Proposal for Navigation System Using Three-Dimensional Maps—Self-Localization Using a 3D Map and Slope Detection Using a 2D Laser Range Finder and 3D Map
Neng Chen, S. Suga, Masato Suzuki, Tomokazu Takahashi, Yasushi Mae, Yasuhiko Arai, S. Aoyagi
{"title":"Proposal for Navigation System Using Three-Dimensional Maps—Self-Localization Using a 3D Map and Slope Detection Using a 2D Laser Range Finder and 3D Map","authors":"Neng Chen, S. Suga, Masato Suzuki, Tomokazu Takahashi, Yasushi Mae, Yasuhiko Arai, S. Aoyagi","doi":"10.20965/jrm.2023.p1604","DOIUrl":null,"url":null,"abstract":"Many teams participating in robotic competitions achieve localization using a 2D map plotted using adaptive Monte Carlo localization, a robot operating system (ROS) open-source software program. However, outdoor environments often include nonlevel terrain such as slopes. In the indoor environment of multilevel structures, the data representing different levels overlap on the map. These factors can lead to localization failures. To resolve this problem, we develop a software by combining HDL localization, which is an ROS open-source software, with our own program, and use it to achieve localization based on a 3D map. Furthermore, the authors observe the erroneous recognition of a slope as a forward obstacle during a competition event. To resolve this, we propose a method to correct erroneous recognition of obstacles using a 2D laser range finder and 3D map and confirm its validity in an experiment carried out on a slope on a university campus.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20965/jrm.2023.p1604","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
Many teams participating in robotic competitions achieve localization using a 2D map plotted using adaptive Monte Carlo localization, a robot operating system (ROS) open-source software program. However, outdoor environments often include nonlevel terrain such as slopes. In the indoor environment of multilevel structures, the data representing different levels overlap on the map. These factors can lead to localization failures. To resolve this problem, we develop a software by combining HDL localization, which is an ROS open-source software, with our own program, and use it to achieve localization based on a 3D map. Furthermore, the authors observe the erroneous recognition of a slope as a forward obstacle during a competition event. To resolve this, we propose a method to correct erroneous recognition of obstacles using a 2D laser range finder and 3D map and confirm its validity in an experiment carried out on a slope on a university campus.