UAVs Path Planning Based on Improved Artificial Fish Swarm Algorithm
LIN Zhijian
YANG Liuqing
TU Zhuang
ZHANG Yong
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.
Keywords：artificial fish swarm algorithmpath planningadaptive visual fieldLévy flight
Publication Date：2024-12-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 33-38 )