We leverage human eye-gaze data to train a deep learning controller for vision-based autonomous drone racing. Our controller achieves performances as good as human pilots.
We compare drone racing performances among human pilots in real-world racing. Our analysis shows that experts consistently achieve more optimal racing lines, maneuver execution, and faster laptimes than beginners.
We This work investigates the relationship between human eye movements, control behavior, and flight performance in a drone racing task.