SLAM for Hybrid Mapping
- Yong-Ju Lee (Ph.D. email@example.com)
- Research Background
- Indoor environments generally consist of visual features and range-based features. Therefore, a hybrid vision/grid map offers a intuitive and useful map to a human and robot.
- Both can be exploited together as landmarks for SLAM.
- Most conventional object recognizers for navigation need the prior knowledge of objects. However, teaching prior knowledge of an object by a human is time-consuming and tedious task.
Environment with both visual and range-based features
- Research objectives
- Development of a practical SLAM(Simultaneous Localization And Mapping) method to model the unknown environments through fusion of vision and range sensors.
Hybrid vision / grid map built by SLAM
- Paper 1 :
Yong-Ju Lee, Tae-Bum Kwon, Jae-Bok Song, SLAM of a Mobile Robot Using Thinning-based Topological Information, Int. Journal of Control, Automation and Systems, Vol. 5, No. 5, pp. 577-583, 2007.10.
- Paper 2 :
Yong-Ju Lee, Jae-Bok Song, Autonomous Recognition and Registration of Objects for Visual SLAM in Indoor Environments, Proc. of Int. Conf. on Control, Automation and Systems, pp. 668-673, 2007.10.
- Paper 3 : Yong-Ju Lee, Byung-Doo Yim, Jae-Bok Song, SLAM of a Mobile Robot Using IR sensor
and Vision sensor, KSME Fall Annual Meeting, pp. 704-709, 2006.
- Paper 4 : Yong-Ju Lee, Park Joong-Tae, Song Jae-Bok and Chung Woo Jin, SLAM of a Mobile Robot Using
Thinning Information, CASS2006, 2006.06.
- Paper 5 : Yong-Ju Lee and Song Jae-Bok, SLAM of a Mobile Robot in Dynamic Enviroments, The
joint conference on control, automation and systems, 2005.11.
* Last updated: 2012. 4. 27