摘要
随着低空空域逐步开放,无人机作为重要的低空飞行器在各领域已获得到广泛应用。然而,现有的单无人机航迹规划技术已经难以满足日益增长的复杂环境与繁重任务需求,因此多无人机协同作业与智能规划成为当前研究重难点。针对多无人机航前路径规划场景,提出基于海星优化算法(starfish optimization algorithm, SFOA)的三维环境下的多无人机航迹规划方法,并通过对比实验来验证了该算法在路径优化方面的有效性与优越性。研究表明,在复杂三维静态环境下,SFOA展现出良好的全局搜索能力和较高的规划效率,为多无人机协同作业提供了一种新的解决方案。
With the gradual opening of the low-altitude airspace,unmanned aerial vehicles(UAVs)have been extensively applied in diverse fields as crucial low-altitude aircraft.However,the increasing demands of complex environments and arduous tasks can hardly be satisfied using the existing single-UAV flight planning techniques.Thus,multiple UAVs cooperative operations and intelligent planning have been considered as the current research hotspots and challenging tasks.A multiple UAVs flight path planning method in a three-dimensional environment based on the starfish optimization algorithm(SFOA)was proposed for multi-UAV pre-flight path planning scenarios.The effectiveness and superiority of this algorithm in path optimization were verified through comparative experiments.The research results show that in a complex three-dimensional static environment,the SFOA demonstrates good global search capabilities and high planning efficiency,providing a new solution for multi-UAV cooperative operations.
作者
杨泳
付玉洁
李东霖
徐开俊
YANG Yong;FU Yu-jie;LI Dong-lin;XU Kai-jun(School of Flight Technology,Civil Aviation Flight School of China,Guanghan 618307,China;Sichuan Provincial Engineering Research Center of Domestic Civil Aircraft Flight and Operation Support,Guanghan 618307,China)
出处
《科学技术与工程》
北大核心
2026年第1期387-394,共8页
Science Technology and Engineering
基金
国产民机飞行与运行支持四川省工程研究中心开放基金(MJCYZY202503)
2024年度中央高校基本科研项目(24CAFUC04002)
四川省民航机场智慧运营与维护工程研究中心自主研究项目(JCZX2023ZZ07)
四川省民航飞行技术与飞行安全工程技术中心项目(GY2024-30D)
2025年度大学生创新创业项目(202510624005)。
关键词
低空空域
三维环境
多无人机
海星优化算法
low-altitude airspace
three-dimensional environment
multiple UAVs
starfish optimization algorithm
