A Path Planning Algorithm for Smooth Trajectories of Unmanned Aerial Vehicles via Potential Fields

Abstract

Path planning is of critical importance to Unmanned Aerial Vehicle (UAV) based applications like unmanned delivery and inspection. The operating space of UAVs in urban environments is usually complex and dynamic. Safety and efficiency are hence the major concerns for UAV operations. Traditional path planning algorithms tend to find trajectories for UAVs in terms of safety which are theoretically optimal. However, the objective is usually difficult to achieve in practice given the complex operating environments and limited UAV capabilities. Thus, a path planning algorithm for UAVs that finds feasible trajectories is needed for UAV-based operations. In this paper, an Artificial Potential Field (APF) based algorithm is proposed for UAV's trajectory planning considerings concerns of safety, efficiency and kinetic constraints of UAVs. Simulation results show an improvement of 23% on efficiency and 89.5% on smoothness of trajectories over existing heuristic based methods. Performance metrics of safety, efficiency and smoothness of trajectories are analyzed based on simulation results. Parameter values in obtaining the good performance metrics have been suggested in the end of the paper.