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A Robot Application for Marine Vessel Inspection
Author(s) -
Eich Markus,
BonninPascual Francisco,
GarciaFidalgo Emilio,
Ortiz Alberto,
Bruzzone Gabriele,
Koveos Yannis,
Kirchner Frank
Publication year - 2014
Publication title -
journal of field robotics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.152
H-Index - 96
eISSN - 1556-4967
pISSN - 1556-4959
DOI - 10.1002/rob.21498
Subject(s) - robot , visual inspection , usability , automated x ray inspection , engineering , computer science , field (mathematics) , safer , artificial intelligence , marine engineering , computer vision , simulation , real time computing , image processing , image (mathematics) , human–computer interaction , computer security , mathematics , pure mathematics
Seagoing vessels have to undergo regular inspections, which are currently performed manually by ship surveyors. The main cost factor in a ship inspection is to provide access to the different areas of the ship, since the surveyor has to be close to the inspected parts, usually within arm's reach, either to perform a visual analysis or to take thickness measurements. The access to the structural elements in cargo holds, e.g., bulkheads, is normally provided by staging or by “cherry‐picking” cranes. To make ship inspections safer and more cost‐efficient, we have introduced new inspection methods, tools, and systems, which have been evaluated in field trials, particularly focusing on cargo holds. More precisely, two magnetic climbing robots and a micro‐aerial vehicle , which are able to assist the surveyor during the inspection, are introduced. Since localization of inspection data is mandatory for the surveyor, we also introduce an external localization system that has been verified in field trials, using a climbing inspection robot. Furthermore, the inspection data collected by the robotic systems are organized and handled by a spatial content management system that enables us to compare the inspection data of one survey with those from another, as well as to document the ship inspection when the robot team is used. Image‐based defect detection is addressed by proposing an integrated solution for detecting corrosion and cracks. The systems' performance is reported, as well as conclusions on their usability, all in accordance with the output of field trials performed onboard two different vessels under real inspection conditions.