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Raspbot📖
1.First Trial and Installation
  • 1.1 Installation video
  • 1.2 First Trial
2.Remote control course
  • 2.1 APP control car
  • 2.2 IR control car
3.Preparation
  • 3.1 Preparation
  • 3.2 Run a code on JupyterLab
  • 3.5 TF card expand capacity
4.OpenCV Basic course
A.Getting started with OpenCV
  • 1.Introduction of OpenCV
  • 2.OpenCV image read and display
  • 3.OpenCV image write
  • 4.OpenCV image quality
  • 5.OpenCV pixel operation
B.OpenCV Geometric transformat
  • 1.Picture Zoom
  • 2.Picture Cut
  • 3.Picture Shift
  • 4.Picture Mirroring
  • 5.Affine Map
  • 6.Picture Rotation
  • 7.Perspective Transformation
C.OpenCV picture processing
  • 1.Grayscale processing
  • 2.Image Binarization
  • 3.Edge detection
  • 4.Drawing line segment
  • 5.Drawing rectangle circle
  • 6.Drawing text picture
D.OpenCV image beautification
  • 1.Histogram of color pictures
  • 2.Histogram equalization
  • 3.Image restoration
  • 4.Brightness enhancement
  • 5.Skin whitening
  • 6.Gaussian mean filtering
  • 7.Median filtering
E.OpenCV machine learning
  • 1.KNN recognition of handwritten numbers
  • 2.CNN recognition of handwritten numbers
  • 3.SVM recognition of handwritten numbers
5.Hardware Control course
  • 5.1 Drive buzzer
  • 5.2 Drive motor
  • 5.3 Drive servo
  • 5.4 Ultrasonic ranging
  • 5.5 Ultrasonic avoid
  • 5.6 Ultrasonic+IR avoid
  • 5.7 Tracking
  • 5.8 Restricting
  • 5.9 Drive LED
  • 5.10 IR control test
  • 5.11 IR control car
6.AI vision course
  • 6.1 Driver camera
  • 6.2 Color recognition
  • 6.3 HSV value test
  • 6.4 Camera color tracking
  • 6.5 Car color tracking
  • 6.6 Tensorflow object recognition
  • 6.7 QR code recognition
  • 6.8 QR code control
  • 6.9 Face detection
  • 6.10 Face tracking
  • 6.11 Autopilot
7.Battery and charging
  • Battery and charging
Download
  • APP(iOS/Android)
  • Code
  • Download image
  • Instruction manual
  • More Annex
Download ZIP
FAQ
  • 1、Raspbot-Raspberry Pi 4b version desktop connection WiFi method
  • 2、Can't connect your home WiFi
  • 3、How to check IIC function on Raspbot
  • 4、Gesture recognition cannot work normally.
  • 5、How to write image file into SD card

Welcome to Raspbot repository

5.7 Tracking


Tip:

In order to avoid sunlight affecting the infrared sensor, the experiment needs to be carried out indoors.

1. Learning target

In this course, we will learn how to use tracking module to make car completes tracking experiment.

2. Principle of experimental

The basic principle of the tracking sensor is to use the reflective nature of the object. 

Our experiment is to tracking the black line. When the infrared light is emitted to the black line, it will be absorbed by the black line. When the infrared light is emitted to the other color line, it will reflected to the infrared receiver tube. 

When detecting tracks of different shapes, the state of the 4-channel tracking sensor is as shown below.

image.png 

For the Raspbot car, we use 4 TT DC gear motors. They are driven by the AT8236 chip. The driver chip is not directly connected to the Raspberry Pi pins.

Raspberry Pi communicates with STM8 MUC through IIC, and then STM8 MCU drives AT8236 chip to drive the motor.

3. Coding method

In this course, we use BOARD coding method.

According to the hardware interface manual, we see that the tracking module pins are connected to the 11,7,13,15 pin of the Raspberry Pi board.

image.png 

STM8 is connected to SDA.1, SCL.1 on the Raspberry Pi board.

We have provided a library text dedicated to driving motors and servos --YB_Pcb_Car.py.

It is located in the same directory as the motor driver.

The pin comparison table of Raspberry Pi as shown below.

image.png 

 

image.png 

4. About code

Path: /home/pi/Yahboom_project/Raspbot/2.Hardware Control course/7.Ultrasonic avoid/Tracking test.ipynb

1) Import time and GPIO library

image.png 

2)Set the GPIO coding mode, define tracking module pin and define the car class is used to drive motors or servos.

image.png 

3) Read the value of the tracking module and print it out.

When we click the stop button, we exit the loop, stop the car, and clear the car class and GPIO.

image.png 

 5. Experimental phenomenon

After the program runs. Place the car on a dedicated black and white tracking map, adjust the knob of the tracking module to make indicator light is on when the sensor detects black, and indicator light is off when it detects white.

We can see that when black is detected, 0 is printed, and when white is detected, 1 is printed.

Path: /home/pi/Yahboom_project/Raspbot/2.Hardware Control course/7.Ultrasonic avoid/Tracking.ipynb

1) Import time, GPIO and YB_Pcb_Car library

image.png 

2)Set the GPIO coding mode, define tracking module pin and define the car class is used to drive motors or servos.

image.png 

3) Define the function of the tracking module

image.png  

4) Call the tracking function in loop to complete the obstacle avoidance experiment.

When we click the stop button, we exit the loop, stop the car, and clear the car class and GPIO.

image.png 

6. Experimental phenomenon

Before running the tracking experiment.

We need to adjust the sensitivity of the tracking module. The indicator light is off when white is detected, and the indicator light is on when black is detected.

After the program runs, place the car on the dedicated black and white tracking map, and the car will move along the black line.

 


Ultrasonic+IR avoid
Restricting

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