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Underwater cultural heritage sites are subject to constant change, whether due to natural forces such as sediments, waves, currents or human intervention. Until a few decades ago, the documentation and research of these sites was mostly done manually by diving archaeologists. This paper presents the results of the integration of remote sensing technologies with autonomous marine vehicles in order to make the task of site documentation even faster, more accurate, more efficient and more precisely georeferenced. It includes the integration of multibeam sonar, side scan sonar and various cameras into autonomous surface and underwater vehicles, remotely operated vehicle and unmanned aerial vehicle. In total, case studies for nine underwater cultural heritage sites around the Mediterranean region are presented. Each case study contains a brief archaeological background of the site, the methodology of using autonomous marine vehicles and sensors for their documentation, and the results in the form of georeferenced side-scan sonar mosaics, bathymetric models or reconstructed photogrammetric models. It is important to mention that this was the first time that any of the selected sites were documented with sonar technologies or autonomous marine vehicles. The main objective of these surveys was to document and assess the current state of the sites and to establish a basis on which future monitoring operations could be built and compared. Beyond the mere documentation and physical preservation, examples of the use of these results for the digital preservation of the sites in augmented and virtual reality are presented.

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Aquaculture net pens inspection and monitoring are important to ensure net stability and fish health in the fish farms. Remotely operated vehicles (ROVs) offer a low-cost and sophisticated solution for the regular inspection of the underwater fish net pens due to their ability of visual sensing and autonomy in a challenging and dynamic aquaculture environment. In this paper, we report the integration of an ROV with a visual servoing scheme for regular inspection and tracking of the net pens. We propose a vision-based positioning scheme that consists of an object detector, a pose generator, and a closed-loop controller. The system employs a modular approach that first utilizes two easily identifiable parallel ropes attached to the net for image processing through traditional computer vision methods. Second, the reference positions of the ROV relative to the net plane are extracted on the basis of a vision triangulation method. Third, a closed-loop control law is employed to instruct the vehicle to traverse from top to bottom along the net plane to inspect its status. The proposed vision-based scheme has been implemented and tested both through simulations and field experiments. The extensive experimental results have allowed the assessment of the performance of the scheme that resulted satisfactorily and can supplement the traditional aquaculture net pens inspection and tracking systems.