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Offline and Online Search: UAV Multiobjective Path Planning Under Dynamic Urban Environment

2017; Institute of Electrical and Electronics Engineers; Volume: 5; Issue: 2 Linguagem: Inglês

10.1109/jiot.2017.2717078

2372-2541

Chao Yin, Zhenyu Xiao, Xianbin Cao, Xing Xi, Peng Yang, Dapeng Wu,

Robotics and Sensor-Based Localization

This paper is concerned with path planning for unmanned aerial vehicles (UAVs) flying through low altitude urban environment. Although many different path planning algorithms have been proposed to find optimal or near-optimal collision-free paths for UAVs, most of them either do not consider dynamic obstacle avoidance or do not incorporate multiple objectives. In this paper, we propose a multiobjective path planning (MOPP) framework to explore a suitable path for a UAV operating in a dynamic urban environment, where safety level is considered in the proposed framework to guarantee the safety of UAV in addition to travel time. To this aim, two types of safety index maps (SIMs) are developed first to capture static obstacles in the geography map and unexpected obstacles that are unavailable in the geography map. Then an MOPP method is proposed by jointly using offline and online search, where the offline search is based on the static SIM and helps shorten the travel time and avoid static obstacles, while the online search is based on the dynamic SIM of unexpected obstacles and helps bypass unexpected obstacles quickly. Extensive experimental results verify the effectiveness of the proposed framework under the dynamic urban environment.