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 |
| Event | International Conference on Control, Automation and Systems, ICCAS 2010 - Gyeonggi-do, Korea, Republic of Duration: 2010 Oct 27 → 2010 Oct 30 |
Publication series
| Name | ICCAS 2010 - International Conference on Control, Automation and Systems |
|---|
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 |
Keywords
- Exploration
- Mobile robot
- SLAM
- Visual feature
ASJC Scopus subject areas
- Artificial Intelligence
- Control and Systems Engineering
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Cite this
Park, J. T., & Song, J. B. (2010). Low-cost sensor-based exploration in home environments with salient visual features. In ICCAS 2010 - International Conference on Control, Automation and Systems (pp. 2218-2222). [5669849] (ICCAS 2010 - International Conference on Control, Automation and Systems).