Identifier to cite or link to this item: http://hdl.handle.net/20.500.13003/15576
A Trajectory-Based Approach to Multi-Session Underwater Visual SLAM Using Global Image Signatures
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CitationBurguera A, Bonnín Pascual F. A Trajectory-Based Approach to Multi-Session Underwater Visual SLAM Using Global Image Signatures. J Mar Sci Eng. 2019 Aug;7(8):278.
This paper presents a multi-session monocular Simultaneous Localization and Mapping (SLAM) approach focused on underwater environments. The system is composed of three main blocks: a visual odometer, a loop detector, and an optimizer. Single session loop closings are found by means of feature matching and Random Sample Consensus (RANSAC) within a search region. Multi-session loop closings are found by comparing hash-based global image signatures. The optimizer refines the trajectories and joins the different maps. Map joining preserves the trajectory structure by adding a single link between the joined sessions, making it possible to aggregate or disaggregate sessions whenever is necessary. All the optimization processes can be delayed until a certain number of loops has been found in order to reduce the computational cost. Experiments conducted in real subsea scenarios show the quality and robustness of this proposal.