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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ahmad, H. Namerikawa, T. |
| Copyright Year | 2011 |
| Description | Author affiliation: Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama, Japan, 223-8522 (Namerikawa, T.) || Kanazawa University, Kakuma-Machi, Kanazawa, Ishikawa, Japan, 920-1192 (Ahmad, H.) |
| Abstract | This paper deals with an analysis based on Fisher Information Matrix(FIM) for Extended Kalman Filter based Simultaneous Localization and Mapping(SLAM) problem. We show theoretically that the Cramer Rao Lower Bound is proportional to the number of landmarks, the magnitude of process and the measurement noises. In addition, we propose a method of adding a pseudo Positive semidefinite(PsD) matrix to the Fisher Information Matrix to decrease the computational cost in EKF based SLAM. The simulation results are convincing and realizes the improvement for EKF-based SLAM. Therefore, this method further improves the estimation in comparison with the normal EKF performance. |
| Starting Page | 782 |
| Ending Page | 787 |
| File Size | 806488 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781612844879 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-05-15 |
| Publisher Place | Taiwan |
| Access Restriction | Subscribed |
| Rights Holder | Asian Control Association |
| Subject Keyword | Simultaneous localization and mapping Robot kinematics Noise Estimation Covariance matrix Mobile robots |
| Content Type | Text |
| Resource Type | Article |
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