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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Seo-Yeon Hwang Jae-Bok Song |
| Copyright Year | 2013 |
| Description | Author affiliation: Sch. of Mech. Eng., Korea Univ., Seoul, South Korea (Seo-Yeon Hwang; Jae-Bok Song) |
| Abstract | This study presents an upward-looking camera-based global localization scheme using the position and orientation of ceiling features. If the robot pose is unknown, the region-based ceiling features from the current image are matched to a pre-built feature map from the RBPF-based SLAM process. Then, the candidate areas of the real robot pose are set around the matched features. The candidates are represented by two spots for the features having both position and orientation, while by a circle if they have only position. Finally, the real robot pose is determined at the intersection point. The candidate areas are realistically modeled by applying the observation error, and useless candidates are significantly reduced by considering the feature orientation. Several experiments in real environments validated the effectiveness of the proposed global localization scheme. |
| Starting Page | 3785 |
| Ending Page | 3790 |
| File Size | 769981 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467356411 |
| ISSN | 10504729 |
| e-ISBN | 9781467356435 |
| DOI | 10.1109/ICRA.2013.6631109 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-05-06 |
| Publisher Place | Germany |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Feature extraction Simultaneous localization and mapping Robot kinematics Cameras Robot vision systems Educational institutions |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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