Abstract
SLAM is very important in autonomous navigation of a mobile robot. Mapping is the task of modeling the robot's environment and localization is the process of determining its position and orientation with respect to the global map. For successful SLAM performance, landmarks for pose estimation should be continuously observed. In this paper, autonomous recognition and registration of objects as visual landmarks is proposed for autonomous visual SLAM. SIFT and the contour detection algorithms are adopted to distinguish the objects from the background. Autonomous object recognition can enable the robot to recognize some objects without giving any object information to the robot and it can help the vision system to cope with unknown environments. Furthermore, by using object information, a small number of landmarks can be used in the same area compared to other visual SLAM schemes using corners and lines or scene recognition. Various experiments show that the proposed visual SLAM can improve autonomous navigation of a mobile robot.
| Original language | English |
|---|---|
| Title of host publication | ICCAS 2007 - International Conference on Control, Automation and Systems |
| Pages | 668-673 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2007 Dec 1 |
| Event | International Conference on Control, Automation and Systems, ICCAS 2007 - Seoul, Korea, Republic of Duration: 2007 Oct 17 → 2007 Oct 20 |
Other
| Other | International Conference on Control, Automation and Systems, ICCAS 2007 |
|---|---|
| Country | Korea, Republic of |
| City | Seoul |
| Period | 07/10/17 → 07/10/20 |
Fingerprint
Keywords
- Appearance based recognition
- Object recognition
- SIFT
- SLAM
ASJC Scopus subject areas
- Control and Systems Engineering
- Electrical and Electronic Engineering
Cite this
Autonomous selection, registration, and recognition of objects for visual SLAM in indoor environments. / Lee, Yong Ju; Song, Jae-Bok.
ICCAS 2007 - International Conference on Control, Automation and Systems. 2007. p. 668-673 4406983.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Autonomous selection, registration, and recognition of objects for visual SLAM in indoor environments
AU - Lee, Yong Ju
AU - Song, Jae-Bok
PY - 2007/12/1
Y1 - 2007/12/1
N2 - SLAM is very important in autonomous navigation of a mobile robot. Mapping is the task of modeling the robot's environment and localization is the process of determining its position and orientation with respect to the global map. For successful SLAM performance, landmarks for pose estimation should be continuously observed. In this paper, autonomous recognition and registration of objects as visual landmarks is proposed for autonomous visual SLAM. SIFT and the contour detection algorithms are adopted to distinguish the objects from the background. Autonomous object recognition can enable the robot to recognize some objects without giving any object information to the robot and it can help the vision system to cope with unknown environments. Furthermore, by using object information, a small number of landmarks can be used in the same area compared to other visual SLAM schemes using corners and lines or scene recognition. Various experiments show that the proposed visual SLAM can improve autonomous navigation of a mobile robot.
AB - SLAM is very important in autonomous navigation of a mobile robot. Mapping is the task of modeling the robot's environment and localization is the process of determining its position and orientation with respect to the global map. For successful SLAM performance, landmarks for pose estimation should be continuously observed. In this paper, autonomous recognition and registration of objects as visual landmarks is proposed for autonomous visual SLAM. SIFT and the contour detection algorithms are adopted to distinguish the objects from the background. Autonomous object recognition can enable the robot to recognize some objects without giving any object information to the robot and it can help the vision system to cope with unknown environments. Furthermore, by using object information, a small number of landmarks can be used in the same area compared to other visual SLAM schemes using corners and lines or scene recognition. Various experiments show that the proposed visual SLAM can improve autonomous navigation of a mobile robot.
KW - Appearance based recognition
KW - Object recognition
KW - SIFT
KW - SLAM
UR - http://www.scopus.com/inward/record.url?scp=48349143627&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=48349143627&partnerID=8YFLogxK
U2 - 10.1109/ICCAS.2007.4406983
DO - 10.1109/ICCAS.2007.4406983
M3 - Conference contribution
AN - SCOPUS:48349143627
SN - 8995003871
SN - 9788995003879
SP - 668
EP - 673
BT - ICCAS 2007 - International Conference on Control, Automation and Systems
ER -