Abstract
Place recognition is widely used in the loop closure detection in SLAM. The current approach to place recognition is based on RGB images, but there are relatively few place recognition studies using a point cloud. This study presents the place recognition method based on the surface graph. The proposed method clusters the surfaces in the point cloud and recognizes a place through a surface descriptor and a surface graph. The advantage of this approach is that it uses the surfaces that are not low-level features such as SIFT and SURF. Another advantage is that the proposed place recognition is robust because of the surface graph. We have experimented on the data set obtained by the mobile robot equipped with a Kinect sensor in the indoor environment. The experimental results show that the proposed place recognition based on the surface graph (PRSG) scheme is useful and can be used as a loop closure detector.
| Original language | English |
|---|---|
| Title of host publication | 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 342-346 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781509030552 |
| DOIs | |
| Publication status | Published - 2017 Jul 25 |
| Event | 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017 - Jeju, Korea, Republic of Duration: 2017 Jun 28 → 2017 Jul 1 |
Other
| Other | 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017 |
|---|---|
| Country | Korea, Republic of |
| City | Jeju |
| Period | 17/6/28 → 17/7/1 |
Keywords
- Fast point feature histogram
- Place recognition
- Surface graph
ASJC Scopus subject areas
- Computer Science Applications
- Biomedical Engineering
- Artificial Intelligence
- Human-Computer Interaction
- Control and Optimization