无线电工程2025，Vol.55Issue(4)：866-876,11.DOI:10.3969/j.issn.1003-3106.2025.04.021
基于ISPSO-ACO融合的无人机三维路径规划算法
UAV 3D Path Planning Algorithm Based on ISPSO-ACO Fusion
摘要
Abstract
For the complex and constrained three-dimensional environment UAV path planning issue,the Spherical Vector-based Particle Swarm Optimization(SPSO)algorithm and Ant Colony Optimization(ACO)algorithm are combined for the first time,the SPSO algorithm is improved and a hybrid UAV three-dimensional path planning algorithm combining SPSO with Ant Colony Hybrid Algorithm—Improved SPSO and ACO(ISPSO-ACO)algorithm is proposed.The Piece Wise chaotic mapping is utilized to optimize the initialization and speed updates of the population in SPSO algorithm,enhancing the quality of initial solutions and the diversity of the search.Adaptive inertia weight coefficients and learning factors are designed to balance the algorithm's global and local search capabilities at different iterative stages.The ACO's pheromone initialization strategy is improved,using pre-searched path from ISPSO as an incremental value for the initial pheromone of ACO.A pseudo-random node transfer strategy is introduced to ensure the search's randomness while enhancing its target-oriented nature.Simulation results demonstrate that the ISPSO-ACO algorithm surpasses other algorithms in multiple dimensions,reducing the blindness of three-dimensional space search,and significantly enhancing search efficiency and path quality,effectively planning optimal paths for UAVs in diverse three-dimensional task environments.关键词
无人机/路径规划/球面矢量粒子群算法/蚁群算法/混合算法Key words
UAV/path planning/SPSO algorithm/ant colony algorithm/hybrid algorithm分类
信息技术与安全科学引用本文复制引用
刘江庭,祝顺康,顾秋逸,李大鹏..基于ISPSO-ACO融合的无人机三维路径规划算法[J].无线电工程,2025,55(4):866-876,11.基金项目
国家自然科学基金(62371245) National Natural Science Foundation of China(62371245) （62371245）
