{"title":"Transformation Between Simple and Detailed Maps Based on Line Matching for Robot Navigation","authors":"Ryo Toshimitsu, Y. Fujimoto","doi":"10.1109/INDIN41052.2019.8972191","DOIUrl":null,"url":null,"abstract":"Most autonomous mobile systems require pre- generated detailed maps that are expensive to prepare. In this study, we proposed an autonomous mobile system that does not rely on a detailed map; instead, it uses a simple map for robot navigation. The robot has two maps; one is a detailed map created by sensor observation during movement, and the other is a simple map provided as pre-information. The robot performs the matching between detailed and simple maps and converts waypoints on the simple map to waypoints on the detailed map. Matching is performed based on straight line matching and is optimized by genetic algorithm. Experiments were conducted in buildings. Our method is compared with linear transformations and conditions that our method works effectively or not are confirmed.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDIN41052.2019.8972191","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Most autonomous mobile systems require pre- generated detailed maps that are expensive to prepare. In this study, we proposed an autonomous mobile system that does not rely on a detailed map; instead, it uses a simple map for robot navigation. The robot has two maps; one is a detailed map created by sensor observation during movement, and the other is a simple map provided as pre-information. The robot performs the matching between detailed and simple maps and converts waypoints on the simple map to waypoints on the detailed map. Matching is performed based on straight line matching and is optimized by genetic algorithm. Experiments were conducted in buildings. Our method is compared with linear transformations and conditions that our method works effectively or not are confirmed.