基于改进粒子群算法的三维路径规划  

Three-Dimensional Path Planning Based on Improved PSO Algorithm

作　　者：付兴武[1] 胡洋[1] FU Xingwu;HU Yang(Institute of Electrical and Control Engineering Liaoning Technical University,Huludao 125105 China)

机构地区：[1]辽宁工程技术大学电气与控制学院,辽宁葫芦岛125105

出　　处：《电光与控制》2021年第3期86-89,共4页Electronics Optics & Control

摘　　要：路径规划是无人机任务目标的重要组成部分,针对粒子群(PSO)算法早期收敛速度快,后期易陷入局部最优的缺点,提出一种结合天牛须搜索(BAS)算法的改进粒子群算法,并将其应用于无人机三维空间路径规划。在改进的粒子群算法中,利用天牛个体的优势,在每次迭代中都有自己对环境空间的判断,使路径更加合理,搜索效率更高。仿真结果表明,与粒子群算法相比,使用改进的粒子群算法进行无人机三维路径规划效果更好、代价更小。Path planning is an important part of the objective of UAV task.Considering that the Particle Swarm Optimization(PSO)algorithm is fast in convergence in the early stage and easy to fall into local optimum in the later stage an improved PSO combined with the Beetle Antennae Search algorithm is proposed which is applied to three-dimensional path planning of UAVs.In the improved PSO algorithm by using the advantage of the individual beetle which has its own judgment on the environment space in each iteration the path is more reasonable and the search efficiency is higher.The simulation results show that:Compared with PSO the three-dimensional path planning of UAV based on improved PSO is more effective with less cost.

关 键 词：无人机 路径规划 粒子群算法 天牛须搜索算法 

分 类 号：TM391[电气工程—电机]