Efficient and Robust Time-Optimal Trajectory Planning and Control for Agile Quadrotor Flight

Understand

Agile quadrotor flight relies on rapidly planning and accurately tracking time-optimal trajectories, a technology critical to their application in the wild.

• However, the computational burden of computing time-optimal trajectories based on the full quadrotor dynamics (typically on the order of minutes or even hours) can hinder its ability to respond quickly to changing scenarios.
• Additionally, modeling errors and external disturbances can lead to deviations from the desired trajectory during tracking in real time.
• This letter proposes a novel approach to computing time-optimal trajectories, by fixing the nodes with waypoint constraints and adopting separate sampling intervals for trajectories between waypoints, which significantly accelerates trajectory planning.