Tutorial

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Table Of Contents

1. Premise
- 1.1STEAM and Raspberry Pi
- 1.2About The Documentation
2. Raspberry Pi System Installation and Developmen
- 2.1 Install An Operating System for The Raspberry
- 2.2 Enable SSH Server of Raspberry Pi
  - 2.2.1 Method A: Enable SSH with Peripherals
  - 2.2.2 Method A: Enable SSH without Peripherals
- 2.3 Configure WiFi on Raspberry Pi
  - 2.3.1 Method A: WiFi Connection with Peripherals
  - 2.3.2 Method A: WiFi Connection without Periphera
3 Log In to The Raspberry Pi and Install The App
- 3.1 Log into Raspberry Pi (Windows 10)
- 3.2 Log into Raspberry Pi (Linux or Mac OS)
- 3.3 Log into Raspberry Pi (Windows 8 or Previous V
- 3.4 Download Program of The Raspberry Pi Robot
- 3.5 Install Corresponding Dependent Libraries
- 3.6 Run the Raspberry Pi Robot's Program
4 Assembly and Precautions
- 4.1 Structure Assembly
- 4.2 Tips for Structural Assemblage
- 4.3 Tips for Power Provision
5 Controlling Robot via WEB App
6 Common Problems and Solutions(Q&A)
7 Set The Program to Start Automatically
- 7.1 Set The Specified Program to Run Automatically
- 7.2 Change The Program That Starts Automatically
8 Remote Operation of Raspberry Pi Via MobaXterm
9 How to Control WS2812 RGB LED
10 How to Control The Servo
- 10.1 Control The Steering Gear to Rotate to A Cert
- 10.2 Control The Slow Motion of The Steering Gear
- 10.3 Non-blocking Control
11 How to Control DC Motor
12 Ultrasonic Module
13 Line Tracking
14 Make A Police Light or Breathing Light
- 14.1 Multi-threading Introduction
- 14.2 Realization of Police Lights / Breathing Ligh
- 14.3 Warning Lights or Breathing Lights in Other P
15 Real-Time Video Transmission
16 Automatic Obstacle Avoidance
17 Why OpenCV Uses Multi-threading to Process Vide
- 17.1 Single Thread Processing of Video Frames
- 17.2 Multi-thread Processing of Video Frames
18 OpenCV Learn to Use OpenCV
19 Using OpenCV to Realize Color Recognition and T
- 19.1 Color Recognition and Color Space
- 19.2 Process of Color Identifying and Tracking
- 19.3 Specific Code
- 19.4 HSV Color Component Range in OpenCV
20 Machine Line Tracking Based on OpenCV
- 20.1 Visual Line Inspection Process
- 20.2 Specific Code
21 Create A WiFi Hotspot on The Raspberry Pi
22 Install GUI Dependent Item under Window
- 22.1 Install GUI Dependencies
23 How to Use GUI
24 Control The WS2812 LED via GUI
25 Real-time Video Transmission Based on OpenCV
26 Use OpenCV to Process Video Frames on The PC
27 Enable UART
- 27.1 Mini UART and CPU Core Frequency
- 27.2 Disabling Linux's Use of Console UART
- 27.3 UART Output on GPIO Pins
- 27.4 UARTs and Device Tree
- 27.5 Relevant Differences Between PL011 and Mini U
28 Control Your AWR with An Android Device
Conclusion

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20 Machine Line Tracking Based on OpenCV

20.1 Visual Line Inspection Process

●For the development preparation and operation of OpenCV function, please refer to 18.

●Create camera_opencv.py in the folder where app.py and base_camera.py in 18, the code related to the

OpenCV visual line tracking function to be introduced in this chapter is written in camera_opencv.py.

●For safety reasons, this routine does not control the motor or servo motion, and only outputs OpenCV

calculation results.