摘要
主要针对无人机在抢险救灾中的灾情巡查问题探究新型巡查方法．通过变“覆盖巡查面”为“有效巡查点”，将传统的多无人机协同覆盖巡查问题转化为带有避障的VRP问题，并以所有无人机总飞行时间最少为目标建立相应的数学模型．运用MATLAB编写蚁群算法求解VRP中任意两点间的最短避障路线长度矩阵，进而用遗传算法来求解带有避障的VRP问题，得到不同需求下的最少无人机数量，规划出飞行路线．经过案例分析可得，此巡查路线覆盖率达到85．95％，具有较好的实用性．
In this paper, we focus on the research of UAV patrolling in areas affected by the disaster, which is a part of rescue and disaster relief. By changing ＂Covering inspection area＂ to ＂effective inspection point＂, the problem of multi-UAV collaborative coverage patrolling can be converted to VRP with obstacle avoidance problem.And a corresponding mathematical model is established with objective function of the least total UAVs＇ flight time.The ant colony algorithm is written by MATLAB to solve the shortest obstacle avoidance course length matrix between any two points in the VRP problem. And then the genetic algorithm is used to solve the VRP problem with obstacle avoidance. To obtain the minimum number of uav under different requirements and plan the flight path.After case analysis, the solution＇s coverage rate is 85.95%, which has a good practicability.
作者
宿爱静
张菲菲
方小星
杨文东
SU Ai-jing;ZHANG Fei-fei;FANG Xiao-xing;YANG Wen-dong(College of Civil Aviation,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China;College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics Nanjing 211106,China)
出处
《数学的实践与认识》
北大核心
2018年第15期37-45,共9页
Mathematics in Practice and Theory
基金
南京航空航天大学研究生创新基地(实验室)开放基金(kfjj20170714,kfjj 20170708)
关键词
无人机
路线规划
避障距离矩阵VRP问题
遗传算法
蚁群算法
UAV
route planning
obstacle avoidance matrix VRP problem
genetic algo-rithm
ant colony algorithm
