粒子群算法下多无人机巡逻区域智能划分方法研究

打开文本图片集

中图分类号：TP29

文献标识码：A 文章编号：2096-4706（2026）05-0028-07

Research on Intelligent Division Method of Multi-UAV Patrol Areas Based on Particle Swarm Optimization Algorithm

LIU Zelin¹，SHEN Huanping'，LI Zheng²，WANG Xin² （1.AVIC ChinaHelicopterResearchandDevelopment Institute，Jingdezhen333ooo，China; 2.Unit 91548 of the Chinese People's Liberation Army， Sanya ， China）

Abstract： Aiming at the problems of uneven area division，low patrol eficiency and complex constraints in multi-UAV patroltasks，an intelligent multi-UAVpatrolarea division method basedonthe Particle Swarm Optimization （PSO）algorithm is proposed.Withthe matchingrelationshipbetween UAVpatrol spedandregionalareaasthecoreconstraint，this method optimizes thelayout，shapeandsizeofpatrolareas through thePSOalgorithm，whilereserving connectedresidual areas for deploying detection equipment to ensure thecoordinationbetween patroland monitoring.Comparative experiments with unconstrainedPSOandequal divisionmethodareconducted toverifytheefectivenessofthe proposed method.Theexperimental results show that the relative error of area division accuracy of this method is 0.28% ，andthepatrol timeisreduced by 43.8% （20 compared with that of unconstrained PSO.This method canstrictlyfollow the time minimization principle of area ratio O= speed ratio，generatepatrolareas withcompactlayoutandregularboundaries，andtheresidualareasmetthedeploymentrequirements of detection equipment， thus significantly improving the overalleffciency of multi-UAV patrol tasks.

Keywords： PSO algorithm; multi-UAV; patrol area division; intelligent optimization

0 引言

随着无人机技术的飞速迭代，其应用场景正不断向各领域深度延伸。（剩余10380字）