Learn to Drive (and Race!) Autonomous Vehicles

on YouTube ↗01h 51m

" summary

Hands-on course that puts working code on a 1/10-scale F1TENTH car (NVIDIA Jetson + LiDAR + camera) and in two simulators (f110_gym and Unity/LGSVL). Students run follow-the-gap reactive navigation, implement mapping/localization with Google Cartographer and particle filters, and tune a pure pursuit controller; advanced work uses a graph-based planner with spline costs, velocity optimization and MPC-style refinements. Code is in Python/C++, runs at realcar speeds up to 40–50 mph, and supports competition-ready stacks used by 60+ universities.

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" chapters (38)

1. 0:00Start
2. 3:23Obstacle Avoidance
3. 3:40Learn to Race
4. 4:16What It Takes To Build an Autonomous Vehicle
5. 7:16Behavioral Planner
6. 9:32Tesla Vehicles Were Recalled because of Safety Concerns
7. 13:45Overview
8. 14:30110 Scale Autonomous Racing Car
9. 18:09Av Driving Basics
10. 19:01An Automatic Emergency Braking System
11. 20:05False Negatives
12. 20:31Simulation Environments
13. 32:07Reactive Algorithms
14. 34:22Reactive Planning Algorithms
15. 35:48Planar Lidar
16. 45:57Hands-on Code
17. 48:33Adjust the Parameters
18. 50:19Fastest Way To Get around the Track
19. 54:07Global Optimal Race Lines
20. 55:06Minimum Curvature Line
21. 55:16Minimizing the Curvature
22. 56:08Minimum Time Trajectory Planning
23. 58:32The Controller
24. 59:22The Pure Pursuit Controller
25. 1:00:50Pure Pursuit Algorithm
26. 1:01:15Look-Ahead Distance
27. 1:02:26Eckermann Steering
28. 1:07:11The Steering Angle
29. 1:07:39Steering Angle
30. 1:09:12Creating a Radius Based on the Look Ahead Distance
31. 1:12:13Tuning
32. 1:22:08N Layer Graph Search
33. 1:23:41Graph Based Planner
34. 1:27:26What Is a Spline
35. 1:28:43C2 Continuity
36. 1:32:29Action Templates
37. 1:37:57Tracking Path and Velocity
38. 1:44:54Next Big Autonomous Racing Competition

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