NERITES

The proposition in this project is to use autonomous platforms for remote monitoring and chemical mapping of underwater heritage sites, such as AUVs (Autonomous Underwater Vehicles), BUOYs (Unmanned Surface Vehicles) and ROVs (remote operated vehicles).

A swarm of self-coordinated AUVs will be responsible to monitor, survey and scan the heritage sites for detecting/identifying and monitor degradation, state of the UW surrounding site, possible intervention actions for alarming conditions etc. The swarm of AUVs will embed high edge processing capacity to support operational autonomy, dynamic path planning, dynamic sample-strategy planning and coordinated-swarming towards overall low energy consumption and long mission endurance, according to the project mission goals.

The proposed swarming concept foresees building common underwater consensus of the cultural site, through periodic bilateral communication between AUVs to mutually achieve the overall common surveying goal; while the mother BUOY will be responsible to collect and deeply analyze raw AUV information to provide enhanced site situation awareness insights to the external human supervisor/user. Furthermore, the BUOY will be equipped with renewable solar collectors to ensure continuous power availability and reduced mission’s footprint, enough to support the overall mission energy needs (AUV will be periodically powered through BUOY). The supervisor/user will be located in a remote monitoring station, onshore, to allow periodic mission lifecycle management and general overview of the whole system situation based on real-time visual analytic mechanisms.

Project Consortium

The formed consortium has been shaped of sixteen (16) partners from eight (8) countries.The project combines different key players and organisation in order to ensure a multifarious cooperation.

Full title: Systematic autonomous remote surveying of underwater cultural heritage monuments and artefacts using non-destructive, cost-effective and transportable digital solutions

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101004152