南京邮电大学学报（自然科学版）2024，Vol.44Issue(6)：120-127,8.DOI:10.14132/j.cnki.1673-5439.2024.06.012
基于改进粒子群算法的无人机三维路径规划
UAV 3D path planning based on improved particle swarm optimization algorithm
摘要
Abstract
In order to solve the problem that the traditional particle swarm optimization algorithm has strong dependence on parameters and is easy to fall into local optimization,chaotic mapping,improved iteration formula and Cauchy mutation operator are introduced to improve the performance of the algorithm.Firstly,establish the three-dimensional operating space of UAV.Secondly,considering ground and air suspension obstacles factors,the fitness function is constructed.In the process of algorithm iteration,Logistic chaotic mapping with interval constraint is introduced to enhance the randomness of the initial particle distribution,and the global search ability and local search ability of the nonlinear iterative formula balance algorithm are improved.Then Cauchy mutation operator is introduced to avoid the algorithm falling into local optimality.Finally,a large number of experimental results show that compared with the three typical path planning algorithms,the improved particle swarm optimization algorithm has a strong ability to jump out of the local optimal and has a stable optimization ability.关键词
粒子群算法/混沌映射/非线性/柯西变异/三维路径规划/无人机Key words
particle swarm optimization(PSO)/chaotic mapping/nonlinearity/Cauchy variation/three-dimensional path planning/unmanned aerial vehicle(UAV)分类
信息技术与安全科学引用本文复制引用
朱润泽,赵静,蒋国平,肖敏,徐丰羽..基于改进粒子群算法的无人机三维路径规划[J].南京邮电大学学报（自然科学版）,2024,44(6):120-127,8.基金项目
航空航天结构力学及控制国家重点实验室开放课题(MCMS-E-0123G04)、工业控制技术全国重点实验室开放课题(ICT2023B21)、江苏省研究生科研与实践创新计划项目(KYCX24_1214)、国家自然科学基金面上项目(51775284)、直升机动力学全国重点实验室开放课题(2024-ZSJ-LB-02-05)和南京邮电大学校级自然科学基金(NY223119)资助项目 （MCMS-E-0123G04）
