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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

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

#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

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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

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.

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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.

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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.

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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. 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.

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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

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roslaunch yahboomcar_ctrl twist_joy.launch

image-20220302122239082

1), view nodes

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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

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~/yahboomcar_ws/src/yahboomcar_ctrl/launch/

2), start

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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
Button upServo No. 4 up
Button downServo No. 4 down
Button leftNo. 3 servo down
Button rightServo No. 3 up
Button XServo No. 1 to the left
Button YServo No. 2 up
Button AServo No. 2 down
Button BServo No. 1 to the right
Left "1" keyNo. 6 servo clamp (tight)/No. 5 servo right turn
Left "2" keyNo. 6 servo clamp (loosen)/No. 5 servo left turn
SELECT keySwitch control of No. 6/No. 5 servo

 

  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.

5), program analysis

Underlying control program:

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Mcnamu_X3plus.py

The code path is:

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~/yahboomcar_ws/src/yahboomcar_bringup/scripts

In Mcnamu_X3plus.py, the subscribers and their respective callback functions for the topic information of the buzzer, speed control, and light strip are defined,

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self.sub_cmd_vel = rospy.Subscriber('cmd_vel', Twist, self.cmd_vel_callback, queue_size=100)
self.sub_RGBLight = rospy.Subscriber("RGBLight", Int32, self.RGBLightcallback, queue_size=100)
self.sub_Buzzer = rospy.Subscriber("Buzzer", Bool, self.Buzzercallback, queue_size=100)
self.sub_Arm = rospy.Subscriber("TargetAngle", ArmJoint, self.Armcallback, queue_size=1000)

def cmd_vel_callback(self, msg) #Speed callback function
def RGBLightcallback(self, msg) #Light strip callback function
def Buzzercallback(self, msg) #Buzzer callback function
def Armcallback(self, msg) #Robotic arm control 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, define the publisher of the buzzer, speed control, and light strip topic information, and publish these messages

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self.ArmPubUpdate = rospy.Publisher("ArmAngleUpdate", ArmJoint, queue_size=1000)
self.EdiPublisher = rospy.Publisher('edition', Float32, queue_size=100)
self.volPublisher = rospy.Publisher('voltage', Float32, queue_size=100)
self.staPublisher = rospy.Publisher('joint_states', JointState, queue_size=100)
self.velPublisher = rospy.Publisher("/pub_vel", Twist, queue_size=100)
self.imuPublisher = rospy.Publisher("/pub_imu", Imu, queue_size=100)
self.magPublisher = rospy.Publisher("/pub_mag", MagneticField, queue_size=100)

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,

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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)),

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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 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.

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     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 stays 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.

  • 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.

    jetson series support mode: PC/PCS mode, the POWER MODE indicator light is red by default in PC mode. You can connect the handle receiver to the USB port of the computer to connect 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 figure below:

    image-20230927111320091

    Raspberry Pi series supported modes: X-BOX mode. In X-BOX mode, the default POWER MODE indicator light is green. You can connect the handle receiver to the power

    Connect the USB port of the computer to the wireless controller, and enter the URL in the browser: https://gamepad-tester.com/. Press the button URL will be displayed

    Indicates the change of key value, as shown in the figure below:

    image-20230927111402162

 

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

Robot keyboard control
Robot state estimation

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