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

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 minute...

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Vydané v:IEEE robotics and automation letters Ročník 8; číslo 12; s. 7913 - 7920
Hlavní autori: Zhou, Ziyu, Wang, Gang, Sun, Jian, Wang, Jikai, Chen, Jie
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 01.12.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Adaptive control
Aerodynamics
Computational efficiency
Computing time
Control architectures and programming
Flight
integrated planning and control
Optimization
optimization and optimal control
Planning
Predictive control
Quadrotors
Robustness
Tracking control
Trajectory
Trajectory control
Trajectory optimization
Trajectory planning
Waypoints
ISSN:2377-3766, 2377-3766
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Shrnutí: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. Furthermore, the planned paths are tracked via a time-adaptive model predictive control scheme whose allocated tracking time can be adaptively adjusted on-the-fly, therefore enhancing the tracking accuracy and robustness. We evaluate our approach through simulations and experimentally validate its performance in dynamic waypoint scenarios for time-optimal trajectory replanning and trajectory tracking.
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ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2023.3322075