PixelBrax: Learning Continuous Control from Pixels End-to-End on the GPU

McInroe, Trevor, Garcin, Samuel

arXiv.org Artificial Intelligence 

We combine the Brax physics engine with a pure JAX renderer, allowing reinforcement learning (RL) experiments to run end-to-end on the GPU. PixelBrax can render observations over thousands of parallel environments and can run two orders of magnitude faster than existing benchmarks that rely on CPU-based rendering. Additionally, PixelBrax supports fully reproducible experiments through its explicit handling of any stochasticity within the environments and supports color and video distractors for benchmarking generalization.