无人机在抢险救灾中的优化应用

doi:10.16180/j.cnki.issn1007-7820.2019.09.005

摘要/Abstract

摘要：

针对在抢险救灾中的多无人机路径规划问题,文中采用遗传算法通过对无人机群的巡航矩阵进行编码组成染色体,设置不同个体数目和最大遗传代数优化巡航轨迹,同时采用0-1规划和非线性规划建立无人机终端流量传输矩阵,为每一个用户分配恰当的功率,使得无人机完成所有任务的时间总和最短。遗传算法分析结果:当从H 和J两处各派出3架无人机时至少需要11.37 h才能完成对7个重点区域的生命迹象搜索,此时巡航总距离为3 808 km,从H处派出3架无人机携带通信装备,并向灾区内的72个地面终端发送不同内容,至少需要25.81 h才能完成所有任务,此时巡航总距离为1 547 km。

关键词: 无人机, 抢险救灾, 生命迹象探测, 遗传算法, 0-1规划, 非线性规划, 路径规划

Abstract:

For the multi-UAV path planning problem in disaster relief, the genetic algorithm was used to encode the cruise matrix of the UAV group to form a chromosome, the number of individuals and the maximum genetic algebra to optimize the cruise trajectory was set, and a drone terminal traffic transfer matrix that assigns the appropriate power to each user was established due to the 0-1 planning and non- Linear programming, minimizing the sum of time for the drone to complete all tasks. Genetic algorithm analysis results: When 3 drones were sent from H and J, it was took at least 11.37 h to complete the life sign search for the seven key areas. At this time, the total distance of the cruise was 3 808 km, and 3 planes were dispatched from H. The communication equipment and sends different content to the 72 ground terminals in the disaster area was carried by the drone. It was took at least 25.81 h to complete all tasks. At this time, the total distance of the cruise was 1 547 km.

Key words: drone, disaster relief, signs of life detection, genetic algorithm, 0-1 planning, nonlinear programming, route plan

中图分类号:

TN256

陈昊,沈景凤,赵程. 无人机在抢险救灾中的优化应用[J]. 电子科技, 2019, 32(9): 20-25.

CHEN Hao,SHEN Jingfeng,ZHAO Cheng. The Application of UAV in Emergency Rescue and Disaster Relief[J]. Electronic Science and Technology, 2019, 32(9): 20-25.

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	无人机	无人机	无人机
序号	1	2	3
行程/km	682.39	682.394	682.39
巡航时间/h	11.37	11.37	11.37
序号	4	5	6
行程/km	586.926	586.926	586.926
巡航时间/h	9.782 101	9.782 101	9.782 101

无人机	U₁	U₂	U₃
行程/km	302.63	628.02	617.42
时间/h	5.04	10.47	10.30