yahboom
HomeLearn
Solution
Blog
Online Store
About Us
EN/中文
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

5.3 Install the Rosmaster driver library

3. Install the Rosmaster driver library

3. Install the Rosmaster driver library 3.1. Declaration before installing the driver library 3.2. Download the Python driver library file 3.3. Transfer files to Jetson Nano 3.4. start the installation 3.5. import library file 3.6. Basic usage of driver library 3.7. Introduction to API

3.1. Declaration before installing the driver library

The latest driver library has been installed in the factory mirror system of the car, so there is no need to install it repeatedly. If you are not using the factory image, or if the driver library has updated content, you only need to install the driver library.

The driver library storage path that comes with the factory system: ~/yahboomcar_ros2_ws/software/py_install_V3.3.1

For the method of installing the driver library, please refer to the following steps. Here, the installation of version V3.3.1 is used as an example.

3.2. Download the Python driver library file

The latest version of the Rosmaster Python driver library is available in this course material, named py_install.zip.

The compressed package contains the following files:

image-20220316160547427

3.3. Transfer files to Jetson Nano

If you use the browser that comes with Jetson Nano to download the file, please download the file to a user-operable path, such as the desktop.

If you use the driver library zip file in the data, or download the driver library file with a computer browser, you can drag the driver library zip file into the Jetson Nano desktop through WinSCP software.

After the installation is successful, the driver library file can be deleted.

image-20210904174213656

 

3.4. start the installation

Open the terminal of Jetson Nano and enter the following command to unzip it.

Go to the desktop and check if the file exists, the red box is the target file

xxxxxxxxxx
cd  ~/Desktop &&  ls 

unzip files

xxxxxxxxxx
unzip py_install.zip 

image-20220325101116150

Note: The entire documentation routine takes the py_install.zip compressed package placed on the desktop of the Jetson Nano system as an example. If you store the compressed package in a different path, please enter the corresponding directory according to the actual path to operate.

Go to the driver library folder

xxxxxxxxxx
cd  py_install 

Run the installation command and see the installation version number indicated at the end, indicating that the installation is successful. This command will overwrite the Rosmaster_Lib driver library that has been installed before.

xxxxxxxxxx
sudo  python3 setup.py install 

image-20220325101329200

3.5. import library file

The name of the Rosmaster driver library is Rosmaster_Lib, and Rosmaster_Lib is used in the program to import the library.

xxxxxxxxxx
from  Rosmaster_Lib  import  Rosmaster 

3.6. Basic usage of driver library

Check out the video tutorial for this lesson for details.

Source code path: Rosmaster/Samples/3.test_rosmaster.ipynb

3.7. Introduction to API

The following is an introduction to the API of the driver library, and the function usage and parameter content will be introduced in the control course later.

