Champion level Drone Racing using Deep Reinforcement Learning ( Nature, 2023)
Firstperson view (FPV) drone racing is a televised sport in which professional competitors pilot highspeed aircraft through a threedimensional circuit. Each pilot sees the environment from their drones perspective via video streamed from an onboard camera. Reaching the level of professional pilots with an autonomous drone is challenging since the robot needs to fly at its physical limits while estimating its speed and location in the circuit exclusively from onboard sensors. 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 in simulation with data collected in the physical world. Swift competed against three human champions, including the world champions of two international leagues, in realworld headtohead races. Swift won multiple races against each of the human champions and demonstrated the fastest recorded race time. This work represents a milestone for mobile robotics and mach
|
|