改进灰狼算法的无人机路径规划  

Path Planning of UAV Based on Improved Grey Wolf Optimizer Algorithm

作　　者：刘云平[1] 朱慧如 方卫华[2] LIU Yunping;ZHU Huiru;FANG Weihua(Nanjing University of Information Science&Technology,Nanjing 210000,China;Nanjing Automation Institute of Water Conservancy and Hydrology Ministry of Water Resources,Nanjing 210000,China)

机构地区：[1]南京信息工程大学,南京210000 [2]水利部南京水利水文自动化研究所,南京210000

出　　处：《电光与控制》2023年第7期1-7,共7页Electronics Optics & Control

基　　金：国家自然科学基金(51875293);江苏省水利科技项目(2021073)。

摘　　要：针对灰狼算法易陷入局部最优导致路径寻优精度低的问题,提出一种用于静态二维无人机路径规划研究的改进灰狼算法。首先,提出一种控制参数非线性调整策略,平衡算法的全局搜索与局部搜索;同时,将灰狼算法与Powell算法结合,提高算法寻优效果及路径规划精度;最后,通过测试与仿真说明改进后的灰狼算法具有更好的寻优精度和路径规划效果。Aiming at the problem that the grey wolf algorithm is easy to fall into the local optimum,which leads to the low precision of path optimization,an improved grey wolf algorithm is proposed and applied to the static 2D UAV path planning research.Firstly,a nonlinear adjustment strategy of control parameters is introduced to balance the global search and local search of the algorithm.At the same time,the grey wolf algorithm is combined with Powell algorithm to improve the optimization effect and path planning accuracy.Finally,the test and simulation show the optimization accuracy and path planning effect of the improved grey wolf algorithm.

关 键 词：路径规划 灰狼算法 POWELL算法 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]