Development of Nemo remotely operated underwater vehicle for the inspection of the Costa Concordia wreck

Remotely operated underwater vehicles are mobile robots increasingly used in underwater applications; these devices are widely used and suitable for different scenarios, for example, for patrolling and monitoring and also for underwater interventions. In the last 30 years, the remotely operated underwater vehicles have become more and more advanced; at the same rate with the progressive technological development of these vehicles, the market of the specialized component industry is fast-increasing. Generally speaking, a remotely operated underwater vehicle allows to investigate areas inaccessible or too dangerous for human beings. The use of remotely operated underwater vehicles during a mission, with the related implication of support ships and specialized pilots, or the involvement of professional divers, is usually associated with high costs. The reduction of these costs is an important topic in the underwater robotic field and the easy piloting of these mobile robots is a crucial aspect in their development. This article describes Nemo remotely operated underwater vehicle, a remotely operated underwater vehicle prototype specifically designed for the exploration of the Costa Concordia wreck, Isola del Giglio, Italy. Nemo remotely operated underwater vehicle can be considered a mini-remotely operated underwater vehicle, that is, a remotely operated underwater vehicle with weight less than 25?kg and easily deployable from a small boat. This article describes the main characteristics of the vehicle: the onboard control logic and on the development of a user-friendly graphical user interface for underwater navigation able to take advantage of its high maneuverability. It is worth to note that the developed graphical user interface enables to operate the vehicle even to inexperienced pilots. Preliminary experimental data collected during navigation are provided.


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  • Accession Number: 01631541
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Mar 31 2017 9:24AM