Semi-autonomous visual inspection of vessels assisted by an unmanned Micro Aerial Vehicle

Vessel maintenance entails periodic visual inspections of internal and external parts of the hull in order to detect the typical defective situations affecting metallic structures, such as cracks, coating breakdown, corrosion, etc. The main goal of the EU-FP7 project MINOAS is the automation of the inspection process, currently undertaken by human surveyors, by means of a fleet of robotic agents. This paper overviews a semi-autonomous approach to the inspection problem consisting of an autonomous Micro Aerial Vehicle (MAV) to be used as part of this fleet and which is in charge of regularly supplying images that can effectively teleport the surveyor from a base station to the areas of the hull to be inspected. Specific image processing software to analyze those images and assist the surveyor during the repair/no repair decision making process is also contributed. The control software approach adopted for the MAV, including self-localization and obstacle avoidance, is described and discussed, and experimental results in this regard are as well reported.