信息工程大学学报2024，Vol.25Issue(1)：80-84,5.DOI:10.3969/j.issn.1671-0673.2024.01.012
基于改进人工鱼群算法的无人机三维航迹规划
Three-dimensional Trajectory Planning for Unmanned Aerial Vehicles Based on Improved Artificial Fish Swarm Algorithm
摘要
Abstract
In the unmanned aerial vehicle(UAV)trajectory planning algorithm,to address the is-sues of easily falling into local optima and inefficient optimization in the traditional artificial fish swarm algorithm(AFSA),a step size attenuation function is introduced,and an adaptive step size artificial fish swarm algorithm(AS-AFSA)is proposed to achieve adaptive convergence in both glob-al and local aspects of trajectory planning.Furthermore,an optimization strategy for the individual fitness weight of artificial fish is provided to improve the convergence speed and accuracy of the AF-SA.Simulation results show that the improved algorithm performs exceptionally well in UAV trajecto-ry planning scenarios.Under the same number of iterations,the fitness is improved by 4.5%com-pared to the wolf colony algorithm(WCA)and 2.5%compared to the traditional AFSA.关键词
无人机/航迹规划/改进人工鱼群算法/自适应步长Key words
UAV/trajectory planning/improved AFSA/adaptive step size分类
信息技术与安全科学引用本文复制引用
田周泰,柴梦娟,刘广怡,张霞,余道杰..基于改进人工鱼群算法的无人机三维航迹规划[J].信息工程大学学报,2024,25(1):80-84,5.基金项目
国家自然科学基金资助项目(61871405) （61871405）
