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Terrain-aided navigation for long-range AUVs in dynamic under-mapped environments

Terrain-aided navigation for long-range AUVs in dynamic under-mapped environments
Terrain-aided navigation for long-range AUVs in dynamic under-mapped environments
Deploying long-range Autonomous Underwater Vehicles (AUVs) mid-water column in the deep ocean is one of the most challenging applications for these submersibles. Without ex ternal support and speed over the ground measurements, Dead-Reckoning (DR) navigation inevitably experiences an error proportional to the mission range and the speed of the water currents. In response to this problem, a computationally feasible and low-power Terrain Aided Navigation (TAN) system is developed. A Rao-Blackwellized Particle Filter (RBPF) robust to estimation divergence is designed to estimate the vehicle’s position and the speed of water currents. To evaluate performance, field data from multi-day AUV deployments in the Southern Ocean are used. These form a unique test case for assessing the TAN performance under extremely challenging conditions. Despite the use of a small number of low-power sensors and a Doppler Velocity Log (DVL) to enable TAN, the algorithm limits the localisation error to within a few hundreds of metres, as opposed to a DR error of 40 km, given a 50 m resolution bathymetric map. To evaluate further the effectiveness of the system under a varying map quality, grids of 100 m, 200 m and 400 m resolution are gen erated by sub-sampling the original 50 m resolution map. Despite the high complexity of the navigation problem, the filter exhibits robust and relatively accurate behaviour. Given the current aim of the oceanographic community to develop maps of similar resolution, the results of this work suggest that TAN can enable AUV operations of the order of months using global bathymetric models.
1556-4959
Salavasidis, Georgios
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Fenucci, Davide
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Prampart, Thomas
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Smart, Micheal
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Pebody, Miles
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Phillips, Alexander B.
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Munafo, Andrea
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Harris, Catherine A.
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Templeton, Robert
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Roper, Daniel T.
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Abrahamsen, Povl E.
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Rogers, Eric
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Salavasidis, Georgios
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Fenucci, Davide
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Prampart, Thomas
1558533d-c49c-43ad-9db6-2bab65cb9234
Smart, Micheal
439cc7c9-b1b9-4fe9-9cfc-a91ec17dc744
Pebody, Miles
34f26387-344c-4457-b24e-4399162acfca
Phillips, Alexander B.
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Munafo, Andrea
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Harris, Catherine A.
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Templeton, Robert
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Roper, Daniel T.
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Abrahamsen, Povl E.
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Rogers, Eric
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Salavasidis, Georgios, Fenucci, Davide, Prampart, Thomas, Smart, Micheal, Pebody, Miles, Phillips, Alexander B., Munafo, Andrea, Harris, Catherine A., Templeton, Robert, Roper, Daniel T., Abrahamsen, Povl E. and Rogers, Eric (2020) Terrain-aided navigation for long-range AUVs in dynamic under-mapped environments. Journal of Field Robotics. (In Press)

Record type: Article

Abstract

Deploying long-range Autonomous Underwater Vehicles (AUVs) mid-water column in the deep ocean is one of the most challenging applications for these submersibles. Without ex ternal support and speed over the ground measurements, Dead-Reckoning (DR) navigation inevitably experiences an error proportional to the mission range and the speed of the water currents. In response to this problem, a computationally feasible and low-power Terrain Aided Navigation (TAN) system is developed. A Rao-Blackwellized Particle Filter (RBPF) robust to estimation divergence is designed to estimate the vehicle’s position and the speed of water currents. To evaluate performance, field data from multi-day AUV deployments in the Southern Ocean are used. These form a unique test case for assessing the TAN performance under extremely challenging conditions. Despite the use of a small number of low-power sensors and a Doppler Velocity Log (DVL) to enable TAN, the algorithm limits the localisation error to within a few hundreds of metres, as opposed to a DR error of 40 km, given a 50 m resolution bathymetric map. To evaluate further the effectiveness of the system under a varying map quality, grids of 100 m, 200 m and 400 m resolution are gen erated by sub-sampling the original 50 m resolution map. Despite the high complexity of the navigation problem, the filter exhibits robust and relatively accurate behaviour. Given the current aim of the oceanographic community to develop maps of similar resolution, the results of this work suggest that TAN can enable AUV operations of the order of months using global bathymetric models.

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Terrain-aided navigation for long-range AUVs in dynamic under-mapped environments - Accepted Manuscript
Restricted to Repository staff only until 6 October 2021.
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Accepted/In Press date: 6 October 2020

Identifiers

Local EPrints ID: 445766
URI: http://eprints.soton.ac.uk/id/eprint/445766
ISSN: 1556-4959
PURE UUID: 0c818151-ce37-4c24-b706-d0a13d1f29c1
ORCID for Eric Rogers: ORCID iD orcid.org/0000-0003-0179-9398

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Date deposited: 07 Jan 2021 17:33
Last modified: 07 Jan 2021 17:33

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Contributors

Author: Georgios Salavasidis
Author: Davide Fenucci
Author: Thomas Prampart
Author: Micheal Smart
Author: Miles Pebody
Author: Alexander B. Phillips
Author: Andrea Munafo
Author: Catherine A. Harris
Author: Robert Templeton
Author: Daniel T. Roper
Author: Povl E. Abrahamsen
Author: Eric Rogers ORCID iD

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