Teach-and-repeat path following for an autonomous underwater vehicle

This paper presents a teach-and-repeat path-following method for an autonomous underwater vehicle (AUV) navigating long distances in environments where external navigation aides are denied. This method utilizes sonar images to construct a series of reference views along a path,stored as a topologica...

Full description

Bibliographic Details
Published in:Journal of Field Robotics
Main Authors: King, PD, Vardy, A, Forrest, AL
Format: Article in Journal/Newspaper
Language:English
Published: John Wiley & Sons, Inc. 2018
Subjects:
AUV
Online Access:https://eprints.utas.edu.au/26056/
https://eprints.utas.edu.au/26056/1/ROB-17-0049-R1.pdf
https://doi.org/10.1002/rob.21776
id ftunivtasmania:oai:eprints.utas.edu.au:26056
record_format openpolar
spelling ftunivtasmania:oai:eprints.utas.edu.au:26056 2023-05-15T17:22:26+02:00 Teach-and-repeat path following for an autonomous underwater vehicle King, PD Vardy, A Forrest, AL 2018 application/pdf https://eprints.utas.edu.au/26056/ https://eprints.utas.edu.au/26056/1/ROB-17-0049-R1.pdf https://doi.org/10.1002/rob.21776 en eng John Wiley & Sons, Inc. https://eprints.utas.edu.au/26056/1/ROB-17-0049-R1.pdf King, PD orcid:0000-0001-9436-0936 , Vardy, A and Forrest, AL orcid:0000-0002-7853-9765 2018 , 'Teach-and-repeat path following for an autonomous underwater vehicle' , Journal of Field Robotics , pp. 1-16 , doi:10.1002/rob.21776 <http://dx.doi.org/10.1002/rob.21776>. navigation autonomy AUV sonar computer vision Article PeerReviewed 2018 ftunivtasmania https://doi.org/10.1002/rob.21776 2021-09-13T22:17:08Z This paper presents a teach-and-repeat path-following method for an autonomous underwater vehicle (AUV) navigating long distances in environments where external navigation aides are denied. This method utilizes sonar images to construct a series of reference views along a path,stored as a topological map. The AUV can then renavigate along this path, either to return to the start location or to repeat the route. Utilizing unique assumptions about the sonar image-generation process, this system exhibits robust image-matching capabilities, providing observations to a discrete Bayesian filter that maintains an estimate of progress along the path. Image-matching also provides an estimate of offset from the path, allowing the AUV to correct its heading and effectively close the gap. Over a series of field trials, this system demonstrated online control of an AUV in the ocean environment of Holyrood Arm, Newfoundland and Labrador, Canada. The system was implemented on an International Submarine Engineering Ltd. Explorer AUV and per-formed multiple path completions over both a 1 and 5 km track. These trials illustrated an AUV operating in a fully autonomous mode, in which navigation was driven solely by sensor feedback and adaptive control. Path-following performance was as desired, with the AUV maintaining close offset to the path. Article in Journal/Newspaper Newfoundland University of Tasmania: UTas ePrints Canada Newfoundland Journal of Field Robotics 35 5 748 763
institution Open Polar
collection University of Tasmania: UTas ePrints
op_collection_id ftunivtasmania
language English
topic navigation
autonomy
AUV
sonar
computer vision
spellingShingle navigation
autonomy
AUV
sonar
computer vision
King, PD
Vardy, A
Forrest, AL
Teach-and-repeat path following for an autonomous underwater vehicle
topic_facet navigation
autonomy
AUV
sonar
computer vision
description This paper presents a teach-and-repeat path-following method for an autonomous underwater vehicle (AUV) navigating long distances in environments where external navigation aides are denied. This method utilizes sonar images to construct a series of reference views along a path,stored as a topological map. The AUV can then renavigate along this path, either to return to the start location or to repeat the route. Utilizing unique assumptions about the sonar image-generation process, this system exhibits robust image-matching capabilities, providing observations to a discrete Bayesian filter that maintains an estimate of progress along the path. Image-matching also provides an estimate of offset from the path, allowing the AUV to correct its heading and effectively close the gap. Over a series of field trials, this system demonstrated online control of an AUV in the ocean environment of Holyrood Arm, Newfoundland and Labrador, Canada. The system was implemented on an International Submarine Engineering Ltd. Explorer AUV and per-formed multiple path completions over both a 1 and 5 km track. These trials illustrated an AUV operating in a fully autonomous mode, in which navigation was driven solely by sensor feedback and adaptive control. Path-following performance was as desired, with the AUV maintaining close offset to the path.
format Article in Journal/Newspaper
author King, PD
Vardy, A
Forrest, AL
author_facet King, PD
Vardy, A
Forrest, AL
author_sort King, PD
title Teach-and-repeat path following for an autonomous underwater vehicle
title_short Teach-and-repeat path following for an autonomous underwater vehicle
title_full Teach-and-repeat path following for an autonomous underwater vehicle
title_fullStr Teach-and-repeat path following for an autonomous underwater vehicle
title_full_unstemmed Teach-and-repeat path following for an autonomous underwater vehicle
title_sort teach-and-repeat path following for an autonomous underwater vehicle
publisher John Wiley & Sons, Inc.
publishDate 2018
url https://eprints.utas.edu.au/26056/
https://eprints.utas.edu.au/26056/1/ROB-17-0049-R1.pdf
https://doi.org/10.1002/rob.21776
geographic Canada
Newfoundland
geographic_facet Canada
Newfoundland
genre Newfoundland
genre_facet Newfoundland
op_relation https://eprints.utas.edu.au/26056/1/ROB-17-0049-R1.pdf
King, PD orcid:0000-0001-9436-0936 , Vardy, A and Forrest, AL orcid:0000-0002-7853-9765 2018 , 'Teach-and-repeat path following for an autonomous underwater vehicle' , Journal of Field Robotics , pp. 1-16 , doi:10.1002/rob.21776 <http://dx.doi.org/10.1002/rob.21776>.
op_doi https://doi.org/10.1002/rob.21776
container_title Journal of Field Robotics
container_volume 35
container_issue 5
container_start_page 748
op_container_end_page 763
_version_ 1766109097914007552