AI algorithms for autonomous vehicles

 Algorithms for AI Driving Olympics: compressing information with autoencoders

Autonomous control algorithms for (small) vehicles are a challenging problem. Events like the Driving Olympics are an excellent testbed for new algorithms in cyber-physical domains. New frameworks with AI and ML libraries make it much easier to integrate custom ML solutions with cyber-physical systems without relying on expensive hardware. 

One of the critical subsystems for autonomous driving is denoising during the pre-training process. Experimenting with Variational Autoencoders (VAE) and visual domain randomization resulted in efficiently compressing input information into a latent representation.

#variationalautoencoders #drivingolympics #deeplearning #AI #VAE #latentrepresentation

#visualdomainrandomization #VDR

https://www.duckietown.org/research/ai-driving-olympics

https://www.ttic.edu/ripl/assets/publications/censi19.pdf