Efficient View-Based SLAM Using Visual Loop Closures

Authors:
I. Mahon;S. B. Williams;O. Pizarro;M. Johnson-Roberson
Affiliations:
ARC Centre of Excellence for Autonomous Syst., Sydney Univ., Sydney, NSW;-;-;-
Venue:
IEEE Transactions on Robotics
Year:
2008

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Abstract

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.