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.