000007718 001__ 7718 000007718 005__ 20240626123056.0 000007718 02470 $$2doi$$a10.24868/issn.2631-8741.2018.005 000007718 035__ $$a2536885 000007718 037__ $$aGENERAL 000007718 245__ $$aAn acoustic-based approach for real-time deep-water navigation of an AUV 000007718 269__ $$a2018-10-02 000007718 336__ $$aConference Proceedings 000007718 520__ $$aNavigation 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).  000007718 542__ $$fCC-BY-NC-ND-4.0 000007718 6531_ $$aAutonomous Underwater Vehicles 000007718 6531_ $$aDeep Water navigation 000007718 6531_ $$aExtended Kalman Filter 000007718 6531_ $$aData Fusion 000007718 7001_ $$aTesei, A$$uNATO Centre for Maritime Research and Experimentation La Spezia, ITALY 000007718 7001_ $$aMicheli, M$$uNATO Centre for Maritime Research and Experimentation La Spezia, ITALY 000007718 7001_ $$aVermeij, A$$uNATO Centre for Maritime Research and Experimentation La Spezia, ITALY 000007718 7001_ $$aFerri, G$$uNATO Centre for Maritime Research and Experimentation La Spezia, ITALY 000007718 7001_ $$aMazzi, M$$uNATO Centre for Maritime Research and Experimentation La Spezia, ITALY 000007718 7001_ $$aGrenon, G$$uNATO Centre for Maritime Research and Experimentation La Spezia, ITALY 000007718 7001_ $$aMorlando, L$$uNATO Centre for Maritime Research and Experimentation La Spezia, ITALY 000007718 7001_ $$aCostanzi, R$$uDipartimento di Ingegneria dell'Informazione, Università di Pisa, Pisa, ITALY 000007718 7001_ $$aFenucci, D$$uDipartimento di Ingegneria dell'Informazione, Università di Pisa, Pisa, ITALY 000007718 7001_ $$aCaiti, A$$uDipartimento di Ingegneria dell'Informazione, Università di Pisa, Pisa, ITALY 000007718 7001_ $$aMunafò, A$$uMarine Autonomous & Robotic Systems National Oceanographic Centre (NOC) Southampton, UK 000007718 773__ $$tConference Proceedings of iSCSS 000007718 773__ $$jiSCSS 2018 000007718 789__ $$whttps://zenodo.org/record/2536885$$2URL$$eIsIdenticalTo 000007718 85641 $$uhttps://www.imarest.org/iscss$$yConference website 000007718 8564_ $$904151db2-6164-4335-b4b4-cda9d03af9d8$$s930406$$uhttps://library.imarest.org/record/7718/files/ISCSS%202018%20Paper%20033%20Tesei%20FINAL.pdf