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...
Published in: | Proceedings of the International Ship Control Systems Symposium (iSCSS), Proceedings of the International Ship Control Systems Symposium (iSCSS) |
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Main Authors: | , , , , , , , , , , |
Format: | Conference Object |
Language: | English |
Published: |
2018
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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 |
_version_ | 1821556773300994048 |
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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). |
format | Conference Object |
genre | Iceland |
genre_facet | Iceland |
id | ftunivpisairis:oai:arpi.unipi.it:11568/1272704 |
institution | Open Polar |
language | English |
op_collection_id | ftunivpisairis |
op_doi | https://doi.org/10.24868/issn.2631-8741.2018.005 |
op_relation | 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 |
publishDate | 2018 |
record_format | openpolar |
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 |