Three-dimensional Path Planning for UAVs Based on Improved PSO-HO Algorithm
ZHANG Feiqiao
MA Xiong
WANG Rundong
LUO Dingfa
MA Xin
QIAO Yingcong
Abstract：To address the issues of local optima entrapment and insufficient global search capabilities in unmanned aerial vehi-cle(UAV)three-dimensional path planning,this paper proposes a hybrid strategy that combines particle swarm optimization(PSO)with hippo optimization(HO),named PSO-HO.This hybrid algorithm effectively integrates the advantages of both algo-rithms through a dynamic switching mechanism and introduces a scaling factor during the HO phase to enhance local search efficien-cy.Specifically,the approach begins with population initialization using an improved Circle mapping combined with an opposi-tion-based learning mechanism,ensuring a more uniform distribution of the population.Subsequently,a fitness variation function is used to monitor and guide the switching between PSO and HO algorithms,optimizing the synergy between global and local searches.During the HO phase,a cosine-decreasing scaling factor is introduced to adjust the aggregation of the hippo population,thereby en-hancing the local development capability of the algorithm.Experimental results demonstrate that this hybrid algorithm significantly improves convergence speed,effectively enhances optimization quality,and shows strong potential in handling complex optimiza-tion problems.
Keywords：Particle Swarm Optimization(PSO)Hippopotamus Optimization(HO)path planning
Publication Date：2025-05-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 56-60,152 )