Tracking data of a Remotely Operated Vehicle and its tether using a motion capture system and a tension sensor

In this paper, we present a dataset related to the behaviour of underwater umbilicals of a Remotely Operated Vehicle (ROV), specifically the BlueROV2. The data were collected from three different sources: a Motion Capture System (mo-cap system), the onboard sensors of the BlueROV2, and a tension sensor. The mo-cap system tracks the motion of the ROV and its tether, while the tension sensor measures the force exerted by the cable tension on the surface side, near the tether drum. The dataset were acquired for research purposes, specifically for studying underwater cables in the context of modeling, estimation, and control using machine learning and data-driven control methods. They can serve as a benchmark for developing and validating underwater tether models, enabling researchers to develop control methods that consider tether drag or entanglement, improving navigation accuracy of ROVs, or developing automated tether management systems. This paper describes the experimental setup, data acquisition, and post-processing procedures. Furthermore, it provides illustrative plots to highlight key features of the dataset.

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Publication Details

Journal
Scientific Data
Published
2025-12-03
DOI
https://doi.org/10.1038/s41597-025-06347-0
Primary Topic
Underwater Vehicles and Communication Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Tracking data of a Remotely Operated Vehicle and its tether using a motion capture system and a tension sensor

Bilal Wehbe, Giovanni Indiveri, Enrico Simetti, Juri Khanmeh
Scientific Data
Underwater Vehicles and Communication Systems
article

Tracking data of a Remotely Operated Vehicle and its tether using a motion capture system and a tension sensor

Bilal Wehbe, Giovanni Indiveri, Enrico Simetti, Juri Khanmeh
article en

Abstract

In this paper, we present a dataset related to the behaviour of underwater umbilicals of a Remotely Operated Vehicle (ROV), specifically the BlueROV2. The data were collected from three different sources: a Motion Capture System (mo-cap system), the onboard sensors of the BlueROV2, and a tension sensor. The mo-cap system tracks the motion of the ROV and its tether, while the tension sensor measures the force exerted by the cable tension on the surface side, near the tether drum. The dataset were acquired for research purposes, specifically for studying underwater cables in the context of modeling, estimation, and control using machine learning and data-driven control methods. They can serve as a benchmark for developing and validating underwater tether models, enabling researchers to develop control methods that consider tether drag or entanglement, improving navigation accuracy of ROVs, or developing automated tether management systems. This paper describes the experimental setup, data acquisition, and post-processing procedures. Furthermore, it provides illustrative plots to highlight key features of the dataset.

Scientific DataVol. 13(1)
German Research Centre for Artificial Intelligence (DE), University of Genoa (IT)
Openalex Percentile: Top 53%
Underwater Vehicles and Communication Systems
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