Cargando…

A Fast Binocular Localisation Method for AUV Docking

Docking technology plays a critical role in realising the long-time operation of autonomous underwater vehicles (AUVs). In this study, a binocular localisation method for AUV docking is presented. An adaptively weighted OTSU method is developed for feature extraction. The foreground object is extrac...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhong, Lijia, Li, Dejun, Lin, Mingwei, Lin, Ri, Yang, Canjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479930/
https://www.ncbi.nlm.nih.gov/pubmed/30978977
http://dx.doi.org/10.3390/s19071735
_version_ 1783413458870468608
author Zhong, Lijia
Li, Dejun
Lin, Mingwei
Lin, Ri
Yang, Canjun
author_facet Zhong, Lijia
Li, Dejun
Lin, Mingwei
Lin, Ri
Yang, Canjun
author_sort Zhong, Lijia
collection PubMed
description Docking technology plays a critical role in realising the long-time operation of autonomous underwater vehicles (AUVs). In this study, a binocular localisation method for AUV docking is presented. An adaptively weighted OTSU method is developed for feature extraction. The foreground object is extracted precisely without mixing or missing lamps, which is independent of the position of the AUV relative to the station. Moreover, this extraction process is more precise compared to other segmentation methods with a low computational load. The mass centre of each lamp on the binary image is used as matching feature for binocular vision. Using this fast feature matching method, the operation frequency of the binocular localisation method exceeds 10 Hz. Meanwhile, a relative pose estimation method is suggested for instances when the two cameras cannot capture all the lamps. The localisation accuracy of the distance in the heading direction as measured by the proposed binocular vision algorithm was tested at fixed points underwater. A simulation experiment using a ship model has been conducted in a laboratory pool to evaluate the feasibility of the algorithm. The test result demonstrates that the average localisation error is approximately 5 cm and the average relative location error is approximately 2% in the range of 3.6 m. As such, the ship model was successfully guided to the docking station for different lateral deviations.
format Online
Article
Text
id pubmed-6479930
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-64799302019-04-29 A Fast Binocular Localisation Method for AUV Docking Zhong, Lijia Li, Dejun Lin, Mingwei Lin, Ri Yang, Canjun Sensors (Basel) Article Docking technology plays a critical role in realising the long-time operation of autonomous underwater vehicles (AUVs). In this study, a binocular localisation method for AUV docking is presented. An adaptively weighted OTSU method is developed for feature extraction. The foreground object is extracted precisely without mixing or missing lamps, which is independent of the position of the AUV relative to the station. Moreover, this extraction process is more precise compared to other segmentation methods with a low computational load. The mass centre of each lamp on the binary image is used as matching feature for binocular vision. Using this fast feature matching method, the operation frequency of the binocular localisation method exceeds 10 Hz. Meanwhile, a relative pose estimation method is suggested for instances when the two cameras cannot capture all the lamps. The localisation accuracy of the distance in the heading direction as measured by the proposed binocular vision algorithm was tested at fixed points underwater. A simulation experiment using a ship model has been conducted in a laboratory pool to evaluate the feasibility of the algorithm. The test result demonstrates that the average localisation error is approximately 5 cm and the average relative location error is approximately 2% in the range of 3.6 m. As such, the ship model was successfully guided to the docking station for different lateral deviations. MDPI 2019-04-11 /pmc/articles/PMC6479930/ /pubmed/30978977 http://dx.doi.org/10.3390/s19071735 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhong, Lijia
Li, Dejun
Lin, Mingwei
Lin, Ri
Yang, Canjun
A Fast Binocular Localisation Method for AUV Docking
title A Fast Binocular Localisation Method for AUV Docking
title_full A Fast Binocular Localisation Method for AUV Docking
title_fullStr A Fast Binocular Localisation Method for AUV Docking
title_full_unstemmed A Fast Binocular Localisation Method for AUV Docking
title_short A Fast Binocular Localisation Method for AUV Docking
title_sort fast binocular localisation method for auv docking
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479930/
https://www.ncbi.nlm.nih.gov/pubmed/30978977
http://dx.doi.org/10.3390/s19071735
work_keys_str_mv AT zhonglijia afastbinocularlocalisationmethodforauvdocking
AT lidejun afastbinocularlocalisationmethodforauvdocking
AT linmingwei afastbinocularlocalisationmethodforauvdocking
AT linri afastbinocularlocalisationmethodforauvdocking
AT yangcanjun afastbinocularlocalisationmethodforauvdocking
AT zhonglijia fastbinocularlocalisationmethodforauvdocking
AT lidejun fastbinocularlocalisationmethodforauvdocking
AT linmingwei fastbinocularlocalisationmethodforauvdocking
AT linri fastbinocularlocalisationmethodforauvdocking
AT yangcanjun fastbinocularlocalisationmethodforauvdocking