Peer-Reviewed Journal Details
Mandatory Fields
Trslic P.;Rossi M.;Robinson L.;O'Donnel C.;Weir A.;Coleman J.;Riordan J.;Omerdic E.;Dooly G.;Toal D.
2020
January
Ocean Engineering
Vision based autonomous docking for work class ROVs
Published
16 ()
Optional Fields
Autonomous docking Computer vision Resident ROV
196
© 2019 This 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 ROV fleet.
0029-8018
10.1016/j.oceaneng.2019.106840
Grant Details