Localization and Mapping for UGV in Dynamic Scenes with Dynamic Objects Eliminated
SLAM (Simultaneous Localization and Mapping) based on lidar is an important method for UGV (Unmanned Ground Vehicle) localization in real time under GNSS (Global Navigation Satellite System)-denied situations. However, dynamic objects in real-world scenarios affect odometry in SLAM and reduce locali...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Machines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1702/10/11/1044 |
| _version_ | 1797467511348789248 |
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| author | Junsong Li Jilin He |
| author_facet | Junsong Li Jilin He |
| author_sort | Junsong Li |
| collection | DOAJ |
| description | SLAM (Simultaneous Localization and Mapping) based on lidar is an important method for UGV (Unmanned Ground Vehicle) localization in real time under GNSS (Global Navigation Satellite System)-denied situations. However, dynamic objects in real-world scenarios affect odometry in SLAM and reduce localization accuracy. We propose a novel lidar SLAM algorithm based on LOAM (Lidar Odometry and Mapping), which is popular in this field. First, we applied elevation maps to label the ground point cloud. Then we extracted convex hulls in point clouds based on scanlines as materials for dynamic object clustering. We replaced these dynamic objects with background point cloud to avoid accuracy reduction. Finally, we extracted feature points from ground points and non-ground points, respectively, and matched these feature points frame-to-frame to estimate ground robot motion. We evaluated the proposed algorithm in dynamic industrial park roads, and it kept UGV maximum relative position error less than 3% and average relative position error less than 2%. |
| first_indexed | 2024-03-09T18:54:43Z |
| format | Article |
| id | doaj.art-53e97afbe8d64e0d8959c6aa9fd164df |
| institution | Directory Open Access Journal |
| issn | 2075-1702 |
| language | English |
| last_indexed | 2024-03-09T18:54:43Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj.art-53e97afbe8d64e0d8959c6aa9fd164df2023-11-24T05:33:25ZengMDPI AGMachines2075-17022022-11-011011104410.3390/machines10111044Localization and Mapping for UGV in Dynamic Scenes with Dynamic Objects EliminatedJunsong Li0Jilin He1State Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha 410083, ChinaState Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha 410083, ChinaSLAM (Simultaneous Localization and Mapping) based on lidar is an important method for UGV (Unmanned Ground Vehicle) localization in real time under GNSS (Global Navigation Satellite System)-denied situations. However, dynamic objects in real-world scenarios affect odometry in SLAM and reduce localization accuracy. We propose a novel lidar SLAM algorithm based on LOAM (Lidar Odometry and Mapping), which is popular in this field. First, we applied elevation maps to label the ground point cloud. Then we extracted convex hulls in point clouds based on scanlines as materials for dynamic object clustering. We replaced these dynamic objects with background point cloud to avoid accuracy reduction. Finally, we extracted feature points from ground points and non-ground points, respectively, and matched these feature points frame-to-frame to estimate ground robot motion. We evaluated the proposed algorithm in dynamic industrial park roads, and it kept UGV maximum relative position error less than 3% and average relative position error less than 2%.https://www.mdpi.com/2075-1702/10/11/1044SLAMdynamic scenelidarodometry |
| spellingShingle | Junsong Li Jilin He Localization and Mapping for UGV in Dynamic Scenes with Dynamic Objects Eliminated Machines SLAM dynamic scene lidar odometry |
| title | Localization and Mapping for UGV in Dynamic Scenes with Dynamic Objects Eliminated |
| title_full | Localization and Mapping for UGV in Dynamic Scenes with Dynamic Objects Eliminated |
| title_fullStr | Localization and Mapping for UGV in Dynamic Scenes with Dynamic Objects Eliminated |
| title_full_unstemmed | Localization and Mapping for UGV in Dynamic Scenes with Dynamic Objects Eliminated |
| title_short | Localization and Mapping for UGV in Dynamic Scenes with Dynamic Objects Eliminated |
| title_sort | localization and mapping for ugv in dynamic scenes with dynamic objects eliminated |
| topic | SLAM dynamic scene lidar odometry |
| url | https://www.mdpi.com/2075-1702/10/11/1044 |
| work_keys_str_mv | AT junsongli localizationandmappingforugvindynamicsceneswithdynamicobjectseliminated AT jilinhe localizationandmappingforugvindynamicsceneswithdynamicobjectseliminated |