Natural landmark-based autonomous navigation using curvature scale space

Madhavan, R; Durrant-Whyte, H; Dissanayake, G

Natural landmark-based autonomous navigation using curvature scale space

Madhavan, R Durrant-Whyte, H Dissanayake, G

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Publication Type:: Conference Proceeding
Citation:: Proceedings-IEEE International Conference on Robotics and Automation, 2002, 4 pp. 3936 - 3941
Issue Date:: 2002-01-01

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Field	Value	Language
dc.contributor.author	Madhavan, R	en_US
dc.contributor.author	Durrant-Whyte, H	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.date.issued	2002-01-01	en_US
dc.identifier.citation	Proceedings-IEEE International Conference on Robotics and Automation, 2002, 4 pp. 3936 - 3941	en_US
dc.identifier.issn	1050-4729	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2843
dc.description.abstract	This paper describes a terrain-aided navigation system that employs points of maximum curvature extracted from laser scan data as primary landmarks. A scale space method is used to extract points of maximum curvature from laser range scans of unmodified outdoor environments. This information is then fused with odometric information to provide localization information for an outdoor vehicle. The method described is invariant to the size and orientation of the range images under consideration (with respect to rotation and translation), is robust to noise, and can reliably detect and localize naturally occurring landmarks in the operating environment. The algorithm is demonstrated in the application of a road vehicle in an unmodified operating domain.	en_US
dc.relation.ispartof	Proceedings-IEEE International Conference on Robotics and Automation	en_US
dc.relation.isbasedon	10.1109/ROBOT.2002.1014342	en_US
dc.title	Natural landmark-based autonomous navigation using curvature scale space	en_US
dc.type	Conference Proceeding
utslib.citation.volume	4	en_US
utslib.for	091007 Manufacturing Robotics and Mechatronics (excl. Automotive Mechatronics)	en_US
utslib.for	090602 Control Systems, Robotics and Automation	en_US
utslib.for	091303 Autonomous Vehicles	en_US
dc.location.activity	Washington DC,USA	en_US
dc.location.activity	WASHINGTON, DC
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	4	en_US

Abstract:

This paper describes a terrain-aided navigation system that employs points of maximum curvature extracted from laser scan data as primary landmarks. A scale space method is used to extract points of maximum curvature from laser range scans of unmodified outdoor environments. This information is then fused with odometric information to provide localization information for an outdoor vehicle. The method described is invariant to the size and orientation of the range images under consideration (with respect to rotation and translation), is robust to noise, and can reliably detect and localize naturally occurring landmarks in the operating environment. The algorithm is demonstrated in the application of a road vehicle in an unmodified operating domain.

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http://hdl.handle.net/10453/2843