AWS DeepRacer: How to master physical racing?

This article explores the challenges of physical AWS DeepRacer racing, highlighting the key differences between virtual and real-world racing environments and potential solutions for improving performance.

• The virtual simulator uses a simplified car model with basic physics, while real cars have complex mechanics
• Major simulation-to-real gaps include visual noise, camera motion blur, and steering imprecision
• Four key research questions were identified:
  • How to train models for real-world racing
  • How to evaluate car performance
  • How to test models on smaller tracks
  • How to modify cars for better performance
• Solutions included:
  • Customizing the simulator environment
  • Modifying car software
  • Creating custom smaller tracks

The author is preparing for re:Invent 2024, experimenting with improved DeepRacer technology and tracking performance.