Experimental Evaluation of Nearest Neighbor Exploration Approach in Field Environments

Quin, P; Paul, G; Liu, D

Experimental Evaluation of Nearest Neighbor Exploration Approach in Field Environments

Quin, P

Paul, G

Liu, D

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Automation Science and Engineering, 2017, 14 (2), pp. 869 - 880
Issue Date:: 2017-04-01

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Field	Value	Language
dc.contributor.author	Quin, P https://orcid.org/0000-0001-6542-3459	en_US
dc.contributor.author	Paul, G https://orcid.org/0000-0002-3478-0020	en_US
dc.contributor.author	Liu, D https://orcid.org/0000-0002-1581-5582	en_US
dc.date.available	2015-11-22	en_US
dc.date.issued	2017-04-01	en_US
dc.identifier.citation	IEEE Transactions on Automation Science and Engineering, 2017, 14 (2), pp. 869 - 880	en_US
dc.identifier.issn	1545-5955	en_US
dc.identifier.uri	http://hdl.handle.net/10453/124440
dc.description.abstract	© 2017 IEEE. Inspecting surface conditions in 3-D environments such as steel bridges is a complex, time-consuming, and often hazardous undertaking that is an essential part of tasks such as bridge maintenance. Developing an autonomous exploration strategy for a mobile climbing robot would allow for such tasks to be completed more quickly and more safely than is possible with human inspectors. The exploration strategy tested in this paper, called the nearest neighbors exploration approach (NNEA), aims to reduce the overall exploration time by reducing the number of sensor position evaluations that need to be performed. NNEA achieves this by first considering at each time step only a small set of poses near to the current robot as candidates for the next best view. This approach is compared with another exploration strategy for similar robots performing the same task. The improvements between the new and previous strategy are demonstrated through trials on a test rig, and also in field trials on a ferromagnetic bridge structure. Note to Practitioners-This paper was motivated by the problem of inspecting confined spaces for rust and flaking paint with a manipulator robot arm. Existing approaches involve creating a large set of candidate robot poses to take a scan from. Evaluating all these candidate poses is very time consuming if full coverage is guaranteed. This paper suggests a principled method for restricting the size of this set in a way that does not reduce inspection coverage but decreases overall time taken for inspection.	en_US
dc.relation	http://purl.org/au-research/grants/arc/LP100200750
dc.relation.ispartof	IEEE Transactions on Automation Science and Engineering	en_US
dc.relation.isbasedon	10.1109/TASE.2016.2640228	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	Industrial Engineering & Automation	en_US
dc.title	Experimental Evaluation of Nearest Neighbor Exploration Approach in Field Environments	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	14	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0910 Manufacturing 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 Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	open_access	*
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	14	en_US

Abstract:

© 2017 IEEE. Inspecting surface conditions in 3-D environments such as steel bridges is a complex, time-consuming, and often hazardous undertaking that is an essential part of tasks such as bridge maintenance. Developing an autonomous exploration strategy for a mobile climbing robot would allow for such tasks to be completed more quickly and more safely than is possible with human inspectors. The exploration strategy tested in this paper, called the nearest neighbors exploration approach (NNEA), aims to reduce the overall exploration time by reducing the number of sensor position evaluations that need to be performed. NNEA achieves this by first considering at each time step only a small set of poses near to the current robot as candidates for the next best view. This approach is compared with another exploration strategy for similar robots performing the same task. The improvements between the new and previous strategy are demonstrated through trials on a test rig, and also in field trials on a ferromagnetic bridge structure. Note to Practitioners-This paper was motivated by the problem of inspecting confined spaces for rust and flaking paint with a manipulator robot arm. Existing approaches involve creating a large set of candidate robot poses to take a scan from. Evaluating all these candidate poses is very time consuming if full coverage is guaranteed. This paper suggests a principled method for restricting the size of this set in a way that does not reduce inspection coverage but decreases overall time taken for inspection.

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http://hdl.handle.net/10453/124440