|  __del __ (self) 
| 
 |  __init__(self, car_type=1, com='/dev/myserial', delay=0.002, debug=False) 
 |      Initialize self.  See help(type(self)) for accurate signature. 
| 
 |  clear_auto_report_data(self) 
| # Clear the cached data automatically sent by the microcontroller 
 |      # Clear the cache data automatically sent by the MCU 
| 
 |  create_receive_threading(self) 
| # Start a thread for receiving and processing data 
 |      # Start the thread that receives and processes data 
| 
 |  get_accelerometer_data(self) 
| # Get the three-axis data of the accelerometer, return a_x, a_y, a_z 
 |      # Get accelerometer triaxial data, return a_x, a_y, a_z 
| 
 |  get_battery_voltage(self) 
| # Get the battery voltage value 
 |      # Get the battery voltage 
| 
 |  get_gyroscope_data(self) 
| # Get the three-axis data of the gyroscope, return g_x, g_y, g_z 
 |      # Get the gyro triaxial data, return g_x, g_y, g_z 
| 
 |  get_magnetometer_data(self) 
| # Get the magnetometer three-axis data, return m_x, m_y, m_z 
| 
 |  get_motion_data(self) 
| # Get the speed of the car, val_vx, val_vy, val_vz 
 |      # Get the car speed, val_vx, val_vy, val_vz 
| 
 |  get_motion_pid(self) 
| # Get the motion PID parameters of the car, return [kp, ki, kd] 
 |      # Get the motion PID parameters of the dolly and return [kp, ki, kd] 
| 
 |  get_motor_encoder(self) 
| # Get four-way motor encoder data 
 |      # Obtain data of four-channel motor encoder 
| 
 |  get_uart_servo_angle(self, s_id) 
| # Read the angle of the bus servo, s_id indicates the ID number of the servo to be read, s_id=[1-6] 
 |      # Read the Angle of the bus steering gear, s_id indicates the ID number of the steering gear to be  
read, s_id=[1-6] 
| 
 |  get_uart_servo_angle_array(self) 
| # Read the angles of six servos at one time [xx, xx, xx, xx, xx, xx], if a servo is wrong, the bit is -1 
 |      # Read the angles of three steering gear [xx, xx, xx, xx, xx, xx] at one time. If one steering gear 
 is wrong, that one is -1 
| 
 |  get_uart_servo_value(self, servo_id) 
| # Read the bus servo position parameter, servo_id=[1-250], return: read ID, current position parameter 
 |      # Read bus servo position parameters, servo_id=[1-250], return: read ID, current position parameter 
s 
| 
 |  get_version(self) 
| # Get the version number of the underlying MCU, such as 1.1 
 |      # Get the underlying microcontroller version number, such as 1.1 
| 
 |  reset_flash_value(self) 
| # Reset the data saved in the car's flash and restore the factory default values. 
 |      # Reset the car flash saved data, restore the factory default value 
| 
 |  set_auto_report_state(self, enable, forever=False) 
| # The MCU automatically returns the data status bit, the default is ON, if it is set to OFF, it will affect part of the data read function. 
| # enable=True, the underlying expansion board will send a packet of data every 10 milliseconds, a total of four packets of different data, so each packet of data is refreshed every 40 milliseconds.  e 
nable=False, do not send. 
| # forever=True for permanent storage, =False for temporary use. 
 |      # The MCU automatically returns the data status bit, which is enabled by default. If the switch is  
closed, the data reading function will be affected.   
 |      # enable=True, The underlying expansion board sends four different packets of data every 10 millise 
conds, so each packet is refreshed every 40 milliseconds.  
 |      # If enable=False, the report is not sent.   
 |      # forever=True for permanent, =False for temporary 
| 
 |  set_beep(self, on_time) 
| # Buzzer switch, on_time=0: off, on_time=1: keep ringing, 
| # on_time>=10: Automatically turn off after xx milliseconds (on_time is a multiple of 10). 
 |      # Buzzer switch. On_time =0: the buzzer is off. On_time =1: the buzzer keeps ringing 
 |      # On_time >=10: automatically closes after xx milliseconds (on_time is a multiple of 10) 
| 
 |  set_car_motion(self, v_x, v_y, v_z) 
| # Car motion control, v_x=[-1.0, 1.0], v_y=[-1.0, 1.0], v_z=[-5.0, 5.0] 
 |      # Car movement control, v_x = [-1.0, 1.0], v_y = [-1.0, 1.0], v_z = [-5.0, 5.0] 
