A Fast Switching-based Trajectory Planning Algorithm for Aggressive Quadrotor Flight
Junjie Gao, Haodi Yao, Hongxu Cao, Fenghua He · 2022 41st Chinese Control Conference (CCC) · 2022
In this paper, an online trajectory planning problem is investigated for aggressive quadrotor flight in cluttered environments with multi-form narrow gaps. An efficient planning framework is developed, in which a switching policy is designed to choose planning methods based on the obstacle information. First, we propose the Guide State Set (GSS) generating algorithm to derive feasible states from the narrow free space (NFS). Next, the initial path is obtained using the generated GSSs: When the search process is near a GSS, a guide trajectory with an expected final state is generated to prevent the aimless expansions. If the current state is away from all GSSs, the graph search method is applied with a lazy checking strategy to speed up searching. Finally, the proposed method is validated by simulation and experimental results.