无人机在次生灾害巡查中的优化运用
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摘要
运用优化工具与优化方法对无人机在抢险救灾过程的次生灾害巡查阶段进行了系统性的研究.首先确立巡查的区域范围,采用往返式"Z"型航行路线,结合无人机的续航时间确定无人机的全部行走路线.根据每架无人机在有效时间内可航行的总路径,结合优化计算将整个巡查区域划分为多个小区域.基于改良的贪婪算法求解出各个小区域的最佳无人机探测方案,以期获得整体最优飞行路线.由于每个小区域在一定时间间隔内需要重复巡查,对每个小区域进行细致的路径规划和无人机数量安排,确保满足巡查要求.
In this paper, the optimization tools and optimization methods are used to carry out systematic research on the secondary disaster inspection stage of unmanned aerial vehicle in the rescue and relief process. Firstly, the regional scope of inspection is established, and the roundtrip type "Z" is adopted. Combined the duration of the unmanned aerial vehicle to determine the entire path of unmanned aerial vehicle. According to the total path of unmanned aerial vehicle in the effective time, the whole inspection area is divided into several small areas according to the optimization calculation. Based on the improved greedy algorithm, the optimal unmanned aerial vehicle detection scheme for each small region is solved to obtain the overall optimal flight path. Because each small area needs to be repeated in a certain time interval, we will carry out detailed path planning and uav quantity arrangement for each small area to ensure that the inspection requirements are met.
In this paper, the optimization tools and optimization methods are used to carry out systematic research on the secondary disaster inspection stage of unmanned aerial vehicle in the rescue and relief process. Firstly, the regional scope of inspection is established, and the roundtrip type "Z" is adopted. Combined the duration of the unmanned aerial vehicle to determine the entire path of unmanned aerial vehicle. According to the total path of unmanned aerial vehicle in the effective time, the whole inspection area is divided into several small areas according to the optimization calculation. Based on the improved greedy algorithm, the optimal unmanned aerial vehicle detection scheme for each small region is solved to obtain the overall optimal flight path. Because each small area needs to be repeated in a certain time interval, we will carry out detailed path planning and uav quantity arrangement for each small area to ensure that the inspection requirements are met.
引文
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[2]张文元,付仲良.基于ArcGIS Engine的综合管线三维可视化研究[J].测绘通报.2008(8):28-31
[3]闵昌万,袁建平.军用飞行器航迹规划综述[J].飞行力学,1998,16(4):14-19.
[4]鲁艺,周德云.无人机初始路径规划空间建模方法研究[J].系统仿真学报,2007,19(3):491-493.
[5]Pellazar M B.Vehicle route planning with constraints using genetic algorithms[C].IEEE,1994,1:111-118.
[6]郑锐,冯振明,陆明泉.基于遗传算法的无人机航路规划优化研究[J].计算机仿真,2011,28(6):88-91.
[7]蒋定定,李万泉.基于改进蚁群算法的无人机侦察航路规划研究[J].飞机设计,2008,28(2):70-72.
[8]Davis G,Mallat S,Avellaneda M.Adaptive greedy approximations[J].Constructive Approximation,1997,13(1):57-98.
[9]Temlyakov V N,Zheltov P.Full length article:On performance of greedy algorithms[M].Academic Press,Inc,2011,163(9):1134-1145.
[10]董军军.动态规划算法和贪心算法的比较与分析[J].软件导刊,2008(2):129-130.