Path planning for unmanned aerial vehicles in surveillance tasks under wind fields

作     者：张兴 陈杰 辛斌 

作者机构：School of AutomationBeijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems 

出 版 物：《Journal of Central South University》 (中南大学学报（英文版）)

年 卷 期：2014年第21卷第8期

页      面：3079-3091页

核心收录：

学科分类：0810[工学-信息与通信工程] 0806[工学-冶金工程] 08[工学] 080202[工学-机械电子工程] 0804[工学-仪器科学与技术] 0805[工学-材料科学与工程（可授工学、理学学位）] 082503[工学-航空宇航制造工程] 0703[理学-化学] 0802[工学-机械工程] 0825[工学-航空宇航科学与技术] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Project(61120106010)supported by the Projects of Major International(Regional)Joint Research Program Nature Science Foundation of China Project(61304215,61203078)supported by National Natural Science Foundation of China Project(2013000704)supported by the Beijing Outstanding Ph.D.Program Mentor,China Project(61321002)supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China 

主　　题：unmanned aerial vehicle path planning in wind field Dubins traveling salesman problem terminal heading relaxation differential evolution 

摘      要：The optimal path planning for fixed-wing unmanned aerial vehicles(UAVs) in multi-target surveillance tasks(MTST) in the presence of wind is *** take into account the minimal turning radius of UAVs,the Dubins model is used to approximate the dynamics of *** on the assumption,the path planning problem of UAVs in MTST can be formulated as a Dubins traveling salesman problem(DTSP).By considering its prohibitively high computational cost,the Dubins paths under terminal heading relaxation are introduced,which leads to significant reduction of the optimization scale and difficulty of the whole ***,in view of the impact of wind on UAVs paths,the notion of virtual target is *** application of the idea successfully converts the Dubins path planning problem from an initial configuration to a target in wind into a problem of finding the minimal root of a transcendental ***,the Dubins tour is derived by using differential evolution(DE) algorithm which employs random-key encoding technique to optimize the visiting sequence of ***,the effectiveness and efficiency of the proposed algorithm are demonstrated through computational *** results exhibit that the proposed algorithm can produce high quality solutions to the problem.