Multi-objective offline and online path planning for UAVs under dynamic urban environment

This paper presents a multi-objective hybrid path planning method MOHPP for unmanned aerial vehicles (UAVs) in urban dynamic environments. Several works have been proposed to find optimal or near-optimal paths for UAVs. However, most of them did not consider multiple decision criteria and/or dynamic obstacles. In this paper, we propose a multi-objective offline/online path planning method to compute an optimal collision-free path in dynamic urban environment, where two objectives are considered: the safety level and the travel time. First, we construct two models of obstacles; static and dynamic. The static obstacles model is based on Fast Marching Square (FM2) method to deal with the uncertainty of the geography map, and the unexpected dynamic obstacles model is constructed using the perception range and the safety distance of the UAV. Then, we develope a jointly offline and online search mechanism to retrieve the optimal path. The offline search is applied to find an optimal path vis-a-vis the static obstacles, while the online search is applied to quickly avoid unexpected dynamic obstacles. Several experiments have been performed to prove the efficiency of the proposed method. In addition, a Pareto front is extracted to be used as a tool for decision making.
UAV path planning, Dynamic urban environment, Fast Marching Square, Drone, Multi-objective path planning methods, MOHPP