Trslic_2019_Vision.pdf (6.69 MB)
Vision based autonomous docking for work class ROVs
journal contribution
posted on 2020-01-31, 12:56 authored by Petar Trslić, Matija Rossi, Luke Robinson, Cathal W. O’Donnel, Anthony Weir, Joseph Coleman, James Riordan, Edin Omerdić, Gerard Dooly, Daniel ToalThis paper presents autonomous docking of an industry standard work-class ROV to both static and dynamic docking station (Tether Management System — TMS) using visual based pose estimation techniques. This is the first time autonomous docking to a dynamic docking station has been presented. Furthermore, the presented system does not require a specially designed docking station but uses a conventional cage type TMS. The paper presents and discusses real-world environmental tests successfully completed during January 2019 in the North Atlantic Ocean. To validate the performance of the system, a commercial state of the art underwater navigation system has been used. The results demonstrate a significant advancement in resident ROV automation and capabilities, and represents a system which can be retrofitted to the current
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Ocean Engineering;196, (2020) 106840Publisher
ElsevierNote
peer-reviewedOther Funding information
SFI, Marine Institute Ireland, Horizon 2020Language
EnglishExternal identifier
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