, only the data of X3(Mecanum wheel) and X3 Plus(Mecanum wheel + mechanical arm) are valid, because of the characteristics of their wheels, they can move laterally, so Y There is speed on the shaft.

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

5.6、Precautions for 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 it to the main board or the middle USB-HUB expansion board (X3plus). If it is directly connected to the main board or the middle USB-HUB expansion board (X3plus), due to the upper and lower aluminum alloy grille, it will seriously interfere with the signal reception of the handle.

  • After plugging and unplugging the handle receiving head, the handle program needs to be restarted, otherwise the car will not be able to be controlled.

  • 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. If the buzzer sounds, it means the switching 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. In PC mode, the POWER MODE indicator light is red by default. You can connect the handle receiver to the usb port of the computer to connect to the wireless handle. Enter the URL in the browser: https://gamepad-tester.com/. Pressing the button URL will display the change of the button value, as shown in the following figure:

 

 

Raspberry Pi series support mode: X-BOX mode. In X-BOX mode, the default POWER MODE indicator light is green. You can connect the handle receiver to the usb port of the computer to connect to the wireless handle. Enter the URL in the browser: https://gamepad-tester.com/. Pressing the button URL will display the change of the button value, as shown in the following figure:

 

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

  • After re-plugging the handle receiver or restarting the motherboard, the handle will reset to the factory mode. If it cannot be controlled, you need to switch the mode again every time you plug or restart.

  • In the case of unsuccessful matching, the POWER MODE indicator light will flash red and green all the time, and will not light up after a few seconds of sleep.

Robot keyboard control
Robot state estimation

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