Journal
IEEE TRANSACTIONS ON ROBOTICS
Volume 24, Issue 5, Pages 1002-1014Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TRO.2008.2004888
Keywords
Autonomous underwater vehicle (AUV) navigation; Cholesky factorization; extended information filter (EIF); simultaneous localization and mapping (SLAM)
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Funding
- Australian Research Council (ARC)
- New South Wales State Government
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This paper presents a simultaneous localization and mapping algorithm suitable for large-scale visual navigation. The estimation process is based on the viewpoint augmented navigation (VAN) framework using an extended information filter. Cholesky factorization modifications are used to maintain a factor of the VAN information matrix, enabling efficient recovery of state estimates and covariances. The algorithm is demonstrated using data acquired by an autonomous underwater vehicle performing a visual survey of sponge beds. Loop-closure observations produced by a stereo vision system are used to correct the estimated vehicle trajectory produced by dead reckoning sensors.
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