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

• Published in: IEEE internet of things journal 2018-04, Vol.5 (2), p.546-558
• Main Authors: Yin, Chao, Xiao, Zhenyu, Cao, Xianbin, Xi, Xing, Yang, Peng, Wu, Dapeng
• Format: Article
• Language: English
• Subjects: Collision avoidance; Collision dynamics; Flight; Geography; Low altitude; Low altitude urban environment; Multiple objective analysis; Obstacle avoidance; offline and online search; Path planning; Product design; Safety; safety index map (SIM); Searching; Sensors; unmanned aerial vehicle (UAV) path planning; Unmanned aerial vehicles; Urban areas; Vehicle dynamics
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2017.2717078

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.