{"title":"3D Point Clouds Segmentation for Autonomous Ground Vehicle","authors":"Danilo Habermann, A. Hata, D. Wolf, F. Osório","doi":"10.1109/SBESC.2013.43","DOIUrl":null,"url":null,"abstract":"Point clouds segmentation is an essential step to improve the performance of obstacle detection and classification in areas of autonomous ground vehicles and mobile robotics. This paper presents a study and comparison of the performance of segmentation methods using point clouds coming from a 3D laser sensor, more specifically obtained from a Velodyne HDL32.","PeriodicalId":359419,"journal":{"name":"2013 III Brazilian Symposium on Computing Systems Engineering","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 III Brazilian Symposium on Computing Systems Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SBESC.2013.43","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
Point clouds segmentation is an essential step to improve the performance of obstacle detection and classification in areas of autonomous ground vehicles and mobile robotics. This paper presents a study and comparison of the performance of segmentation methods using point clouds coming from a 3D laser sensor, more specifically obtained from a Velodyne HDL32.
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