An acoustic-based approach for real-time deep-water navigation of an AUV

Navigation of Autonomous Underwater Vehicles (AUVs) remains a challenge due to the impossibility to use radio frequency signals and Global Positioning System (GPS). Navigation systems usually integrate different proprioceptive sensors to estimate the asset and the speed of the vehicle. In particular...

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Published in:Proceedings of the International Ship Control Systems Symposium (iSCSS), Proceedings of the International Ship Control Systems Symposium (iSCSS)
Main Authors: Tesei, A, Micheli, M, Vermeij, A, Ferri, G, Mazzi, M, Grenon, G, Morlando, L, Costanzi, R, Fenucci, D, Caiti, A, Munafò, A
Format: Conference Object
Language:English
Published: 2018
Subjects:
Online Access:https://hdl.handle.net/11568/1272704
https://doi.org/10.24868/issn.2631-8741.2018.005
https://library.imarest.org/record/7718?v=pdf
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author Tesei, A
Micheli, M
Vermeij, A
Ferri, G
Mazzi, M
Grenon, G
Morlando, L
Costanzi, R
Fenucci, D
Caiti, A
Munafò, A
author2 Tesei, A
Micheli, M
Vermeij, A
Ferri, G
Mazzi, M
Grenon, G
Morlando, L
Costanzi, R
Fenucci, D
Caiti, A
Munafò, A
author_facet Tesei, A
Micheli, M
Vermeij, A
Ferri, G
Mazzi, M
Grenon, G
Morlando, L
Costanzi, R
Fenucci, D
Caiti, A
Munafò, A
author_sort Tesei, A
collection ARPI - Archivio della Ricerca dell'Università di Pisa
container_title Proceedings of the International Ship Control Systems Symposium (iSCSS), Proceedings of the International Ship Control Systems Symposium (iSCSS)
container_volume 1
description Navigation of Autonomous Underwater Vehicles (AUVs) remains a challenge due to the impossibility to use radio frequency signals and Global Positioning System (GPS). Navigation systems usually integrate different proprioceptive sensors to estimate the asset and the speed of the vehicle. In particular, the Doppler Velocity Log (DVL) is fundamental during the navigation to have an accurate estimate of the vehicle’s speed. This work addresses the enhancement of the navigation performance of an AUV through the development of a Deep Water Navigation Filter (DWNF). The DWNF is able to work in those scenarios where traditional navigation sensors show their limits: e.g., deep waters where DVL bottom lock cannot be achieved, or areas where the use of traditionally used static and dedicated beacons is incompatible with the mission requirements. The proposed approach exploits the concept of using a network of vehicles cooperatively supporting each other for their navigation. Several types of measurements coming from the different nodes (i.e. acoustic positioning system such as ship-mounted SSBL acoustic positioning system, USBL, range measurements from the different nodes) are fused in an Extended Kalman Filter framework with the odometry data. DWNF pushes forward the idea of using a network of robotic assets as a provider of navigation services allowing more flexible and robust operations of the deployed system. The approach has been tested at sea during several experiments. We report here results from DWNF running successfully in real-time on the NATO STO-Centre for Maritime Research and Experimentation (CMRE) vehicles during the Dynamic Mongoose’17 experimentation off the South coast of Iceland (June-July 2017).
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https://hdl.handle.net/11568/1272704
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spelling ftunivpisairis:oai:arpi.unipi.it:11568/1272704 2025-01-16T22:40:08+00:00 An acoustic-based approach for real-time deep-water navigation of an AUV Tesei, A Micheli, M Vermeij, A Ferri, G Mazzi, M Grenon, G Morlando, L Costanzi, R Fenucci, D Caiti, A Munafò, A Tesei, A Micheli, M Vermeij, A Ferri, G Mazzi, M Grenon, G Morlando, L Costanzi, R Fenucci, D Caiti, A Munafò, A 2018 ELETTRONICO https://hdl.handle.net/11568/1272704 https://doi.org/10.24868/issn.2631-8741.2018.005 https://library.imarest.org/record/7718?v=pdf eng eng ispartofbook:Proceedings of the International Ship Control Systems Symposium (iSCSS), 2018 International Naval Engineering Conference and Exhibition incorporating the International Ship Control Systems Symposium, INEC/iSCSS 2018 volume:1 firstpage:1 lastpage:7 numberofpages:7 https://hdl.handle.net/11568/1272704 https://library.imarest.org/record/7718?v=pdf Autonomous Underwater Vehicle Data Fusion Deep Water navigation Extended Kalman Filter info:eu-repo/semantics/conferenceObject 2018 ftunivpisairis https://doi.org/10.24868/issn.2631-8741.2018.005 2024-11-05T01:01:10Z Navigation of Autonomous Underwater Vehicles (AUVs) remains a challenge due to the impossibility to use radio frequency signals and Global Positioning System (GPS). Navigation systems usually integrate different proprioceptive sensors to estimate the asset and the speed of the vehicle. In particular, the Doppler Velocity Log (DVL) is fundamental during the navigation to have an accurate estimate of the vehicle’s speed. This work addresses the enhancement of the navigation performance of an AUV through the development of a Deep Water Navigation Filter (DWNF). The DWNF is able to work in those scenarios where traditional navigation sensors show their limits: e.g., deep waters where DVL bottom lock cannot be achieved, or areas where the use of traditionally used static and dedicated beacons is incompatible with the mission requirements. The proposed approach exploits the concept of using a network of vehicles cooperatively supporting each other for their navigation. Several types of measurements coming from the different nodes (i.e. acoustic positioning system such as ship-mounted SSBL acoustic positioning system, USBL, range measurements from the different nodes) are fused in an Extended Kalman Filter framework with the odometry data. DWNF pushes forward the idea of using a network of robotic assets as a provider of navigation services allowing more flexible and robust operations of the deployed system. The approach has been tested at sea during several experiments. We report here results from DWNF running successfully in real-time on the NATO STO-Centre for Maritime Research and Experimentation (CMRE) vehicles during the Dynamic Mongoose’17 experimentation off the South coast of Iceland (June-July 2017). Conference Object Iceland ARPI - Archivio della Ricerca dell'Università di Pisa Proceedings of the International Ship Control Systems Symposium (iSCSS), Proceedings of the International Ship Control Systems Symposium (iSCSS) 1
spellingShingle Autonomous Underwater Vehicle
Data Fusion
Deep Water navigation
Extended Kalman Filter
Tesei, A
Micheli, M
Vermeij, A
Ferri, G
Mazzi, M
Grenon, G
Morlando, L
Costanzi, R
Fenucci, D
Caiti, A
Munafò, A
An acoustic-based approach for real-time deep-water navigation of an AUV
title An acoustic-based approach for real-time deep-water navigation of an AUV
title_full An acoustic-based approach for real-time deep-water navigation of an AUV
title_fullStr An acoustic-based approach for real-time deep-water navigation of an AUV
title_full_unstemmed An acoustic-based approach for real-time deep-water navigation of an AUV
title_short An acoustic-based approach for real-time deep-water navigation of an AUV
title_sort acoustic-based approach for real-time deep-water navigation of an auv
topic Autonomous Underwater Vehicle
Data Fusion
Deep Water navigation
Extended Kalman Filter
topic_facet Autonomous Underwater Vehicle
Data Fusion
Deep Water navigation
Extended Kalman Filter
url https://hdl.handle.net/11568/1272704
https://doi.org/10.24868/issn.2631-8741.2018.005
https://library.imarest.org/record/7718?v=pdf