BIT*-based path planning for micro aerial vehicles
Menglu Lan, Shupeng Lai, Yingcai Bi, Hailong Qin, Jiaxin Li, Feng Dan Lin, Ben M. Chen · 2016
This paper presents a 3D on-line path planning algorithm for micro sized aerial vehicles (MAVs). The proposed approach adopts a two-layered planning framework. The first layer of the algorithm utilizes a sampling-based planner named Batch Informed Trees (BIT*) to quickly find an geometric obstacle-free passage. The second layer takes into account the dynamic constrains of the vehicle. By adopting a two-point boundary value problems (TPBVPs) approach, dynamically feasible trajectories can be generated efficiently within the previously found passage for lower-level controller. The main contribution of this work is proposing a complete on-line 3D path planning algorithm which can be implemented on the MAV with limited computational power.