计算机与现代化Issue(5)：11-15,21,6.DOI:10.3969/j.issn.1006-2475.2024.05.003
基于改进蜉蝣优化算法的机器人磁定位方法
Parking Positioning Method for Automatic Guided Vehicle Based on MA-LM Algorithm
摘要
Abstract
To address the challenge that autonomous navigation parking and charging solutions have poor positioning accuracy at long distances,resulting in AGVs not being able to align with the charging pile in automatic charging back mode,a parking posi-tioning method based on an improved mayfly optimization algorithm(MA-LM)is proposed.This method fuses the magnetic nail positioning data from multiple magnetic sensor arrays,thereby improving the position accuracy and attitude accuracy of the park-ing positioning.To quantitatively evaluate the improvement effect of magnetic nail localization,this method is tested in a charg-ing pile scenario using a sensor array of nine magnetic sensors and a two-wheeled differential speed mobile robot.Compared with the genetic optimization algorithm(GA-LM)and the particle swarm optimization algorithm(PSO-LM),the experimental results show that the MA-LM algorithm has the localization accuracy of±1.65 mm and the orientation accuracy of 0.9°in the parking lo-calization.关键词
物流机器人/蜉蝣优化算法/磁钉导航/停车定位/充电桩导航Key words
automatic guided vehicle/mayfly algorithm/magnetic nail navigation/parking positioning/charging station navigation分类
信息技术与安全科学引用本文复制引用
张源超,杨贵志,薛广,姚瀚晨,彭建伟,戴厚德..基于改进蜉蝣优化算法的机器人磁定位方法[J].计算机与现代化,2024,(5):11-15,21,6.基金项目
福建省中青年教师教育科研项目(JAT200487) （JAT200487）
中央引导地方科技发展专项资金资助项目(2021L3047) （2021L3047）
