A Trajectory-Based Approach to Multi-Session Underwater Visual SLAM Using Global Image Signatures

Authors Antoni Burguera Burguera | Francisco Bonin-Font
In Journal of Marine Science and Engineering, MDPI, vol. 7, no. 8, August, 2019.
ISBN 2077-1312


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.

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