Sensing for Autonomous Navigation Inside Steel Bridges

Ranasinghe, R; Dissanayake, G; Liu, D

Sensing for Autonomous Navigation Inside Steel Bridges

Ranasinghe, R

Dissanayake, G

Liu, D

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Publication Type:: Conference Proceeding
Citation:: Proceedings of IEEE Sensors, 2018, 2018-October
Issue Date:: 2018-12-26

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Field	Value	Language
dc.contributor.author	Ranasinghe, R https://orcid.org/0000-0002-3785-3723	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.contributor.author	Liu, D https://orcid.org/0000-0002-1581-5582	en_US
dc.date.issued	2018-12-26	en_US
dc.identifier.citation	Proceedings of IEEE Sensors, 2018, 2018-October	en_US
dc.identifier.isbn	9781538647073	en_US
dc.identifier.issn	1930-0395	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133466
dc.description.abstract	© 2018 IEEE. The main contribution of this paper is a strategy to build a map of a bridge structure and estimate the precise location of a robot within it. In particular, the focus is on the autonomous navigation of a robot inside the steel arches that support the Sydney Harbour Bridge. A two dimensional laser range finder sensor, rotated about an axis perpendicular to its spin axis is used to capture the geometry of the environment in the form of a set of three-dimensional points; a point cloud. First, the approximate robot location is estimated by exploiting the fact that the environment predominantly consists of planes. Using this location estimate as an initial guess, the iterative closest point (ICP) algorithm is used to align point clouds obtained from nearby locations. Results from the ICP, together with a simultaneous localisation and mapping algorithm is then used to obtain accurate estimates of the locations of all the poses from where information is gathered, as well as a complete map of the environment. Results from experiments are used to demonstrate the effectiveness of proposed techniques.	en_US
dc.relation.ispartof	Proceedings of IEEE Sensors	en_US
dc.relation.isbasedon	10.1109/ICSENS.2018.8589784	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Sensing for Autonomous Navigation Inside Steel Bridges	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2018-October	en_US
utslib.for	0913 Mechanical Engineering	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	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	closed_access	*
pubs.publication-status	Published	en_US
pubs.volume	2018-October	en_US

Abstract:

© 2018 IEEE. The main contribution of this paper is a strategy to build a map of a bridge structure and estimate the precise location of a robot within it. In particular, the focus is on the autonomous navigation of a robot inside the steel arches that support the Sydney Harbour Bridge. A two dimensional laser range finder sensor, rotated about an axis perpendicular to its spin axis is used to capture the geometry of the environment in the form of a set of three-dimensional points; a point cloud. First, the approximate robot location is estimated by exploiting the fact that the environment predominantly consists of planes. Using this location estimate as an initial guess, the iterative closest point (ICP) algorithm is used to align point clouds obtained from nearby locations. Results from the ICP, together with a simultaneous localisation and mapping algorithm is then used to obtain accurate estimates of the locations of all the poses from where information is gathered, as well as a complete map of the environment. Results from experiments are used to demonstrate the effectiveness of proposed techniques.

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http://hdl.handle.net/10453/133466