Ad hoc Acoustic Network Aided Localization for micro-AUVs

Fenucci, Davide; Sitbon, Jeremy; Neasham, Jeffrey; Phillips, Alexander; Munafò, Andrea. 2022 Ad hoc Acoustic Network Aided Localization for micro-AUVs. Field Robotics, 2 (1). 1888-1919. https://doi.org/10.55417/fr.2022059

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Official URL: http://dx.doi.org/10.55417/fr.2022059

Abstract/Summary

The navigation of Autonomous Underwater Vehicles (AUVs) is still an open research problem. This is further exacerbated when vehicles can only carry limited sensors as typically the case with micro-AUVs that need to survey large marine areas that can be characterized by high currents and dynamic environments. To address this problem, this work investigates the usage of ad hoc acoustic networks that can be established by a set of cooperating vehicles. Leveraging the network structure makes it possible to greatly improve the navigation of the vehicles and as a result to enlarge the operational envelope of vehicles with limited capabilities. The paper details the design and implementation of the network, and specific details of localization and navigation services made available to the vehicles by the network stack. Results are provided from a sea-trial undertaken in Croatia in October 2019. Results validate the approach, demonstrating the increased flexibility of the system and the navigational performance obtained: the deployed network was able to support long-range navigation of vehicles with no inertial navigation or Doppler Velocity Log (DVL) during a 9.5 km channel crossing, reducing the navigation error from approximately 7% to 0.27% of the distance traveled.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.55417/fr.2022059
ISSN:	27713989
Date made live:	18 Oct 2022 17:56 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/533371

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.55417/fr.2022059

ISSN:

27713989

Date made live:

18 Oct 2022 17:56 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/533371