Teach‐and‐repeat path following for an autonomous underwater vehicle
Abstract 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...
Published in: | Journal of Field Robotics |
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crwiley:10.1002/rob.21776 2024-06-02T08:10:45+00:00 Teach‐and‐repeat path following for an autonomous underwater vehicle King, Peter Vardy, Andrew Forrest, Alexander L. Research and Development Corporation of Newfoundland and Labrador Atlantic Canada Opportunities Agency Australian Research Council 2018 http://dx.doi.org/10.1002/rob.21776 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Frob.21776 https://onlinelibrary.wiley.com/doi/pdf/10.1002/rob.21776 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/rob.21776 https://onlinelibrary.wiley.com/doi/am-pdf/10.1002/rob.21776 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#am http://onlinelibrary.wiley.com/termsAndConditions#vor Journal of Field Robotics volume 35, issue 5, page 748-763 ISSN 1556-4959 1556-4967 journal-article 2018 crwiley https://doi.org/10.1002/rob.21776 2024-05-03T10:58:47Z Abstract 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 performed 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 Wiley Online Library Canada Newfoundland Journal of Field Robotics 35 5 748 763 |
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English |
description |
Abstract 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 performed 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. |
author2 |
Research and Development Corporation of Newfoundland and Labrador Atlantic Canada Opportunities Agency Australian Research Council |
format |
Article in Journal/Newspaper |
author |
King, Peter Vardy, Andrew Forrest, Alexander L. |
spellingShingle |
King, Peter Vardy, Andrew Forrest, Alexander L. Teach‐and‐repeat path following for an autonomous underwater vehicle |
author_facet |
King, Peter Vardy, Andrew Forrest, Alexander L. |
author_sort |
King, Peter |
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 |
Wiley |
publishDate |
2018 |
url |
http://dx.doi.org/10.1002/rob.21776 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Frob.21776 https://onlinelibrary.wiley.com/doi/pdf/10.1002/rob.21776 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/rob.21776 https://onlinelibrary.wiley.com/doi/am-pdf/10.1002/rob.21776 |
geographic |
Canada Newfoundland |
geographic_facet |
Canada Newfoundland |
genre |
Newfoundland |
genre_facet |
Newfoundland |
op_source |
Journal of Field Robotics volume 35, issue 5, page 748-763 ISSN 1556-4959 1556-4967 |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#am http://onlinelibrary.wiley.com/termsAndConditions#vor |
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 |
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1800756656409149440 |