A high‐resolution AUV navigation framework with integrated communication and tracking for under‐ice deployments

dc.contributor.author Randeni, Supun
dc.contributor.author Schneider, Toby
dc.contributor.author Bhatt, EeShan C.
dc.contributor.author Víquez, Oscar A.
dc.contributor.author Schmidt, Henrik
dc.date.accessioned 2023-05-24T17:04:11Z
dc.date.available 2023-05-24T17:04:11Z
dc.date.issued 2022-11-16
dc.description © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Randeni, S., Schneider, T., Bhatt, E., Viquez, O., & Schmidt, H. A high-resolution AUV navigation framework with integrated communication and tracking for under-ice deployments. Journal of Field Robotics, 40(2), (2022): 346-367, https://doi.org/10.1002/rob.22133.
dc.description.abstract We developed an environmentally adaptive under‐ice navigation framework that was deployed in the Arctic Beaufort Sea during the United States Navy Ice Exercise in March 2020 (ICEX20). This navigation framework contained two subsystems developed from the ground up: (1) an on‐board hydrodynamic model‐aided navigation (HydroMAN) engine, and (2) an environmentally and acoustically adaptive integrated communication and navigation network (ICNN) that provided acoustic navigation aiding to the former. The HydroMAN synthesized measurements from an inertial navigation system (INS), ice‐tracking Doppler velocity log (DVL), ICNN and pressure sensor into its self‐calibrating vehicle flight dynamic model to compute the navigation solution. The ICNN system, which consisted of four ice buoys outfitted with acoustic modems, trilaterated the vehicle position using the one‐way‐travel‐times (OWTT) of acoustic datagrams transmitted by the autonomous underwater vehicle (AUV) and received by the ice buoy network. The ICNN digested salinity and temperature information to provide model‐assisted real‐time OWTT range conversion to deliver accurate acoustic navigation updates to the HydroMAN. To decouple the contributions from the HydroMAN and ICNN subsystems towards a stable navigation solution, this article evaluates them separately: (1) HydroMAN was compared against DVL bottom‐track aided INS during pre‐ICEX20 engineering trials where both systems provided similar accuracy; (2) ICNN was evaluated by conducting a static experiment in the Arctic where the ICNN navigation updates were compared against GPS with ICNN error within low tens of meters. The joint HydroMAN‐ICNN framework was tested during ICEX20, which provided a nondiverging high‐resolution navigation solution—with the majority of error below 15 m—that facilitated a successful AUV recovery through a small ice hole after an 11 km untethered run in the upper and mid‐water column.
dc.description.sponsorship This work was funded by the Office of Naval Research, Code 322OA. SR was funded by the Battelle-MIT postdoctoral fellowship program; ECB was funded by the National Defense Science and Engineering Graduate Fellowship.
dc.identifier.citation Randeni, S., Schneider, T., Bhatt, E., Viquez, O., & Schmidt, H. (2022). A high-resolution AUV navigation framework with integrated communication and tracking for under-ice deployments. Journal of Field Robotics, 40(2), 346-367.
dc.identifier.doi 10.1002/rob.22133
dc.identifier.uri https://hdl.handle.net/1912/66250
dc.publisher Wiley
dc.relation.uri https://doi.org/10.1002/rob.22133
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/ *
dc.subject Acoustic communication
dc.subject Autonomous underwater vehicles
dc.subject Extended Kalman filter
dc.subject Real-time model-aided navigation
dc.subject Sensor fusion
dc.title A high‐resolution AUV navigation framework with integrated communication and tracking for under‐ice deployments
dc.type Article
dspace.entity.type Publication
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