| 
 |  set_car_run(self, state, speed, adjust=False) 
| # Control the car to move forward, backward, left, right, etc. 
| # state=[0~6],=0 stop,=1 forward,=2 backward,=3 left,=4 right,=5 left,=6 right 
| # speed=[-100, 100],=0 to stop. 
| # adjust=True to enable the gyroscope to assist the movement direction.  =False to disable. 
 |      # Control the car forward, backward, left, right and other movements. 
 |      # State =[0~6],=0 stop,=1 forward,=2 backward,=3 left,=4 right,=5 spin left,=6 spin right 
 |      # Speed =[-100, 100], =0 Stop. 
 |      # Adjust =True Activate the gyroscope auxiliary motion direction.  If =False, the function is disab 
led. 
| 
 |  set_car_type(self, car_type) 
| # Set the car type 
 |      # Set car Type 
| 
 |  set_colorful_effect(self, effect, speed=255, parm=255) 
| # RGB programmable light strip special effects display. 
| # effect=[0, 6], 0: stop light effect, 1: running water light, 2: marquee light, 3: breathing light, 4: gradient light, 5: starlight, 6: battery display 
| # speed=[1, 10], the smaller the value, the faster the speed changes. 
| # parm, optional, as an additional parameter. Usage 1: Enter [0, 6] for the breathing light effect to modify the color of the breathing light. 
 |      # RGB programmable light band special effects display. 
 |      # Effect =[0, 6], 0: stop light effect, 1: running light, 2: running horse light, 3: breathing ligh 
t, 4: gradient light, 5: starlight, 6: power display  
 |      # Speed =[1, 10], the smaller the value, the faster the speed changes 
 |      # Parm, left blank, as an additional argument.  Usage 1: The color of breathing lamp can be modifie 
d by the effect of breathing lamp [0, 6] 
| 
 |  set_colorful_lamps(self, led_id, red, green, blue) 
| # RGB programmable light strip control, which can be controlled individually or as a whole. Before the control, you need to stop the RGB light effects. 
| # led_id=[0, 13], control the corresponding number of RGB lights; led_id=0xFF, control all lights. 
| # red,green,blue=[0, 255], representing the color RGB value. 
 |      # RGB programmable light belt control, can be controlled individually or collectively, before contr 
ol need to stop THE RGB light effect. 
 |      # Led_id =[0, 13], control the CORRESPONDING numbered RGB lights;  Led_id =0xFF, controls all light 
s. 
 |      # Red,green,blue=[0, 255], indicating the RGB value of the color. 
| 
 |  set_motor(self, speed_1, speed_2, speed_3, speed_4) 
| # Controls the motor PWM pulses, thus controlling the speed (not using the encoder to measure the speed).  speed_X=[-100, 100] 
 |      # Control PWM pulse of motor to control speed (speed measurement without encoder). speed_X=[-100, 1 
00] 
| 
 |  set_pid_param(self, kp, ki, kd, forever=False) 
| # PID parameter control will affect the change of the motion speed of the car controlled by the set_car_motion function. By default it can be left unadjusted. 
| # kp ki kd = [0, 10.00], you can enter decimals. 
| # forever=True for permanent storage, =False for temporary use. 
| # Since the permanent storage needs to be written into the chip flash, the operation time is long, so add the delay time to avoid the problem of packet loss caused by the microcontroller. 
| # Temporary action has a quick response and is valid for one time, and the data is no longer maintained after restarting the single chip. 
 |      # PID parameter control will affect the set_CAR_motion function to control the speed change of the  
car.  This parameter is optional by default.   
,  # KP ki kd = [0, 10.00] 
 |      # forever=True for permanent, =False for temporary.   
 |      # Since permanent storage needs to be written into the chip flash, which takes a long time to opera 
te, delay is added to avoid packet loss caused by MCU.   
 |      # Temporary effect fast response, single effective, data will not be maintained after restarting th 
e single chip 
| 
 |  set_pwm_servo(self, servo_id, angle) 
| # Servo control, servo_id: corresponding to the ID number, angle: corresponding to the angle value of the servo 
 |      # servo_id=[1, 4], angle=[0, 180] 
