Champion-level drone racing using deep reinforcement learning

Abstract First-person view (FPV) drone racing is a televised sport in which professional competitors pilot high-speed aircraft through a 3D circuit. Each pilot sees the environment from the perspective of their drone by means of video streamed from an onboard camera. Reaching the level of professional pilots with an autonomous drone is challenging because the robot needs to fly at its physical limits while estimating its speed and location in the circuit exclusively from onboard sensors 1 . Here we introduce Swift, an autonomous system that can race physical vehicles at the level of the human world champions. The system combines deep reinforcement learning (RL) in simulation with data collected in the physical…

• NS
  National Science Foundation
• SN
  Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
• IO
  Institute of Nuclear Energy Research