Three underwater two-agent sequences for multi-agent, monocular visual SLAM validation

Some underwater applications involve deploying multiple underwater Remotely Operated Vehicles in a common area. Such applications require the localization of these vehicles, not only with respect to each other but also with respect to a previously unknown environment, hence the interest in multi-agent simultaneous localization and mapping (SLAM) algorithms. Underwater VSLAM usually relies on multi-sensor fusion, but some works highlight the interest of visual SLAM for underwater applications. The current dataset provides three underwater two-agent sequences for the evaluation of multi-agent, monocular, VSLAM algorithms in underwater environments. The sequences include two in pool and one in the sea. Reference trajectories computed using Structure-from-Motion are provided.

Disciplines

Cross-discipline

Keywords

Underwater dataset, Visual SLAM, Multi-agent SLAM

Location

44.138733N, 42.714607S, 8.612247E, 4.437442W

Data

FileSizeFormatProcessingAccess
Dataset
96 MoZIPProcessed data
How to cite
Drupt Juliette, Dune-Maillard Claire, Comport Andrew I., Hugel Vincent (2023). Three underwater two-agent sequences for multi-agent, monocular visual SLAM validation. SEANOE. https://doi.org/10.17882/99618

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