舰船电子工程2024，Vol.44Issue(12)：33-38,6.DOI:10.3969/j.issn.1672-9730.2024.12.008
基于改进人工鱼群算法的无人机集群航迹规划
UAVs Path Planning Based on Improved Artificial Fish Swarm Algorithm
摘要
Abstract
Aiming at the efficient and fast path planning of UAVs in complex battlefield environment,an improved artificial fish swarm algorithm with adaptive mechanism is proposed.On the basis of traditional artificial fish swarm algorithms,the popula-tion initialization based on Logistic mapping is introduced to enhance the diversity of the population.An adaptive visual field model is presented,which can adjust the visual field size of fish swarm adaptively according to the optimization situation,so it can improve the convergence speed of the algorithm.Finally,the random walk based on Lévy flight path is added to the artificial fish behavior to enhance the global optimization ability and convergence accuracy of the algorithm.Comparing the improved algorithm with tradition-al artificial fish swarm algorithm and particle swarm optimization,the simulation results show that the improved algorithm has the smallest path cost,meanwhile the convergence accuracy and speed of the algorithm have been greatly improved.关键词
人工鱼群算法/航迹规划/自适应视野/莱维飞行Key words
artificial fish swarm algorithm/path planning/adaptive visual field/Lévy flight分类
航空航天引用本文复制引用
林志坚,杨柳庆,屠壮,张勇..基于改进人工鱼群算法的无人机集群航迹规划[J].舰船电子工程,2024,44(12):33-38,6.基金项目
国家自然科学基金项目(编号:52272369)资助. （编号:52272369）
