Tank dataset: an underwater multi-sensor dataset for SLAM evaluation
File(s)
Author(s)
Type
Journal Article
Abstract
Underwater visual Simultaneous Localization and Mapping (SLAM) is essential for autonomous underwater navigation and close-range underwater inspection. However, the turbid and low-light conditions common underwater severely limit visibility and cause motion blurring, posing significant open challenges for visual SLAM approaches deployed underwater. On the other hand, the scarcity of public underwater multi-sensor datasets, coupled with the lack of 6 Degree-of-Freedom (DoF) ground truth data for SLAM evaluation, hinders the advancement of underwater visual SLAM research. To address these problems, this paper introduces an underwater dataset encompassing multi-sensor data from a stereo camera, an Inertial Measurement Unit, a Doppler Velocity Log and a pressure sensor. To cover various difficulty levels for underwater SLAM evaluation, it provides 8 sequences collected under different speed and illumination conditions. Extrinsic and intrinsic calibration parameters are also provided for multi-sensor fusion. Additionally, we present TankGT, a fiducial-marker-based SLAM system designed to provide highly accurate 6 DoF ground truth poses in underwater environments, enabling rigorous quantitative and qualitative benchmarking for underwater SLAM algorithms. We demonstrate the effectiveness of the proposed Tank dataset with four SLAM algorithms. The dataset is released to facilitate underwater SLAM research in the community at http://senseroboticslab.github.io/underwater-tank-dataset.
Date Issued
2026-04-01
Date Acceptance
2025-06-04
Citation
International Journal of Robotics Research, 2026, 45 (4), pp.541-551
ISSN
0278-3649
Publisher
SAGE Publications
Start Page
541
End Page
551
Journal / Book Title
International Journal of Robotics Research
Volume
45
Issue
4
Copyright Statement
© The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). Request permissions for this article.
License URL
Identifier
10.1177/02783649251364904
Subjects
underwater dataset
underwater robotics
visual SLAM
Publication Status
Published
Date Publish Online
2025-08-30