Abstract
This paper describes an exploration method based on sonar sensors and a stereo camera. To build an accurate map in unknown environments during exploration, SLAM (Simultaneous Localization and Mapping) problem should be solved. Therefore, a salient visual feature (SVF) extraction method is proposed for SLAM. The key concept of SVF extraction method is to extract meaningful features of environments using SIFT keypoints. The extracted SVFs are applied to the EKF (Extended Kalman Filter)-based SLAM framework. This proposed method was verified by various experiments which show that the robot could build an accurate map autonomously with sonar sensors and a stereo camera in various home environments.
| Original language | English |
|---|---|
| Title of host publication | ICCAS 2010 - International Conference on Control, Automation and Systems |
| Pages | 2218-2222 |
| Number of pages | 5 |
| Publication status | Published - 2010 Dec 1 |
| Event | International Conference on Control, Automation and Systems, ICCAS 2010 - Gyeonggi-do, Korea, Republic of Duration: 2010 Oct 27 → 2010 Oct 30 |
Other
| Other | International Conference on Control, Automation and Systems, ICCAS 2010 |
|---|---|
| Country | Korea, Republic of |
| City | Gyeonggi-do |
| Period | 10/10/27 → 10/10/30 |
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Keywords
- Exploration
- Mobile robot
- SLAM
- Visual feature
ASJC Scopus subject areas
- Artificial Intelligence
- Control and Systems Engineering
Cite this
Low-cost sensor-based exploration in home environments with salient visual features. / Park, Joong Tae; Song, Jae-Bok.
ICCAS 2010 - International Conference on Control, Automation and Systems. 2010. p. 2218-2222 5669849.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Low-cost sensor-based exploration in home environments with salient visual features
AU - Park, Joong Tae
AU - Song, Jae-Bok
PY - 2010/12/1
Y1 - 2010/12/1
N2 - This paper describes an exploration method based on sonar sensors and a stereo camera. To build an accurate map in unknown environments during exploration, SLAM (Simultaneous Localization and Mapping) problem should be solved. Therefore, a salient visual feature (SVF) extraction method is proposed for SLAM. The key concept of SVF extraction method is to extract meaningful features of environments using SIFT keypoints. The extracted SVFs are applied to the EKF (Extended Kalman Filter)-based SLAM framework. This proposed method was verified by various experiments which show that the robot could build an accurate map autonomously with sonar sensors and a stereo camera in various home environments.
AB - This paper describes an exploration method based on sonar sensors and a stereo camera. To build an accurate map in unknown environments during exploration, SLAM (Simultaneous Localization and Mapping) problem should be solved. Therefore, a salient visual feature (SVF) extraction method is proposed for SLAM. The key concept of SVF extraction method is to extract meaningful features of environments using SIFT keypoints. The extracted SVFs are applied to the EKF (Extended Kalman Filter)-based SLAM framework. This proposed method was verified by various experiments which show that the robot could build an accurate map autonomously with sonar sensors and a stereo camera in various home environments.
KW - Exploration
KW - Mobile robot
KW - SLAM
KW - Visual feature
UR - http://www.scopus.com/inward/record.url?scp=78751496309&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78751496309&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:78751496309
SN - 9781424474530
SP - 2218
EP - 2222
BT - ICCAS 2010 - International Conference on Control, Automation and Systems
ER -