# Underwater inspection and intervention dataset

arXiv: https://arxiv.org/abs/2107.13628 · HTML: https://mlsanity.com/paper/2107.13628/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 9 references that are in the map.
- First posted on arXiv 28 Jul 2021.

## Builds on (most cited first, 2 of 2)

- [ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM](https://mlsanity.com/paper/2007.11898/) (2020)
- [Robust Gesture-Based Communication for Underwater Human-Robot Interaction in the context of Search and Rescue Diver Missions](https://mlsanity.com/paper/1810.07122/) (2018)

## Built on by (most cited first, 1 of 1)

- [FLSea: Underwater Visual-Inertial and Stereo-Vision Forward-Looking Datasets](https://mlsanity.com/paper/2302.12772/) (2023)

## Abstract (arXiv)

This paper presents a novel dataset for the development of visual navigation and simultaneous localisation and mapping (SLAM) algorithms as well as for underwater intervention tasks. It differs from existing datasets as it contains ground truth for the vehicle's position captured by an underwater motion tracking system. The dataset contains distortion-free and rectified stereo images along with the calibration parameters of the stereo camera setup. Furthermore, the experiments were performed and recorded in a controlled environment, where current and waves could be generated allowing the dataset to cover a wide range of conditions - from calm water to waves and currents of significant strength.