Image-Based Motion Planning for High-Speed Flight in Unknown Cluttered Environment

Fang Liao, Pengfei Wang, Kemao Peng, Rodney Teo, Feng Lin, Jianliang Wang

Abstract: In this paper, a novel motion planning approach is proposed for high-speed flight of Micro Air Vehicles (MAVs) in unknown cluttered environment using a stereo camera as unique sensor. The proposed motion planning works directly on a depth map which represents partial surrounding environment due to limited field of view (FOV) of the stereo camera. The depth map updates at each sampling time. An optimal local target is selected from a set of local targets to which line-of-sight paths are collision-free. Then an optimal collision-free trajectory satisfying kinematic constraints is generated. The simulation results demonstrate the effectiveness of the proposed motion planning approach.