Multi-strategy fusion improved sand cat swarm optimization algorithm for UAV 3D path planning
CUI Chen
TIAN Liqin
WU Wenxing
JI Haosen
Abstract：Aiming at the problems of high flight cost and poor stability of the Sand Cat Swarm Optimization al-gorithm in the three-dimensional path of UAV emergency rescue,the Multi Strategy Sand Cat Swarm Optimiza-tion algorithm(MSSCSO)was proposed in the paper.Firstly,the Sobol sequence was used to initialize the population to enhance the diversity of the population.Secondly,the golden sine-based strategy was integrated in the development stage to improve the local search ability of the algorithm.Finally,a nonlinear adjustment strategy was used to balance the exploration and development stages of the algorithm.Simulation results on simple and complex threat terrains show MSSCSO reduces average flight costs by 0.3％and 8.9％respectively versus the original algorithm,while achieving perfect(100％)pathfinding success and the minimal standard deviation among six benchmark algorithms.The experimental results show that the MSSCSO algorithm signifi-cantly improves the efficiency and stability of UAV three-dimensional path planning.
Keywords：sand cat swarm optimization algorithmmulti-strategy fusionUAVpath planning3D environ-ment
Publication Date：2025-06-30
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：11( 45-55 )