The ability of acoustic waves to penetrate through waters in all visibility conditions and for long ranges has made SOund NAvigation Ranging (SONAR) devices increasingly widespread for underwater sensing. In particular, imaging sonars, such as Forward-Looking SONARs (FLSs), have become ubiquitous nowadays both for Autonomous Underwater Vehicles (AUVs) and Remotely Operated Vehicles (ROVs). However, the loss of elevation angle information during the 3D to 2D image projection lessens the ability to understand the underwater environment. This paper presents a probabilistic 3D occupancy mapping framework that employs FLS images, and it is specifically tailored to AUVs. The proposed method is tested through the use of data recorded during sea trials performed in 2018 with FeelHippo AUV, a vehicle developed by the Department of Industrial Engineering of the University of Florence (UNIFI DIEF), at the NATO Science and Technology Organization Centre for Maritime Research and Experimentation (CMRE), La Spezia (Italy).

A Probabilistic 3D Map Representation for Forward-Looking SONAR Reconstructions / Franchi M.; Bucci A.; Zacchini L.; Topini E.; Ridolfi A.; Allotta B.. - ELETTRONICO. - (2020), pp. 1-6. (Intervento presentato al convegno 2020 IEEE/OES Autonomous Underwater Vehicles Symposium, AUV 2020 tenutosi a St. Johns, NL, Canada nel 2020) [10.1109/AUV50043.2020.9267934].

A Probabilistic 3D Map Representation for Forward-Looking SONAR Reconstructions

Franchi M.
;
Bucci A.;Zacchini L.;Topini E.;Ridolfi A.;Allotta B.
2020

Abstract

The ability of acoustic waves to penetrate through waters in all visibility conditions and for long ranges has made SOund NAvigation Ranging (SONAR) devices increasingly widespread for underwater sensing. In particular, imaging sonars, such as Forward-Looking SONARs (FLSs), have become ubiquitous nowadays both for Autonomous Underwater Vehicles (AUVs) and Remotely Operated Vehicles (ROVs). However, the loss of elevation angle information during the 3D to 2D image projection lessens the ability to understand the underwater environment. This paper presents a probabilistic 3D occupancy mapping framework that employs FLS images, and it is specifically tailored to AUVs. The proposed method is tested through the use of data recorded during sea trials performed in 2018 with FeelHippo AUV, a vehicle developed by the Department of Industrial Engineering of the University of Florence (UNIFI DIEF), at the NATO Science and Technology Organization Centre for Maritime Research and Experimentation (CMRE), La Spezia (Italy).
2020
2020 IEEE/OES Autonomous Underwater Vehicles Symposium, AUV 2020
2020 IEEE/OES Autonomous Underwater Vehicles Symposium, AUV 2020
St. Johns, NL, Canada
2020
Franchi M.; Bucci A.; Zacchini L.; Topini E.; Ridolfi A.; Allotta B.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1225537
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