Planar scan matching using incident angle

Lv, J; Wang, Y; Wu, K; Dissanayake, G; Kobayashi, Y; Xiong, R

Planar scan matching using incident angle

Lv, J Wang, Y Wu, K Dissanayake, G

Kobayashi, Y Xiong, R

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Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Intelligent Robots and Systems, 2017, 2017-September pp. 4049 - 4056
Issue Date:: 2017-12-13

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Field	Value	Language
dc.contributor.author	Lv, J	en_US
dc.contributor.author	Wang, Y	en_US
dc.contributor.author	Wu, K	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.contributor.author	Kobayashi, Y	en_US
dc.contributor.author	Xiong, R	en_US
dc.date.issued	2017-12-13	en_US
dc.identifier.citation	IEEE International Conference on Intelligent Robots and Systems, 2017, 2017-September pp. 4049 - 4056	en_US
dc.identifier.isbn	9781538626825	en_US
dc.identifier.issn	2153-0858	en_US
dc.identifier.uri	http://hdl.handle.net/10453/127484
dc.description.abstract	© 2017 IEEE. The main contribution of this paper is a planar scan matching algorithm that makes use of the incident angle of a scan point as a feature to enhance the robustness to large relative transformations, particularly in orientation. A new definition of the incident angle is introduced and its consistency with respect to relative transformation between scans is demonstrated. A method that uses the Radial distance and Incident Angle (RIA) for scan alignment, that can efficiently estimate the relative transformation between two scans, is proposed. This approach is designed as a preprocessor for fine scan matching and it is able to pre-align scans that have large angular but limited translational displacement. Scans collected with aggressive robot motion in two typical indoor environments as well as benchmark datasets, are used to demonstrate the effectiveness of RIA when compared with a range of scan matching algorithms reported in the literature.	en_US
dc.relation.ispartof	IEEE International Conference on Intelligent Robots and Systems	en_US
dc.relation.isbasedon	10.1109/IROS.2017.8206260	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Planar scan matching using incident angle	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2017-September	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	2017-September	en_US

Abstract:

© 2017 IEEE. The main contribution of this paper is a planar scan matching algorithm that makes use of the incident angle of a scan point as a feature to enhance the robustness to large relative transformations, particularly in orientation. A new definition of the incident angle is introduced and its consistency with respect to relative transformation between scans is demonstrated. A method that uses the Radial distance and Incident Angle (RIA) for scan alignment, that can efficiently estimate the relative transformation between two scans, is proposed. This approach is designed as a preprocessor for fine scan matching and it is able to pre-align scans that have large angular but limited translational displacement. Scans collected with aggressive robot motion in two typical indoor environments as well as benchmark datasets, are used to demonstrate the effectiveness of RIA when compared with a range of scan matching algorithms reported in the literature.

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http://hdl.handle.net/10453/127484