An improved artificial potential field based path planning algorithm for unmanned aerial vehicle in dynamic environments
Shoufeng Chen, Zhihua Yang, Zhentao Liu, Haojie Jin · 2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) · 2017
In a dynamic environment, an Unmanned Aerial Vehicle (UAV) confronts frequently with stochastic obstacles during tracking a moving target. In this paper, we proposed an improved artificial potential field based trajectory planning algorithm for UAV tracking a dynamic target. In particular, the proposed algorithm constructed a new repulsion field by coupling a directional coordination force with relative distance between UAV and target. As a result, it can effectively solve a local minimum problem in optimization on a general potential field function, without introducing unexpected collisions with stochastically moving obstacles. Simulation results verify the feasibility and effectiveness of the proposed method.