{"title":"An implementation of SLAM using ROS and Arduino","authors":"A. Ibanez, Renxi Qiu, Dayou Li","doi":"10.1109/3M-NANO.2017.8286298","DOIUrl":null,"url":null,"abstract":"This paper aims to explore the Simultaneous Localization and Mapping (SLAM) problem in the context of implementation using the Robot Operating System (ROS) framework and the Arduino technology. The implementation of an inexpensive differential drive robot for SLAM is detailed and verified by mapping experiments conducted within domestic environments. Furthermore, a modest, yet convenient, theoretical explanation of the algorithm (Rao-Blackwellization particle filter) behind the platform is also presented. Overall, this report leads to a simple and cost effective way — including a code base and guidelines — to create robots for 2D mapping using modern technologies such as ROS.","PeriodicalId":6582,"journal":{"name":"2017 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO)","volume":"12 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/3M-NANO.2017.8286298","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
This paper aims to explore the Simultaneous Localization and Mapping (SLAM) problem in the context of implementation using the Robot Operating System (ROS) framework and the Arduino technology. The implementation of an inexpensive differential drive robot for SLAM is detailed and verified by mapping experiments conducted within domestic environments. Furthermore, a modest, yet convenient, theoretical explanation of the algorithm (Rao-Blackwellization particle filter) behind the platform is also presented. Overall, this report leads to a simple and cost effective way — including a code base and guidelines — to create robots for 2D mapping using modern technologies such as ROS.