About This Course
Skills you'll learn from this course
- done_all Driverless Cars Benefits & Challenges
- done_all Driverless Cars Autonomy Levels
- done_all Introduction to Machine Learning Basic Principles
- done_all Introduction to SVM and Neural Network Models
- done_all Computer Vision for Human Detection and Tracking on Driverless Cars
During Course "Human Tracking with Driverless Cars", which continues the driverless cars topic introduced in Course "Build a Lane Following Driverless Car", students will be able to study how to harness the power of Machine Learning and Computer Vision to make their wheeled robot capable of detecting humans in front of it and following them. Students will firstly continue to study driverless cars and challenges that they face on the way to full autonomy, while getting introduced to Machine Learning and how it assists with modern applications, especially for human detection. Then, Python commands and functions of OpenCV and our Machine Learning framework are taught, so that the students become familiar with some processes that are used for this course's challenge. Finally, students are presented with the challenge of using our Machine Learning framework to visually detect humans in front of the wheeled robot and follow it.
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Course Features
- check_circle Programming Environment
- check_circle Jupyter Notebook
- check_circle Forum & Support
Course Chapters
Course Introduction
Car Autonomy Challenges- Course Objectives
Session 1: Theoretical Principles
- Session Objectives
- Driverless Car Benefits
- Technical Challenges
- Human Challenges
- Other Challenges
- Driving Automation Levels
- Mini challenge
- Machine Learning Basics
- ML and Deep Learning
- Driverless Car Vision
- Human Detection
- Human Detection with CV
- Mini-challenge
- Session Summary
Session 2: Hardware Assembly
Session 3: Programming
- Session Objectives
- Robot Management
- WorkSpace Setup
- Lane Detection Review
- Python Classes
- Mini Challenge
- CV with ML
- Mini Challenge
- Human Tracking
- Session Summary
Session 4: Challenge
- Challenge Introduction
- Challenge Time
- Submit Your Code
- Upload Your Video
- Course Completion
