基于改进灰狼算法的数控车间AGV路径规划研究  

Research on AGV Path Planning of NC Workshop Based on Improved Grey Wolf Algorithm

作　　者：李泓坤 Li Hongkun(Xi’an University of Technology,Xi’an Shaanxi,710021)

机构地区：[1]西安工业大学,陕西西安710021

出　　处：《电子测试》2022年第22期59-61,共3页Electronic Test

摘　　要：针对数控车间环境中的AGV路径规划的问题,本文提出一种基于Skew Tent混沌映射初始化种群的改进灰狼(IGWO)算法,并将其运用于数控车间AGV全局路径规划问题。并且基于仿真软件,根据实际车间环境,建立栅格地图进行仿真模拟;在相同条件下传统GWO算法和IGWO算法进行仿真测试,对两种算法的路径规划时间和所规划路径的优劣进行了评估。仿真模拟结果表明改进后的灰狼算法具有明显的优势。Aiming at the problem of AGV path planning in NC workshop environment, this paper proposes an improved gray wolf(IGWO) algorithm based on Skew Tent chaotic map initialization population, and applies it to the problem of AGV global path planning in NC workshop. Based on the simulation software, according to the actual workshop environment, establish grid map for simulation;Under the same conditions, the GA algorithm, SA algorithm, PSO algorithm, traditional GWO algorithm and IGWO algorithm are simulated and tested, and the path planning time of the five algorithms and the advantages and disadvantages of the planned path are evaluated. The simulation results show that the improved gray wolf algorithm has obvious advantages.

关 键 词：数控车间 AGV 路径规划 灰狼算法 Skew Tent混沌映射 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]