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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

12.Lidar avoid

Lidar avoid

Lidar avoidHardware connectionControl principleMain codeProgram flow chartExperimental phenomenon

The tutorial mainly demonstrates the obstacle avoidance function of the balance car combined with the Tmini-Plus radar.

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The tutorial only introduces the standard library project code

Hardware connection

Since we have configured a special connection line, we only need to install it to the corresponding interface.

PeripheralsDevelopment Board
Tmini-Plus radar: VCC5V
Tmini-Plus radar: TXDPC10
Tmini-Plus radar: RXDPC11
Tmini-Plus radar: GNDGND

Control principle

The program analyzes the radar data and determines the movement direction of the balance car based on the distance information at the specified angle.

  • Tmini-Plus radar

image-20240820102356793

Product nameTmini-Plus radar
Scanning frequency6-12Hz
Sampling frequency4000 times/s
Measuring radiusBlack object: 12m
Minimum measuring distance0.05m
Ranging principleTOF ranging
Scanning angle360°
Communication interfaceStandard asynchronous serial port (UART)
1. Baud rate: 230400
2. Data bits: 8
3. Check bit: None
4. Stop bit: 1
ROS supportROS1/ROS2
Windows supportHost computer

Radar angle distribution

The arrow in the center of the radar points to 0°/360°, and the angle increases clockwise.

image-20240820204025164

Communication protocol

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For detailed information, please refer to the "T_Mini_Plus Manual"

Main code

The tutorial mainly explains the code for implementing the radar obstacle avoidance function. For detailed code, please refer to the corresponding project file.

Car_Avoid

The obstacle position of the balance car is determined through the radar's 0°, 90°, and 270° distance data and the movement of the balance car is controlled.

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void Car_Avoid(void)
{
    static u8 avoid_step = 0;// Obstacle Avoidance Steps
    
    // Each time this function is called, the value is dynamically refreshed.
    float get_data_mid = Tminidis[0];   
    float get_data_Lmid = Tminidis[270];// Left
    float get_data_Rmid = Tminidis[90];// Right
    
    switch(avoid_step)
    {
        case 0:
        if(get_data_mid <avoid_dis && get_data_mid >0 )//  Obstacle Avoidance
        { 
            // Car stop
            Move_X = 0,Move_Z = 0;
            delay_time_int(10);
            avoid_step = 1;
        }
        else    
        {
            // Car moving forward
            Move_X = GO_speed,Move_Z = 0;
        }
        break;
        case 1: if(get_time_int()==0) avoid_step ++;break; // Time to go to next step
        case 2: 
        {
            // Trolley backward
            Move_X = -15,Move_Z = 0;
            delay_time_int(100); //1s
            avoid_step = 3;
        }
        case 3: if(get_time_int()==0) avoid_step ++;break; // Time to go to next step
        case 4: 
        {
            if(get_data_Lmid >= get_data_Rmid )
            {
                // left
                Move_X = 0,Move_Z = -450;
                delay_time_int(100);
            }
            else
            {
                // right
                Move_X = 0,Move_Z = 450;
                delay_time_int(100);
            }
            avoid_step = 5;
        }
        case 5: if(get_time_int()==0) avoid_step=0;break; // Time to go to next step
    }
}

Program flow chart

Briefly introduce the process of function implementation:

Experimental phenomenon

Software code

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

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Product supporting data source code path: Attachment → Source code summary → 5.Balanced_Car_Extended → 12.Balance_Radar_Avoid

Experimental phenomenon

After the program is started, press KEY1 according to the OLED prompt to start the radar obstacle avoidance function of the balance car: OLED displays start control!

Radar does not detect obstacles (obstacle distance>200mm): the car moves forward

Radar detects obstacles in front (0mm<obstacle distance<200mm): the car stops and moves backward

Judge the distance between left and right obstacles:

Left obstacle distance ≥ right obstacle distance: the car turns left and then moves forward

Left obstacle distance <right obstacle distance: the car turns right and then moves 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-Number recognition
Lidar guard

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