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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Heon-Cheol Lee Seung-Hee Lee Jimin Kim Beom-Hee Lee |
| Copyright Year | 2011 |
| Description | Author affiliation: School of Electrical Engineering and Computer Science, Seoul National University, South Korea (Heon-Cheol Lee; Seung-Hee Lee; Jimin Kim) || Faculty of the School of Electrical Engineering and Computer Science, Seoul National University, South Korea (Beom-Hee Lee) |
| Abstract | This paper presents a novel scan matching algorithm which uses not whole scan region but only salient scan region selected around curvature-based features. A curvature function computed by the relative coordinates of neighbor scan points is used to extract salient features which are invariant to translation and rotation. Because the scan matching regions are selected around the salient features, the presented algorithm can be robustly performed even in noisy environments. The robustness of the presented algorithm was tested by datasets obtained from various noisy environments and was verified by consistently showing smaller errors than other scan matching algorithms. Moreover, the presented algorithm was successfully applied to SLAM. |
| Starting Page | 1257 |
| Ending Page | 1262 |
| File Size | 684564 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781457715235 |
| e-ISBN | 9781457715242 |
| DOI | 10.1109/SII.2011.6147629 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-12-20 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Real time systems Simultaneous localization and mapping Iterative closest point algorithm Feature extraction Robustness Noise measurement |
| Content Type | Text |
| Resource Type | Article |
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