铁道运输与经济2026，Vol.48Issue(5)：58-72,15.DOI:10.16668/j.cnki.issn.1003-1421.20250912002
基于改进GA-QPSO算法多无人机集群高原地区巡逻路径优化
Multi-UAV Swarm Patrol Route Optimization in Plateau Areas Based on Improved GA-QPSO Algorithm
摘要
Abstract
Restricted by the terrain and climate in plateau areas,unmanned aerial vehicle(UAV)patrol confronts multiple challenges.Multi-UAV swarm path planning requires a trade-off between safety and efficiency while adapting to the environment in plateau areas,so the development of an efficient and reliable path planning method is critical.This study focused on the path planning model and algorithm for multi-UAV swarm patrols for the low-altitude application scenarios in plateau areas,realizing automatic path optimization for multi-fleet scale under different objectives and quantitatively evaluating the improvement effects on safety and efficiency.Taking the typical mountainous environment of plateau areas as the research background,this paper constructed a simulation platform for plateau scenarios.On this basis,patrol mission scenarios were generated to conduct case verification.The results indicate that the proposed method,applicable to multi-UAV swarms with 2～15 UAVs,automatically plans paths to avoid hazardous terrains such as"terrain penetration"and generates optimized schemes with balanced objectives.Compared with traditional heuristic algorithms,the proposed algorithm reduces the total flight distance and the maximum mission completion time by up to 29.07%and 27.71%,respectively,which fully demonstrates the excellent multi-objective collaborative optimization performance.关键词
多无人机集群/高原巡逻路径/改进GA-QPSO算法/智能避障/分层优化Key words
Multi-UAV Swarm/Patrol Route in Plateau Area/Improved GA-QPSO Algorithm/Intelligent Obstacle Avoidance/Hierarchical Optimization分类
交通工程引用本文复制引用
陈华群,吴麟,高震宇,黄宇杰,王薏婷..基于改进GA-QPSO算法多无人机集群高原地区巡逻路径优化[J].铁道运输与经济,2026,48(5):58-72,15.基金项目
西藏自治区科技计划项目(XZ202403ZY0014,XZ202601ZY0091) （XZ202403ZY0014,XZ202601ZY0091）
中国民用航空飞行学院面上项目(25CAFUC03045) （25CAFUC03045）
中国民用航空飞行学院研究生科研创新基金项目(202601) （202601）
