Artificial Intelligence methods for Underwater target Tracking

Informazioni relative al progetto

AIforUTracking

ID dell’accordo di sovvenzione: 893089

DOI 10.3030/893089

Progetto chiuso

Data della firma CE 16 Marzo 2020

Data di avvio 1 Marzo 2021

Data di completamento 30 Settembre 2023

Finanziato da

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Costo totale € 226 801,76

Contributo UE € 226 801,76

Coordinato da

AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS
Spain

Pubblicazioni

Peer reviewed articles (4)

Spatial ecology of Norway lobster Nephrops norvegicus in Mediterranean deep-water environments: implications for designing no-take marine reserves

Autori: Maria Vigo; Joan Navarro; I. Masmitja; I. Masmitja; Jacopo Aguzzi; José A. García; Guiomar Rotllant; Nixon Bahamon
Pubblicato in: Marine Ecology Progress Series, Numero 16161599, 2021, ISSN 1616-1599
Editore: Inter-Research Science Publisher
DOI: 10.3354/meps13799

Dynamic robotic tracking of underwater targets using reinforcement learning

Autori: I. Masmitja, M. Martin, T. O’Reilly, B. Kieft, N. Palomeras, J. Navarro, K. Katija
Pubblicato in: Science Robotics, Numero 26/07/2023, 2023, Pagina/e eade7811, ISSN 2470-9476
Editore: American Association for the Advancement of Science
DOI: 10.1126/scirobotics.ade7811

Burrow emergence rhythms of deep-water Mediterranean Norway lobsters (Nephrops norvegicus) revealed by acoustic telemetry

Autori: J. Aguzzi; M. Vigo; N. Bahamon; I. Masmitja; D. Chatzievangelou; N. J. Robinson; J. P. Jónasson; A. Sánchez-Márquez; J. Navarro; J. B. Company
Pubblicato in: Reviews in Fish Biology and Fisheries, Numero 26/05/2023, 2023, ISSN 0960-3166
Editore: Kluwer Academic Publishers
DOI: 10.1007/s11160-023-09787-2

Spatial ecology of Norway lobster Nephrops norvegicus in Mediterranean deep-water environments: implications for designing no-take marine reserves

Autori: Vigo M., Navarro J., Masmitja I., Aguzzi J., García JA., Rotllant G., Bahamón N., Company JB.
Pubblicato in: Marine Ecology Progress Series, Numero 16/09/2021, 2021, Pagina/e 173-188, ISSN 0171-8630
Editore: Inter-Research Science Publishing
DOI: 10.3354/meps13799

Conference proceedings (4)

Platform-portable reinforcement learning methods to localize underwater targets

Autori: Ivan Masmitja, Mario Martin, Tom O'Reilly, Kakani Katija, Joan Navarro
Pubblicato in: Oceans MTS/IEEE proceedings, Numero 15/05/2023, 2023, ISBN 979-8-3503-3226-1
Editore: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/oceanslimerick52467.2023.10244488

A reinforcement learning path planning approach for range-only underwater target localization with autonomous vehicles

Autori: Ivan Masmitja; Mario Martin; Kakani Katija; Spartacus Gomariz; Joan Navarro
Pubblicato in: IEEE 18th International Conference on Automation Science and Engineering (CASE), 2022, ISBN 978-1-4799-1515-6
Editore: IEEE

TransfQMix: Transformers for Leveraging the Graph Structure of Multi-Agent Reinforcement Learning Problems

Autori: Gallici M., Martin M., Masmitja I.
Pubblicato in: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, Numero 15/05/2023, 2023, Pagina/e 1679–1687, ISBN 9781450394321
Editore: International Foundation for Autonomous Agents and Multiagent Systems
DOI: 10.48550/arxiv.2301.05334

Engineering a testbed for bidirectional acoustic tag development

Autori: Gerrard Batet, Ivan Masmitja, David Sarria, Spartacus Gomariz, Joaquin Del Rio
Pubblicato in: OCEANS MTS/IEEE proceedings, Numero 15/05/2023, 2023, ISBN 979-8-3503-3226-1
Editore: Engineering a testbed for bidirectional acoustic tag development
DOI: 10.1109/oceanslimerick52467.2023.10244649