  First-person view drone racing has become a popular televised sport. However,
very little is known about the perceptual and motor skills of professional
drone racing pilots. A better understanding of these skills may inform path
planning and control algorithms for autonomous multirotor flight. By using a
real-world drone racing track and a large-scale position tracking system, we
compare the drone racing performance of five professional and five beginner
pilots. Results show that professional pilots consistently outperform beginner
pilots by achieving faster lap times, higher velocity, and more efficiently
executing the challenging maneuvers. Trajectory analysis shows that experienced
pilots choose more optimal racing lines than beginner pilots. Our results
provide strong evidence for a contribution of expertise to performances in
real-world human-piloted drone racing. We discuss the implications of these
results for future work on autonomous fast and agile flight. We make our data
openly available.
