Automated robotic monitoring and inspection of steel structures and bridges

La, HM; Dinh, TH; Pham, NH; Ha, QP; Pham, AQ

Automated robotic monitoring and inspection of steel structures and bridges

La, HM Dinh, TH Pham, NH Ha, QP

Pham, AQ

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Publication Type:: Journal Article
Citation:: Robotica, 2019, 37 (5), pp. 947 - 967
Issue Date:: 2019-05-01

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Field	Value	Language
dc.contributor.author	La, HM	en_US
dc.contributor.author	Dinh, TH	en_US
dc.contributor.author	Pham, NH	en_US
dc.contributor.author	Ha, QP https://orcid.org/0000-0003-0978-1758	en_US
dc.contributor.author	Pham, AQ	en_US
dc.date.available	2020-05-25T19:13:58Z
dc.date.issued	2019-05-01	en_US
dc.identifier.citation	Robotica, 2019, 37 (5), pp. 947 - 967	en_US
dc.identifier.issn	0263-5747	en_US
dc.identifier.uri	http://hdl.handle.net/10453/135676
dc.description.abstract	© 2018 Cambridge University Press. This paper presents visual and 3D structure inspection for steel structures and bridges using a developed climbing robot. The robot can move freely on a steel surface, carry sensors, collect data and then send to the ground station in real-time for monitoring as well as further processing. Steel surface image stitching and 3D map building are conducted to provide a current condition of the structure. Also, a computer vision-based method is implemented to detect surface defects on stitched images. The effectiveness of the climbing robot's inspection is tested in multiple circumstances to ensure strong steel adhesion and successful data collection. The detection method was also successfully evaluated on various test images, where steel cracks could be automatically identified, without the requirement of some heuristic reasoning.	en_US
dc.relation.ispartof	Robotica	en_US
dc.relation.isbasedon	10.1017/S0263574717000601	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	Industrial Engineering & Automation	en_US
dc.title	Automated robotic monitoring and inspection of steel structures and bridges	en_US
dc.type	Journal Article
utslib.citation.volume	5	en_US
utslib.citation.volume	37	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0913 Mechanical Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CBI - Centre for Built Infrastructure
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access	*
pubs.issue	5	en_US
pubs.publication-status	Published	en_US
pubs.volume	37	en_US

Abstract:

© 2018 Cambridge University Press. This paper presents visual and 3D structure inspection for steel structures and bridges using a developed climbing robot. The robot can move freely on a steel surface, carry sensors, collect data and then send to the ground station in real-time for monitoring as well as further processing. Steel surface image stitching and 3D map building are conducted to provide a current condition of the structure. Also, a computer vision-based method is implemented to detect surface defects on stitched images. The effectiveness of the climbing robot's inspection is tested in multiple circumstances to ensure strong steel adhesion and successful data collection. The detection method was also successfully evaluated on various test images, where steel cracks could be automatically identified, without the requirement of some heuristic reasoning.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/132298