- Abstract:
-
This paper develops a Square Root Unscented Kalman Filter (SRUKF) for performing video-rate visual simultaneous localization and mapping (SLAM) using a single camera. The conventional UKF has been proposed previously for SLAM, improving the handling of nonlinearities compared with the more widely used Extended Kalman Filter (EKF). However, no account was taken of the comparative complexity of the algorithms: In SLAM, the UKF scales as O(N;{3}) in the state length, compared to the EKF's O(N;{2...
Expand abstract - Publication status:
- Published
- Publisher copy:
- 10.1109/tpami.2008.189
-
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- Journal:
- IEEE transactions on pattern analysis and machine intelligence
- Volume:
- 31
- Issue:
- 7
- Pages:
- 1251-1263
- Publication date:
- 2009-07-05
- DOI:
- EISSN:
-
1939-3539
- ISSN:
-
0162-8828
- URN:
-
uuid:e77619c6-1e71-450f-a2d7-4300686a5976
- Source identifiers:
-
62594
- Local pid:
- pubs:62594
- Language:
- English
- Keywords:
- Copyright date:
- 2009
Journal article
An O(N(2)) square root unscented Kalman Filter for visual simultaneous localization and mapping.
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