Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/71235
Título: Acoustic detection of tagged angelsharks from an autonomous sailboat
Autores/as: Cabrera Gámez, Jorge 
Domínguez-Brito, Antonio C. 
Santana Jorge, F.
Gamo, Diego
Jiménez, David
Guerra, A.
Castro, José Juan 
Clasificación UNESCO: 120325 Diseño de sistemas sensores
251011 Acústica submarina
120304 Inteligencia artificial
120326 Simulación
331913 Vehículos submarinos
Palabras clave: Acoustic receiver
Acoustic tag detection
Angelshark (squatina squatina)
Autonomous navigation
Autonomous sailboat, et al.
Fecha de publicación: 2020
Editor/a: Springer 
Proyectos: Acusquat:Seguimiento Acustico Del Comportamiento Del Angelote (Squatina Squatina) en Areas Criticas de Conservación. 
Publicación seriada: Advances in Intelligent Systems and Computing 
Conferencia: 4th Iberian Robotics Conference, ROBOT 2019 
Resumen: Autonomous sailboats are silent surface vehicles which are well suited for acoustic monitoring. The integration of an acoustic receiver in an unmanned surface vehicle has a large potential for population monitoring as it permits to report geo-referenced detections in real time, so that researchers can adapt monitoring strategies as data arrive. In this paper we present preliminary work, done on the framework of ACUSQUAT project, to explore the usage of an acoustic receiver onboard a small (2 m length-over-all) autonomous sailboat in order to detect the presence of tagged adult exemplars of angelshark (Squatina squatina), the target species in ACUSQUAT, in certain areas which have demonstrated that this approach is feasible. Results obtained in simulation and during field trials are presented.
URI: http://hdl.handle.net/10553/71235
ISBN: 978-3-030-35989-8
ISSN: 2194-5365
DOI: 10.1007/978-3-030-35990-4_24
Fuente: Silva M., Luís Lima J., Reis L., Sanfeliu A., Tardioli D. (eds) Robot 2019: Fourth Iberian Robotics Conference. ROBOT 2019. Advances in Intelligent Systems and Computing, vol 1092, pp. 295-304. Springer, Cham. 2020.
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