Abstract
This paper proposes a novel scheme of extracting the features in the ceiling using an upwardlooking camera for SLAM in indoor environments. The conventional approaches based on corner or line features have difficulties in associating adjacent indistinguishable features since their descriptors do not have enough information to distinguish them. Therefore, we used various properties of the objects in the ceiling, such as the distribution of nodes, and size and orientation strength of the region of interest. Also, the similarities among adjacent features are calculated to distinguish between unique and non-unique features. The non-unique features are discarded before they are registered to the feature map. The robustness of the proposed scheme is verified by several experiments using a mobile robot. The extended Kalman filter is used to estimate both robot pose and feature position and orientation, and the experimental results show that the proposed scheme successfully works in various indoor environments.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 18th IFAC World Congress |
| Publisher | IFAC Secretariat |
| Pages | 8165-8170 |
| Number of pages | 6 |
| Edition | 1 PART 1 |
| ISBN (Print) | 9783902661937 |
| DOIs | |
| Publication status | Published - 2011 |
Publication series
| Name | IFAC Proceedings Volumes (IFAC-PapersOnline) |
|---|---|
| Number | 1 PART 1 |
| Volume | 44 |
| ISSN (Print) | 1474-6670 |
Bibliographical note
Funding Information:This research was performed for the Intelligent Robotics Development Program, one of the 21st Century Frontier R&D Programs funded by the Ministry of Knowledge Economy of Korea.
Keywords
- Feature extraction
- Mobile robots
- Monocular vision-based SLAM
- Upward-looking camera
ASJC Scopus subject areas
- Control and Systems Engineering