The backend research in deep learning never ceases. Starting from a simple open-loop CNN regression structure for car control, we experiment with a variety of architectures including Categorical CNN,  LSTM, and Transformer, some of which yields exciting results in competitions. We’ve also developed computer vision pipelines that assist the feature extraction of neural networks.

We are part of the global DIY robocar community which hosts regular competitions of autonomous robotic vehicles. We fly to different parts of the state with our vehicles, and achieve top results in the races. Even durning the pandemic, with everything happening in the simulator, we are still actively competing against racers joining us online from around the world.