基于ROS的移动工业机器人定位算法研究  

Research on Positioning Algorithm of Mobile Industrial Robot Based on ROS

作　　者：邢凯盛 王伟 伍永健 XING Kaisheng;WANG Wei;WU Yongjian(School of Electrical and Electronic Engineering,Anhui Institute of Information Technology,241199,Wuhu,Anhui,China;School of Electrical Engineering,Anhui Technical College of Mechanical and Electrical Engineering,241002,Wuhu,Anhui,China)

机构地区：[1]安徽信息工程学院电气与电子工程学院,安徽芜湖241199 [2]安徽机电职业技术学院电气工程学院,安徽芜湖241002

出　　处：《淮北师范大学学报（自然科学版）》2024年第2期49-55,共7页Journal of Huaibei Normal University：Natural Sciences

基　　金：安徽省教育厅高校科学研究项目(2022AH051886,2023AH052694)。

摘　　要：室内移动工业机器人在工业生产、智慧物流等领域的应用越来越广泛,其导航定位成为学者研究的热点问题,具有较高的应用价值。为解决蒙特卡罗定位(MCL)算法粒子匮乏、定位精度不高等问题,将基于自适应蒙特卡罗定位(AMCL)算法应用到移动工业机器人定位系统中,通过在MCL重采样中引入随机采样和尔贝克-莱布勒散度(KLD)采样自适应动态调节粒子数量,实现较好的定位效果,同时搭建基于机器人操作系统(ROS)的实验平台进行定位实验。经实验,AMCL定位算法在ROS平台下能够较好地实现移动工业机器人的定位功能。The application of indoor mobile industrial robots in industrial production,intelligent logistics and other fields is becoming increasingly widespread,and their navigation and positioning with its high applica⁃tion value have become a hot topic of research for scholars.In order to solve the problems of particle scarcity and low positioning accuracy in Monte Carlo localization(MCL)algorithm,the adaptive Monte Carlo localiza⁃tion(AMCL)algorithm is applied to the positioning system of mobile industrial robots.By introducing ran⁃dom sampling and KLD sampling in MCL resampling,the number of particles is adaptively dynamically ad⁃justed to achieve good positioning results.At the same time,an experimental platform based on robot operat⁃ing system(ROS)is built for positioning experiments.Through experiments,the AMCL positioning algorithm can effectively achieve the positioning function of mobile industrial robots on the ROS platform。

关 键 词：室内移动工业机器人 定位 自适应蒙特卡罗定位(AMCL) 机器人操作系统(ROS) 

分 类 号：TP242.2[自动化与计算机技术—检测技术与自动化装置]