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...
Published in: | Journal of Field Robotics |
---|---|
Main Authors: | , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
John Wiley & Sons, Inc.
2018
|
Subjects: | |
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 |