광범위 환경에서 EKF-SLAM의 일관성 향상을 위한 새로운 관찰모델A new Observation Model to Improve the Consistency of EKF-SLAM Algorithm in Large-scale Environments
- Other Titles
- A new Observation Model to Improve the Consistency of EKF-SLAM Algorithm in Large-scale Environments
- Authors
- 남창주; 강재현; 도낙주
- Issue Date
- 2012
- Publisher
- 한국로봇학회
- Keywords
- Observation Model; EKF-SLAM; Consistency
- Citation
- 로봇학회 논문지, v.7, no.1, pp.29 - 34
- Indexed
- KCI
OTHER
- Journal Title
- 로봇학회 논문지
- Volume
- 7
- Number
- 1
- Start Page
- 29
- End Page
- 34
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/110588
- ISSN
- 1975-6291
- Abstract
- This paper suggests a new observation model for Extended Kalman Filter based Simultaneous Localization and Mapping (EKF-SLAM). Since the EKF framework linearizes non-linear functions around the current estimate, the conventional line model has large linearization errors when a mobile robot locates faraway from its initial position. On the other hand, the model that we propose yields less linearization error with respect to the landmark position and thus suitable in a large-scale environment. To achieve it, we build up a three-dimensional space by adding a virtual axis to the robot’s two-dimensional coordinate system and extract a plane by using a detected line on the two-dimensional space and the virtual axis. Since Jacobian matrix with respect to the landmark position has small value, we can estimate the position of landmarks better than the conventional line model. The simulation results verify that the new model yields less linearization errors than the conventional line model.
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Collections - Executive Vice President for Research > Institute of Convergence Science > 1. Journal Articles
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