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Self-balancing Robot Car📖
00.Get started quickly
  • 01.Balance car manual
  • 02.Balancing car assembly
  • 03.Get started quickly
  • 04.Balance car interface description
  • 05.Common Problem Analysis
  • 06.Balance Car V2 Library Function Development Manual
01.Environment development
  • 01.MDK-ARM installation
  • 02.STM32CubeIDE installation
  • 03.Common driver installation
  • 04.Download the program
  • 05.MDK-ARM project usage
  • 06.Program simulation
  • 07. VSCode Installation
02.STM32 getting started course
  • 01.Project creation
  • 02.LED Control(GPIO)
  • 03.Buzzer control(GPIO)
  • 04.Button control(EXTI)
  • 05.Serial communication(USART)
  • 06.Voltage detection(ADC)
  • 07.Basic timer(TIM)
  • 08.Universal timer(TIM)
  • 09.Advanced Timer(TIM)
  • 10.I2C Communication(I2C)-OLED
  • 11.SPI communication(SPI)-2.4G handle
  • 12.Independent Watchdog (IWDG)
  • 13.Window Watchdog (WWDG)
  • 14.DMA-USART
  • 15.DMA-I2C
03.STM32 expansion course
  • 01.Battery voltage detection (ADC)
  • 02.Ultrasonic module-measuring distance (TIM)
  • 03.Motor drive+encoder (TIM)
  • 04.OLED Data-Display(I2C)
  • 05.MPU6050-Data Read (I2C)
  • 06.Bluetooth module-Data reading (USART)
  • 07.2.4G handle-Data reading (SPI)
  • 08.Tracking module-Read status (GPIO)
  • 09.CCD module-Reading data (ADC)
  • 10.Electromagnetic module-Reading data (ADC)
  • 11.K210 module-Serial communication (USART)
  • 12.Tmini-Plus lidar-Reading data (USART)
04.Robot car PID control course
  • 01.PID basic concept
  • 02.PID example analysis
  • 03.P, PI, PD controller theory
  • 04.Position PID
  • 05.Incremental PID
  • 06.Cascade PID
  • 07.Balance principle of car
  • 08.Car upright control (PD)
  • 09.Car speed ​​control (PI)
  • 10.Car steering control (PD)
  • 11.Got angle and angular velocity (DMP algorithm)
  • 12.Got angle and angular velocity (Kalman filter algorithm)
  • 13.Got angle and angular velocity(Complementary filter algorithm)
05.Robot car basic course
  • 01.Car parameter adjustment
  • 02.Ultrasonic obstacle avoidance
  • 03.Ultrasonic follow
  • 04.Bluetooth remote control
  • 05.Load balance
06.Robot car advanced course
  • 01.4-channel tracking
  • 02.4-channel tracking avoid
  • 03.2.4G handle control
  • 04.CCD tracking
  • 05.CCD tracking avoid
  • 06.Electromagnetic tracking
  • 07.K210-QR code recognition
  • 08.K210-Color line tracking
  • 09.K210-Color follow
  • 10.K210-Self learning
  • 11.K210-Number recognition
  • 12.Lidar avoid
  • 13.Lidar guard
  • 14.Lidar follow
  • 15.Lidar patrol
  • 16.Lidar wall tracking-straight line
  • 17.Lidar wall tracking-multiple walls
  • 18. DIY Automatic driving car
07.Robot car LQR control
  • Robot car LQR control
08.Circuit design
  • 01.Overall circuit design
  • 02.STM32 minimum system
  • 03.Serial port circuit design
  • 04.Power circuit design
  • 05.MPU6050 Circuit Design
  • 06.Motor drive circuit design
09.Mathematical model
  • Mathematical model
10.Expand course
  • Autonomous Driving
Download
  • APP(Android)
  • Codes
  • Hardware-Info
  • SCH
  • Software Tools
  • STM32_Chip_DataSheet
  • 3D_Model_File
  • Video_PPT
Download ZIP

Welcome to Self-balancing Robot Car repository

08.K210-Color line tracking

K210-Color line tracking

K210-Color line trackingHardware connectionControl principleMain codeProgram flow chartExperimental phenomenon

The tutorial mainly demonstrates the function of color line patrol (colored route) by combining the balance car with the K210 vision module.

