基于IPSO⁃GA算法的无人机三维路径规划  

UAV 3D path planning based on IPSO⁃GA algorithm

作　　者：胡观凯 钟建华 李永正 黎万洪 HU Guankai;ZHONG Jianhua;LI Yongzheng;LI Wanhong(Sichuan Institute of Industrial Science and Technology,Deyang 618000,China;The Second Research Institute of Civil Aviation of China,Chengdu 610000,China;School of Science,Civil Aviation Flight Academy of China,Deyang 618000,China;Chongqing Chang’an Automobile Software Technology Co.,Ltd.,Chongqing 400000,China)

机构地区：[1]四川工业科技学院,四川德阳618000 [2]中国民航局第二研究所,四川成都610000 [3]中国民航飞行学院理学院,四川德阳618000 [4]重庆长安汽车软件科技有限公司,重庆400000

出　　处：《现代电子技术》2023年第7期115-120,共6页Modern Electronics Technique

基　　金：国家重点研发计划项目(2022YFB2602400);四川省重点研发项目(22ZDYF2958);四川省成都航空产业发展与文化建设研究中心课题(CAIACDRCXM2022⁃29)。

摘　　要：针对传统粒子群优化(PSO)算法参数设置难且易陷入局部最优,遗传算法(GA)易早熟、局部搜索能力差、规划路径不平滑等问题,提出了改进粒子群遗传算法(IPSO⁃GA)的无人机路径规划方法。根据地形环境模型绘制出无人机飞行的地形环境,根据约束条件和目标函数建立无人机飞行的数学模型;IPSO⁃GA通过在产生下一代群体时引入选择、复制和变异操作,产生更优质群体,并寻找最优路径,通过三次B样条插值平滑飞行路径,仿真结果表明,代价值和迭代次数皆得到改善,具有较好的鲁棒性。In allusion to the problems that traditional particle swarm optimization(PSO)algorithm is difficult to set parameters and easy to fall into local optimum,genetic algorithm(GA)is prone to premature and has poor local search ability,and the planning path is not smooth,an UAV path planning method based on the improved particle swarm optimization and genetic algorithm(IPSO⁃GA)is proposed.The terrain environment of UAV flight is drawn according to the terrain environment model.The mathematical model of UAV flight is established according to the constraint conditions and objective functions.An improved IPSO⁃GA is proposed.By introducing selection,replication and mutation operations when generating the next generation population,a better population is generated,and the optimal path is found.The flight path is smoothed by cubic B⁃spline interpolation.The simulation results show that the cost value and the number of iterations are improved and have good robustness.

关 键 词：无人机 路径规划 粒子群算法 遗传算法 地形绘制 数学模型 最优路径寻找 

分 类 号：TN919-34[电子电信—通信与信息系统] TP391.9[电子电信—信息与通信工程]