About This Course
Skills you'll learn from this course
- done_all Basics of Driverless Car Technology
- done_all Introduction to Buzzers
- done_all Buzzer integration on Raspberry Pi-based wheeled robots
- done_all Image Processing for Automatic Lane Detection and Following
Course "Build a Lane Following Driverless Car", which follows Course "Object Collection with Wheeled Robots", introduces the modern topic of autonomous vehicles and teaches students how to modify their wheeled robot to resemble a driverless car, how to program it to detect lanes on its path and follow its own lane on the road. Firstly, students learn about the basic features of driverless cars and their functions, along with the main artificial intelligence methodology currently used for lane detection and lane following. Then, they are taught how to attach a buzzer and two RGD LED lights as headlights to the 4-wheeled robot, how to connect them to the processing board, and how to further customize the robot to resemble a driverless car. Afterwards, the robot is connected to the programming environment and students study more image processing capabilities with OpenCV and the lane detection functions given in libraries in the Python programming language. Finally, the students combine the functions they learned to complete the navigation of the robot in a challenging track while staying inside its lane.
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Course Features
- check_circle Programming Environment
- check_circle Jupyter Notebook
- check_circle Forum & Support
Course Chapters
Course Introduction
Driverless Car- Course Objectives
Session 1: Theoretical Principles
- Session Objectives
- Driverless Vehicle?
- How do they work?
- Radar Sensors
- LIDAR Sensors
- Video Cameras
- Ultrasonic Sensors
- Driverless Cars Applications
- Mini Challenge
- Lane Detection steps
- Steps of Automatic Lane Detection for Self Driving Cars
- Mini Challenge
- Buzzer
- Buzzer Applications
- Mini Challenge
- Session Summary
Session 2: Hardware Assembly
- Session Objectives
- Component Intro
- Mini Challenge
- Assembly Preview
- Hardware Assembly
- Mini Challenge
- Vehicle Customization
- Session Summary
Session 3: Programming
- Session Objectives
- Robot Management
- WorkSpace Setup
- OpenCV & Python Review
- OpenCV-Python Detection
- Color Space Conversion
- Filtering Colors
- Canny Edge Detection
- ROI Filtering
- Mini Challenge
- HSV Settings
- Lane Following
- Session Summary
Session 4: Challenge
- Session Objectives
- Challenge Introduction
- HSV Settings
- Challenge Time
- Submit Your Code
- Upload Your Video
- Course Completion
