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Rotary unmanned aerial vehicles path planning in rough terrain based on multi-objective particle swarm optimization

查看全文 作　　者：XU [1]Zhen;ZHANG [2]Enze;CHEN [1]Qingwei 高影响力作者 机构地区：[1]School of Automation,Nanjing University of Science and Technology,Nanjing 210094,China;[2]College of Information Engineering,Yangzhou University,Yangzhou 225009,China高影响力机构 出　　处：《Journal of Systems Engineering and Electronics》索引2020年第31卷第1期,共12页高影响力期刊 基　　金：supported by the National Natural Science Foundation of China(61673214;61673217;61673219);the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(18KJB120011);the Postgraduate Research and Practice Innovation Program of Jiangsu Province(KYCX19_0299) 摘　　要：This paper presents a path planning approach for rotary unmanned aerial vehicles(R-UAVs)in a known static rough terrain environment.This approach aims to find collision-free and feasible paths with minimum altitude,length and angle variable rate.First,a three-dimensional(3D)modeling method is proposed to reduce the computation burden of the dynamic models of R-UAVs.Considering the length,height and tuning angle of a path,the path planning of R-UAVs is described as a tri-objective optimization problem.Then,an improved multi-objective particle swarm optimization algorithm is developed.To render the algorithm more effective in dealing with this problem,a vibration function is introduced into the collided solutions to improve the algorithm efficiency.Meanwhile,the selection of the global best position is taken into account by the reference point method.Finally,the experimental environment is built with the help of the Google map and the 3D terrain generator World Machine.Experimental results under two different rough terrains from Guilin and Lanzhou of China demonstrate the capabilities of the proposed algorithm in finding Pareto optimal paths. 关 键 词：unmanned aerial vehicle(UAV) path planning multiobjective optimization particle swarm optimization
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