2026-04-29T04:08:43Zhttps://repisalud.isciii.es/rest/oai/requestoai:repisalud.isciii.es:20.500.12105/227452024-11-28T23:41:08Zcom_20.500.12105_15322com_20.500.12105_2051col_20.500.12105_16967
Repisalud
author
Burguera, Antoni
author
Bonin-Font, Francisco
2024-09-10T13:09:40Z
2024-09-10T13:09:40Z
2019-08
Burguera 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.
http://hdl.handle.net/20.500.13003/15576
https://hdl.handle.net/20.500.12105/22745
10.3390/jmse7080278
2077-1312
Journal of Marine Science and Engineering
2-s2.0-85071173012
482991100008
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.
eng
Visual SLAM
Multi-session robot
Posidonia oceanica
A Trajectory-Based Approach to Multi-Session Underwater Visual SLAM Using Global Image Signatures
research article