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The tutorial only introduces the standard library project code

Hardware connection

PeripheralsDevelopment board
K210 vision module: VCC5V
K210 vision module: TXDPA2
K210 vision module: RXDPA3
K210 vision module: GNDGND

Control principle

The K210 vision recognition module identifies the colored route on the tracking map, and sends the center coordinates of the identified route to the development board. The development board controls the balance car to patrol the line according to the center coordinate information.

  • K210 Vision Module

image-20240819151049932

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The K210 Vision Module itself is a development board. For detailed usage, please refer to the module supporting tutorial

Download the program

Connect the SD card of the K210 Vision Module to the computer through a card reader, rename the program file to main.py and copy it to the SD card, then reinstall the SD card into the SD card slot of the K210 Vision Module.

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The K210 vision module and development board case codes are in the same folder: the folder name will distinguish the development board to which the code belongs

Color learning

After the color recognition program is started, the K210 vision recognition module will display a box on the screen. We need to align the box with the colored route to be patrolled for color learning (the box needs to be completely inside the color route); after the color learning is completed, the camera will recognize the colored route, and you can observe the recognition effect yourself.

Communication protocol

The K210 vision module program will automatically calculate the center coordinates of the recognized color route and send it to the development board for processing.

Data headerData (X represents X-axis data, Y represents Y-axis data: data occupies three characters)Data tailExample
$XXXYYY#$160120#: represents the center position (160, 120)
$XXXYYY#$080060#: represents the center position (80, 60)

Main code

The tutorial mainly explains the code for implementing the K210 visual line patrol function. For detailed code, refer to the corresponding project file.

Turn_K210_PD

K210 visual line patrol PID implementation code. If the line patrol effect of the balance car is not good, modify the PID parameters of the app_line.c file. It is not recommended to modify the PID parameters of the pid_control.c file (the PID parameters of the pid_control.c file are subject to the parameters finally confirmed in the balance car parameter adjustment tutorial).

​x
int Turn_K210_PD(float gyro)
{   
    int k210Turn = 0; 
    float K210x_median_err = 0;   
    
    K210x_median_err=K210_data.k210_X-K210_Minddle;
    
    k210Turn=K210x_median_err*K210_Trun_KP+gyro*K210_Trun_KD;
    
    return k210Turn;

}

Set_track_speed

Set the patrol speed of the balancing car.

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void Set_track_speed(void)
{
    Move_X = Track_Speed;       
}

Program flow chart

Briefly introduce the process of function implementation:

image-20240904122121490

Experimental phenomenon

Software code

The BalancedCar_color_line.hex file generated by the project compilation is located in the OBJ folder of the BalancedCar_color_line project. Find the BalancedCar_color_line.hex file corresponding to the project and use the FlyMcu software to download the program to the development board.

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The corresponding functions can only be realized after both the K210 visual module and the development board download the program
Product supporting information source code path: Attachment → Source code summary → 5.Balanced_Car_Extended → 08.BalancedCar_color_line

Experimental phenomenon

After the program is started, press the KEY1 button according to the OLED prompt to start the color line patrol function of the balance car: OLED displays the program function name in real time (Start follow line!); K210 visual recognition module recognizes the color route and patrols the line; if the color route is not recognized, the balance car will keep moving forward.

The program has voltage detection. If the voltage is less than 9.6V, a low voltage alarm is triggered and the buzzer will sound.
Common situations that trigger voltage alarms:
1. The power switch of the development board is not turned on, and only the Type-C data cable is connected for power supply
2. The battery pack voltage is lower than 9.6V and needs to be charged in time
K210-QR code recognition
K210-Color follow

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