A Light-and-Fast SLAM Algorithm for Robots in Indoor Environments Using Line Segment Map
Simultaneous Localization and Mapping (SLAM) is an important technique for robotic system navigation. Due to the high complexity of the algorithm, SLAM usually needs long computational time or large amount of memory to achieve accurate results. In this paper, we present a lightweight Rao-Blackwelliz...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2011-01-01
|
| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2011/257852 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832558420368031744 |
|---|---|
| author | Bor-Woei Kuo Hsun-Hao Chang Yung-Chang Chen Shi-Yu Huang |
| author_facet | Bor-Woei Kuo Hsun-Hao Chang Yung-Chang Chen Shi-Yu Huang |
| author_sort | Bor-Woei Kuo |
| collection | DOAJ |
| description | Simultaneous Localization and Mapping (SLAM) is an important technique for robotic system navigation. Due to the high complexity of the algorithm, SLAM usually needs long computational time or large amount of memory to achieve accurate results. In this paper, we present a lightweight Rao-Blackwellized particle filter- (RBPF-) based SLAM algorithm for indoor environments, which uses line segments extracted from the laser range finder as the fundamental map structure so as to reduce the memory usage. Since most major structures of indoor environments are usually orthogonal to each other, we can also efficiently increase the accuracy and reduce the complexity of our algorithm by exploiting this orthogonal property of line segments, that is, we treat line segments that are parallel or perpendicular to each other in a special way when calculating the importance weight of each particle. Experimental results shows that our work is capable of drawing maps in complex indoor environments, needing only very low amount of memory and much less computational time as compared to other grid map-based RBPF SLAM algorithms. |
| format | Article |
| id | doaj-art-e9c610e3124b4e1bb79572cc32654788 |
| institution | Kabale University |
| issn | 1687-9600 1687-9619 |
| language | English |
| publishDate | 2011-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-e9c610e3124b4e1bb79572cc326547882025-02-03T01:32:25ZengWileyJournal of Robotics1687-96001687-96192011-01-01201110.1155/2011/257852257852A Light-and-Fast SLAM Algorithm for Robots in Indoor Environments Using Line Segment MapBor-Woei Kuo0Hsun-Hao Chang1Yung-Chang Chen2Shi-Yu Huang3Department of Electrical Engineering, National Tsing-Hua University 101, Section 2, Kuang-Fu Road, Hsinchu 30013, TaiwanDepartment of Electrical Engineering, National Tsing-Hua University 101, Section 2, Kuang-Fu Road, Hsinchu 30013, TaiwanDepartment of Electrical Engineering, National Tsing-Hua University 720R, EECS Bldg, 101, Section 2, Kuang-Fu Road, Hsinchu 30013, TaiwanDepartment of Electrical Engineering, National Tsing-Hua University 818, EECS Bldg, 101, Section 2, Kuang-Fu Road, Hsinchu 30013, TaiwanSimultaneous Localization and Mapping (SLAM) is an important technique for robotic system navigation. Due to the high complexity of the algorithm, SLAM usually needs long computational time or large amount of memory to achieve accurate results. In this paper, we present a lightweight Rao-Blackwellized particle filter- (RBPF-) based SLAM algorithm for indoor environments, which uses line segments extracted from the laser range finder as the fundamental map structure so as to reduce the memory usage. Since most major structures of indoor environments are usually orthogonal to each other, we can also efficiently increase the accuracy and reduce the complexity of our algorithm by exploiting this orthogonal property of line segments, that is, we treat line segments that are parallel or perpendicular to each other in a special way when calculating the importance weight of each particle. Experimental results shows that our work is capable of drawing maps in complex indoor environments, needing only very low amount of memory and much less computational time as compared to other grid map-based RBPF SLAM algorithms.http://dx.doi.org/10.1155/2011/257852 |
| spellingShingle | Bor-Woei Kuo Hsun-Hao Chang Yung-Chang Chen Shi-Yu Huang A Light-and-Fast SLAM Algorithm for Robots in Indoor Environments Using Line Segment Map Journal of Robotics |
| title | A Light-and-Fast SLAM Algorithm for Robots in Indoor Environments Using Line Segment Map |
| title_full | A Light-and-Fast SLAM Algorithm for Robots in Indoor Environments Using Line Segment Map |
| title_fullStr | A Light-and-Fast SLAM Algorithm for Robots in Indoor Environments Using Line Segment Map |
| title_full_unstemmed | A Light-and-Fast SLAM Algorithm for Robots in Indoor Environments Using Line Segment Map |
| title_short | A Light-and-Fast SLAM Algorithm for Robots in Indoor Environments Using Line Segment Map |
| title_sort | light and fast slam algorithm for robots in indoor environments using line segment map |
| url | http://dx.doi.org/10.1155/2011/257852 |
| work_keys_str_mv | AT borwoeikuo alightandfastslamalgorithmforrobotsinindoorenvironmentsusinglinesegmentmap AT hsunhaochang alightandfastslamalgorithmforrobotsinindoorenvironmentsusinglinesegmentmap AT yungchangchen alightandfastslamalgorithmforrobotsinindoorenvironmentsusinglinesegmentmap AT shiyuhuang alightandfastslamalgorithmforrobotsinindoorenvironmentsusinglinesegmentmap AT borwoeikuo lightandfastslamalgorithmforrobotsinindoorenvironmentsusinglinesegmentmap AT hsunhaochang lightandfastslamalgorithmforrobotsinindoorenvironmentsusinglinesegmentmap AT yungchangchen lightandfastslamalgorithmforrobotsinindoorenvironmentsusinglinesegmentmap AT shiyuhuang lightandfastslamalgorithmforrobotsinindoorenvironmentsusinglinesegmentmap |