arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2109.07307cs.ROcs.HC

Expertise Affects Drone Racing Performance

University of Zurich(苏黎世大学);ETH Zurich(苏黎世联邦理工学院)

Christian Pfeiffer, Davide Scaramuzza

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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