Environment representation for mobile robot localisation

Ranasinghe, R; Dissanayake, G; Furukawa, T; Arukgoda, J; Dantanarayana, L

Environment representation for mobile robot localisation

Ranasinghe, R

Dissanayake, G

Furukawa, T Arukgoda, J Dantanarayana, L

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Publication Type:: Conference Proceeding
Citation:: 2017 IEEE International Conference on Industrial and Information Systems, ICIIS 2017 - Proceedings, 2018, 2018-January pp. 1 - 6
Issue Date:: 2018-02-21

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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	Furukawa, T	en_US
dc.contributor.author	Arukgoda, J	en_US
dc.contributor.author	Dantanarayana, L https://orcid.org/0000-0002-8887-329X	en_US
dc.date.issued	2018-02-21	en_US
dc.identifier.citation	2017 IEEE International Conference on Industrial and Information Systems, ICIIS 2017 - Proceedings, 2018, 2018-January pp. 1 - 6	en_US
dc.identifier.isbn	9781538616741	en_US
dc.identifier.uri	http://hdl.handle.net/10453/124702
dc.description.abstract	© 2017 IEEE. An adequate representation of the environment is an essential component of a mobile robot navigation system. This paper reviews the techniques reported in the literature for capturing the geometry of the space surrounding a mobile robot. In particular, the use of distance functions that combine some of the advantages of feature based and occupancy grid based representations for mobile robot localisation is described in detail. The effectiveness of various distance function based representations is demonstrated using a number of practical examples for localising ground and air vehicles.	en_US
dc.relation.ispartof	2017 IEEE International Conference on Industrial and Information Systems, ICIIS 2017 - Proceedings	en_US
dc.relation.isbasedon	10.1109/ICIINFS.2017.8300384	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Environment representation for mobile robot localisation	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2018-January	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	closed_access	*
pubs.publication-status	Published	en_US
pubs.volume	2018-January	en_US

Abstract:

© 2017 IEEE. An adequate representation of the environment is an essential component of a mobile robot navigation system. This paper reviews the techniques reported in the literature for capturing the geometry of the space surrounding a mobile robot. In particular, the use of distance functions that combine some of the advantages of feature based and occupancy grid based representations for mobile robot localisation is described in detail. The effectiveness of various distance function based representations is demonstrated using a number of practical examples for localising ground and air vehicles.

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http://hdl.handle.net/10453/124702