Preprint Article Version 1 This version is not peer-reviewed

A Method for Recognition and Coordinate Reference of Autono-Mous Underwater Vehicle to Inspected Objects of Industrial Sub-Sea Structures Using Stereo Images

Version 1 : Received: 2 August 2024 / Approved: 2 August 2024 / Online: 6 August 2024 (03:44:04 CEST)

How to cite: Bobkov, V.; Kudryashov, A. A Method for Recognition and Coordinate Reference of Autono-Mous Underwater Vehicle to Inspected Objects of Industrial Sub-Sea Structures Using Stereo Images. Preprints 2024, 2024080202. https://doi.org/10.20944/preprints202408.0202.v1 Bobkov, V.; Kudryashov, A. A Method for Recognition and Coordinate Reference of Autono-Mous Underwater Vehicle to Inspected Objects of Industrial Sub-Sea Structures Using Stereo Images. Preprints 2024, 2024080202. https://doi.org/10.20944/preprints202408.0202.v1

Abstract

To date, the development of unmanned technologies using autonomous underwater vehicles (AUV) has become an urgent demand for solving the problem of inspection of industrial sub-sea structures. A key issue here is precise localization of AUVs relative to underwater objects. However, the well-known challenges of recognizing and coordinating underwater objects (impossibility to use GPS, undercurrents, etc.) do not allow high-precision navigation if based solely on a standard suite of AUV navigation tools (sonars, etc.). An alternative is a technology of processing of optical images that, at short distances, can provide higher accuracy of AUV navigation compared to a technology of acoustic measurement processing. In this study, in the context of the problem of subsea production system inspection, we propose a method to recognize underwater objects and provide coordinate reference of AUV to them, based on stereo-image processing. Its distinctive features are the use of a non-standard technique for generating a geometric model of an object from its views (foreshortening) taken from positions of a pre-made overview trajectory, the use of various characteristic geometric elements when recognizing objects, and the original algorithms for comparing visual data of the inspection trajectory with an a priori model of the object.

Keywords

autonomous underwater vehicle (AUV); subsea production systems (SPS); computer vision; stereo; visual navigation

Subject

Computer Science and Mathematics, Computer Vision and Graphics

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