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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - IEEE International Conference on Robotics and Automation |
| Pages | 3785-3790 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2013 Nov 14 |
| Event | 2013 IEEE International Conference on Robotics and Automation, ICRA 2013 - Karlsruhe, Germany Duration: 2013 May 6 → 2013 May 10 |
Other
| Other | 2013 IEEE International Conference on Robotics and Automation, ICRA 2013 |
|---|---|
| Country | Germany |
| City | Karlsruhe |
| Period | 13/5/6 → 13/5/10 |
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ASJC Scopus subject areas
- Software
- Artificial Intelligence
- Control and Systems Engineering
- Electrical and Electronic Engineering
Cite this
Monocular vision-based global localization using position and orientation of ceiling features. / Hwang, Seo Yeon; Song, Jae-Bok.
Proceedings - IEEE International Conference on Robotics and Automation. 2013. p. 3785-3790 6631109.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Monocular vision-based global localization using position and orientation of ceiling features
AU - Hwang, Seo Yeon
AU - Song, Jae-Bok
PY - 2013/11/14
Y1 - 2013/11/14
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84887273415&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84887273415&partnerID=8YFLogxK
U2 - 10.1109/ICRA.2013.6631109
DO - 10.1109/ICRA.2013.6631109
M3 - Conference contribution
AN - SCOPUS:84887273415
SN - 9781467356411
SP - 3785
EP - 3790
BT - Proceedings - IEEE International Conference on Robotics and Automation
ER -