Publication | Open Access
ENDURUNS: An Integrated and Flexible Approach for Seabed Survey Through Autonomous Mobile Vehicles
48
Citations
63
References
2020
Year
EngineeringUnderwater SystemH2020 Enduruns ProjectField RoboticsOceanographyMarine EngineeringIntelligent SystemsFlexible ApproachSocial SciencesNatural ResourcesSeabed Survey ActivitiesCartographyUnderwater RoboticsGeographyAutonomous Underwater VehiclesComputer ScienceDeep Sea ExplorationMarine RoboticsUnderwater RobotUnderwater VehicleOcean EngineeringAerospace EngineeringUnderwater TechnologyRobotics
The oceans cover more than two‑thirds of the planet, yet only a small fraction of their depths has been explored. The ENDURUNS project proposes a novel scientific and technological framework for extended autonomous seabed surveys in both deep‑sea and coastal environments. The system integrates a hybrid autonomous underwater vehicle that can operate as a thruster‑driven vehicle or a sea glider, coupled with an unmanned surface vehicle equipped with satellite communications, photovoltaic panels, hydrogen fuel cells and Li‑ion batteries, and onboard CPUs for real‑time data analysis, compression, and semantic classification.
The oceans cover more than two-thirds of the planet, representing the vastest part of natural resources. Nevertheless, only a fraction of the ocean depths has been explored. Within this context, this article presents the H2020 ENDURUNS project that describes a novel scientific and technological approach for prolonged underwater autonomous operations of seabed survey activities, either in the deep ocean or in coastal areas. The proposed approach combines a hybrid Autonomous Underwater Vehicle capable of moving using either thrusters or as a sea glider, combined with an Unmanned Surface Vehicle equipped with satellite communication facilities for interaction with a land station. Both vehicles are equipped with energy packs that combine hydrogen fuel cells and Li-ion batteries to provide extended duration of the survey operations. The Unmanned Surface Vehicle employs photovoltaic panels to increase the autonomy of the vehicle. Since these missions generate a large amount of data, both vehicles are equipped with onboard Central Processing units capable of executing data analysis and compression algorithms for the semantic classification and transmission of the acquired data.
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