信息与控制2023，Vol.52Issue(6)：689-700,12.DOI:10.13976/j.cnki.xk.2023.2319
基于改进黑猩猩优化算法的仓储移动机器人路径规划
Path Planning of Storage Mobile Robot Based on Improved Chimp Optimization Algorithm
摘要
Abstract
In this study,an improved chimp optimization algorithm is proposed to facilitate the path planning of mobile robots in an intelligent storage environment.For this,the algorithm initializes the population by neighborhood search,improving the quality of the population.Consequently,the algorithm improves the adaptive convergence process via the cosine convergence factor and also im-proves the diversity of the population and global search ability.A distance heuristic factor is intro-duced to classify and weigh the population so as to avoid the local optimal problem caused by late search chaos.The introduction of this factor improves the local search and exploration ability of the algorithm.By using traveling salesman problem library(TSPLIB)standard example database,the improved algorithm is compared with several intelligent algorithms,such as the standard chimp optimization algorithm.Our experimental results show that the improved algorithm has better ro-bustness,convergence precision,and optimization speed in comparison with the other studied algo-rithms.Moreover,the improved algorithm has good applicability,can effectively optimize the path of the warehouse mobile robot,and improve the working efficiency.关键词
移动机器人/路径规划/黑猩猩优化算法/智能仓储Key words
mobile robot/path planning/chimp optimization algorithm/intelligent storage分类
信息技术与安全科学引用本文复制引用
刘海龙,雷斌,王菀莹,云雁,柴获..基于改进黑猩猩优化算法的仓储移动机器人路径规划[J].信息与控制,2023,52(6):689-700,12.基金项目
国家自然科学基金(71961015) （71961015）
教育部产学合作协同育人项目(202102310002) （202102310002）
甘肃省优秀研究生"创新之星"项目(2022CXZX-566) （2022CXZX-566）
