信息与控制2023，Vol.52Issue(6)：747-757,772,12.DOI:10.13976/j.cnki.xk.2023.2372
基于改进狮群算法的城市无人机低空路径规划
Low Altitude Path Planning of Urban UAV Based on Improved Lion Swarm Optimization
摘要
Abstract
In order to solve the problems of the intelligent optimization algorithm in the three-dimensional(3D)path planning of grid method,such as weak searching ability,many turns and large angles of the planned path.In response to these problems,we propose an improved lion swarm optimiza-tion(ILSO)algorithm.Firstly,on the basis of the lion swarm optimization(LSO),we firstly in-tegrate the Cauchy mutation operator to perform disturbance mutation at the optimal solution posi-tion to enhance the ability to jump out of the local optimal solution.Secondly,for the problem of path planning,we introduce the valuation function to screen the node connections,so as to avoid blind search of the algorithm.Thirdly,we perform a quadratic planning operation on the planned path to increase the probability that the algorithm will obtain the optimal solution.At the same time,we smooth the planning result by using the cubic B-spline function.Finally,the simulation results show that the ILSO algorithm is compared with genetic algorithm,particle swarm optimiza-tion,whale optimization algorithm,lion swarm optimization.The path is shortened by 5.42％,the time is shortened by 17.14％,and the number of turns is reduced by 45.71％on average under different distance planning.关键词
改进狮群算法/3维路径规划/无人机/B-spline/柯西变异Key words
improved lion swarm optimization/3D path planning/UAV/B-spline/Cauchy mutation分类
航空航天引用本文复制引用
黄志锋,刘媛华..基于改进狮群算法的城市无人机低空路径规划[J].信息与控制,2023,52(6):747-757,772,12.基金项目
国家自然科学基金(72071130) （72071130）
