クアッドロータのウェイポイント飛行における時間最適計画
Time-Optimal Planning for Quadrotor Waypoint Flight
軌道に沿った進行度を導入することで時間配分と軌道を同時最適化し、アクチュエータ限界を活かした真に時間最適なクアッドロータ軌道を生成する手法を提案した。実機のドローンレースで人間のエキスパートパイロットを上回った。
著者: Philipp Foehn, Angel Romero, Davide Scaramuzza
分類: cs.RO, cs.AI, cs.SY, eess.SY
原文アブストラクト
Quadrotors are among the most agile flying robots. However, planning time-optimal trajectories at the actuation limit through multiple waypoints remains an open problem. This is crucial for applications such as inspection, delivery, search and rescue, and drone racing. Early works used polynomial trajectory formulations, which do not exploit the full actuator potential because of their inherent smoothness. Recent works resorted to numerical optimization but require waypoints to be allocated as costs or constraints at specific discrete times. However, this time allocation is a priori unknown and renders previous works incapable of producing truly time-optimal trajectories. To generate truly time-optimal trajectories, we propose a solution to the time allocation problem while exploiting the full quadrotor's actuator potential. We achieve this by introducing a formulation of progress along the trajectory, which enables the simultaneous optimization of the time allocation and the trajectory itself. We compare our method against related approaches and validate it in real-world flights in one of the world's largest motion-capture systems, where we outperform human expert drone pilots in a drone-racing task.