 |      # Servo control, servo_id: corresponding, Angle: corresponding servo Angle value 
| 
 |  set_pwm_servo_all(self, angle_s1, angle_s2, angle_s3, angle_s4) 
| # Control the angle of four PWM channels at the same time, angle_sX=[0, 180] 
 |      # At the same time control four PWM Angle, angle_sX=[0, 180] 
| 
 |  set_uart_servo(self, servo_id, pulse_value, run_time=500) 
| # Control the bus servo.  servo_id:[1-255], indicates the ID number of the servo to be controlled, when id=254, it controls all connected servos. 
| # pulse_value=[96,4000] indicates the position to which the servo should run. 
| # run_time indicates the running time (ms), the shorter the time, the faster the servo rotates. Minimum is 0, maximum is 2000 
 |      # Control bus steering gear.  Servo_id :[1-255], indicating the ID of the steering gear to be contr 
olled. If ID =254, control all connected steering gear.   
 |      # pulse_value=[96,4000] indicates the position to which the steering gear will run.   
 |      # run_time indicates the running time (ms). The shorter the time, the faster the steering gear rota 
tes.  The minimum value is 0 and the maximum value is 2000 
| 
 |  set_uart_servo_angle(self, s_id, s_angle, run_time=500) 
| # Set the bus servo angle interface: id:7-9, angle: 7:[0, 225], 8:[30, 270], 9:[30, 180], set the angle to which the servo should move 
. 
| # Set the vertical and upward clamping state, the three servos are all 180 degrees, the 7/8th turn clockwise (down) to decrease, counterclockwise (up) to increase, and the clamp is released 
To reduce, clamp to increase. 
| # run_time indicates the running time (ms), the shorter the time, the faster the servo rotates. Minimum is 0, maximum is 2000 
 |      # Set bus steering gear Angle interface: ID :7-9, Angle :7 :[0, 225], 8:[30, 270], 9:[30, 180], set 
 steering gear to move to the Angle.   
 |      # Set up the vertical clamping state, the three steering gear are 180 degrees, 7/8 clockwise (down) 
 to decrease, counterclockwise (up) to increase, clip release to decrease, clamping to increase.   
 |      # run_time indicates the running time (ms). The shorter the time, the faster the steering gear rota 
tes.  The minimum value is 0 and the maximum value is 2000 
| 
 |  set_uart_servo_angle_array(self, angle_s=[90, 90, 90, 90, 90, 180], run_time=500) 
| # Control the angles of all servos of the robotic arm at the same time. 
 |      # Meanwhile, the Angle of all steering gear of the manipulator is controlled 
| 
 |  set_uart_servo_id(self, servo_id) 
| # Set the ID number of the bus servo, servo_id=[1-250]. 
| # Please make sure to connect only one bus servo before running this function, otherwise all connected bus servos will be set to the same ID, resulting in control confusion 
. 
 |      # Set the bus servo ID, servo_id=[1-250].   
 |      # Before running this function, please confirm that only one bus actuator is connected. Otherwise,  
all connected bus actuators will be set to the same ID, resulting in confusion of control 
| 
 |  set_uart_servo_offset(self, servo_id) 
| # Set the median deviation of the robotic arm, servo_id=0~6, =0 all restore the factory default value 
 |      # Run the following command to set the mid-bit deviation of the manipulator: servo_id=0 to 6, =0 Re 
store the factory default values 
| 
 |  set_uart_servo_torque(self, enable) 
| # Turn off/on bus servo torque, enable=[0, 1]. 
| # enable=0: Turn off the steering gear torque, you can turn the steering gear by hand, but the command cannot control the rotation; 
| # enable=1: Turn on the torque force, the command can control the rotation, and the servo cannot be turned by hand. 
 |      # Turn off/on the bus steering gear torque force, enable=[0, 1].   
 |      # enable=0: Turn off the torque force of the steering gear, the steering gear can be turned by hand 
, but the command cannot control the rotation;   
 |      # enable=1: Turn on torque force, command can control rotation, can not turn steering gear by hand 
Turn off the self-starting process at startup
Buzzer whistle

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