Satoshi Ito, R. Kaneko, Takumi Saito, Yuji Nakamura
{"title":"基于设计图纸和平板扫描数据的激光雷达定位地图制作","authors":"Satoshi Ito, R. Kaneko, Takumi Saito, Yuji Nakamura","doi":"10.20965/jrm.2023.p0470","DOIUrl":null,"url":null,"abstract":"This paper proposes a method for the point cloud data (PCD) map creation for the 3D LiDAR localization. The features of the method include the creation of a PCD map from a drawing of the buildings and partial scan of the not-existing object of the map by the tablet computer with the LiDAR. In the former, a map creation procedure, including the up- and down-sampling, as well as the processing, with voxel grid filter is established. In the latter, automatic position correction of the tablet scan data is introduced when they are placed to the current PCD map. Experiments are conducted to determine the size of the voxel grid filter and prove the effect of the tablet scan data in enhancing the matching level and the localization accuracy. Finally, the experiment with an autonomous mobile robot demonstrates that a map created using the proposed method is sufficient for autonomous driving without losing the localization.","PeriodicalId":178614,"journal":{"name":"J. Robotics Mechatronics","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Map Creation for LiDAR Localization Based on the Design Drawings and Tablet Scan Data\",\"authors\":\"Satoshi Ito, R. Kaneko, Takumi Saito, Yuji Nakamura\",\"doi\":\"10.20965/jrm.2023.p0470\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a method for the point cloud data (PCD) map creation for the 3D LiDAR localization. The features of the method include the creation of a PCD map from a drawing of the buildings and partial scan of the not-existing object of the map by the tablet computer with the LiDAR. In the former, a map creation procedure, including the up- and down-sampling, as well as the processing, with voxel grid filter is established. In the latter, automatic position correction of the tablet scan data is introduced when they are placed to the current PCD map. Experiments are conducted to determine the size of the voxel grid filter and prove the effect of the tablet scan data in enhancing the matching level and the localization accuracy. Finally, the experiment with an autonomous mobile robot demonstrates that a map created using the proposed method is sufficient for autonomous driving without losing the localization.\",\"PeriodicalId\":178614,\"journal\":{\"name\":\"J. Robotics Mechatronics\",\"volume\":\"63 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"J. Robotics Mechatronics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.20965/jrm.2023.p0470\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Robotics Mechatronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20965/jrm.2023.p0470","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Map Creation for LiDAR Localization Based on the Design Drawings and Tablet Scan Data
This paper proposes a method for the point cloud data (PCD) map creation for the 3D LiDAR localization. The features of the method include the creation of a PCD map from a drawing of the buildings and partial scan of the not-existing object of the map by the tablet computer with the LiDAR. In the former, a map creation procedure, including the up- and down-sampling, as well as the processing, with voxel grid filter is established. In the latter, automatic position correction of the tablet scan data is introduced when they are placed to the current PCD map. Experiments are conducted to determine the size of the voxel grid filter and prove the effect of the tablet scan data in enhancing the matching level and the localization accuracy. Finally, the experiment with an autonomous mobile robot demonstrates that a map created using the proposed method is sufficient for autonomous driving without losing the localization.