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Exploratory dives are traditionally the first step for marine scientists to acquire information on a previously unknown area of scientific interest. Manned submersibles have been the platform of choice for such exploration, as they allow a high level of environmental perception by the scientist on-board, and the ability to take informed decisions on what to explore next. However, manned submersibles have extremely high operation costs and provide very limited bottom time. Remotely operated vehicles (ROVs) can partially address these two issues, but have operational and cost constraints that restrict their usage. This paper discusses new capabilities to assist scientists operating lightweight hybrid remotely operated vehicles (HROV) in exploratory missions of mapping and surveying. The new capabilities, under development within the Spanish National project OMNIUS, provide a new layer of autonomy for HROVs by exploring three key concepts: Omni-directional optical sensing for collaborative immersive exploration, Proximity safety awareness and Online mapping during mission time.

Natural CO2 releases from shallow marine hydrothermal vents are assumed to mix into the water column and not accumulate into stratified seafloor pools. We present newly discovered shallow subsea pools located within the Santorini volcanic caldera of the Southern Aegean Sea, Greece, that accumulate CO2 emissions from geologic reservoirs. This type of hydrothermal seafloor pool, containing highly concentrated CO2, provides direct evidence of shallow benthic CO2 accumulations originating from sub-seafloor releases. Samples taken from within these acidic pools are devoid of calcifying organisms and channel structures among the pools indicate gravity driven flow, suggesting that seafloor release of CO2 at this site may preferentially impact benthic ecosystems. These naturally occurring seafloor pools may provide a diagnostic indicator of incipient volcanic activity and can serve as an analog for studying CO2 leakage and benthic accumulations from subsea carbon capture and storage sites.

We present a novel method for planning coverage paths for inspecting complex structures on the ocean floor using an autonomous underwater vehicle (AUV). Our method initially uses a 2.5-dimensional (2.5D) prior bathymetric map to plan a nominal coverage path that allows the AUV to pass its sensors over all points on the target area. The nominal path uses a standard mowing-the-lawn pattern in effectively planar regions, while in regions with substantial 3D relief it follows horizontal contours of the terrain at a given offset distance. We then go beyond previous approaches in the literature by considering the vehicle's state uncertainty rather than relying on the unrealistic assumption of an idealized path execution. Toward that end, we present a replanning algorithm based on a stochastic trajectory optimization that reshapes the nominal path to cope with the actual target structure perceived in situ. The replanning algorithm runs onboard the AUV in real time during the inspection mission, adapting the path according to the measurements provided by the vehicle's range-sensing sonars. Furthermore, we propose a pipeline of state-of-the-art surface reconstruction techniques we apply to the data acquired by the AUV to obtain 3D models of the inspected structures that show the benefits of our planning method for 3D mapping. We demonstrate the efficacy of our method in experiments at sea using the GIRONA 500 AUV, where we cover part of a breakwater structure in a harbor and an underwater boulder rising from 40 m up to 27 m depth This research has been sponsored by the Government of Spain (COMAROB Project, DPI2011-27977-C03-02), the MORPH EU FP7-Project (grant agreement FP7-ICT-2011-7-288704), and the Eurofleets2 EU FP7-Project (grant agreement FP7-INF-2012-312762). The authors are grateful to Lluis Magi, Carles Candela, and Arnau Carrera for helping with the GIRONA 500 operations

Underwater maps are an important source of information for the scientific community, since mapping the seafloor is the starting point for underwater exploration. The advance of range scanning methodologies (both acoustic and optical), enables the mapping of the seabed to attain increasingly larger resolutions. However, all these techniques sample the surface to reconstruct in the form of a point cloud. Surface reconstruction methods try to recover from these points a continuous surface representing the object in the form of a mesh of triangles, easing visualization and further processing. This thesis proposes four different strategies to tackle the problem of surface reconstruction from point sets corrupted with high levels of noise and outliers, while also recovering the boundaries of these surfaces. The results obtained by our algorithms are discussed and compared both qualitatively and quantitatively with other state-of-the-art approaches, Els mapes del fons del marí són una important font d'informació per la comunitat científica. Els avenços en les metodologies d'escaneig (acústic o òptic), permeten que la construcció de mapes del fons marí es realitzi cada cop a més altes resolucions. Tot i això, totes aquestes tècniques mostregen la superfície de l'àrea d’interès en la forma d'un núvol de punts. Els mètodes de reconstrucció de superfícies són els encarregats d’obtenir una superfície continua que representi l'objecte en forma d'una malla de triangles, que facilitarà la visualització i el processat posterior d'aquestes dades. Aquest treball contribueix a l'àrea de reconstrucció de superfícies amb quatre mètodes diferents, capaços de treballar amb núvols de punts que continguin alts nivells de soroll i outliers, i que recuperen al mateix moment els llindars d’aquestes superfícies. Els resultats obtinguts han estat avaluats i comparats tant qualitativament com quantitativament contra altres mètodes de l'estat de l'art

Starting in January 2009, the RAUVI (Reconfigurable Autonomous Underwater Vehicle for Intervention Missions) project is a 3-year coordinated research action funded by the Spanish Ministry of Research and Innovation. In this paper, the state of progress after 2 years of continuous research is reported. As a first experimental validation of the complete system, a search and recovery problem is addressed, consisting of finding and recovering a flight data recorder placed at an unknown position at the bottom of a water tank. An overview of the techniques used to successfully solve the problem in an autonomous way is provided. The obtained results are very promising and are the first step toward the final test in shallow water at the end of 2011 This research was partly supported by Spanish Ministry of Research and Innovation DPI2008-06548-C01-02-03 (RAUVI Project), by the European Commissions Seventh Framework Programme FP7/2007-2013 underGrant agreement 248497 (TRIDENT Project), by Fundació Caixa Castelló-Bancaixa P1-1B2009-50, and by the Spanish Ministry of Education and Science (MCINN Grant CTM2010-15216), Ramon Y Cajal Program (N. Gracias) and the FPI program (R. Campos)