Bio-mimetic path integration using a self organizing population of grid cells

Sinha, A; Wang, JJ

Bio-mimetic path integration using a self organizing population of grid cells

Sinha, A Wang, JJ

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, 8681 LNCS pp. 675 - 682
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Sinha, A	en_US
dc.contributor.author	Wang, JJ https://orcid.org/0000-0002-6282-0456	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, 8681 LNCS pp. 675 - 682	en_US
dc.identifier.isbn	9783319111780	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/121082
dc.description.abstract	Grid cells in the dorsocaudal medial entorhinal cortex (dMEC) of the rat provide a metric representation of the animal's local environment. The collective firing patterns in a network of grid cells forms a triangular mesh that accurately tracks the location of the animal. The activity of a grid cell network, similar to head direction cells, displays path integration characteristics. Classical robotics use path integrators in the form of inertial navigation systems to track spatial information of an agent as well. In this paper, we describe an implementation of a network of grid cells as a dead reckoning system for the PR2 robot. © 2014 Springer International Publishing Switzerland.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-319-11179-7_85	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Bio-mimetic path integration using a self organizing population of grid cells	en_US
dc.type	Conference Proceeding
utslib.citation.volume	8681 LNCS	en_US
utslib.for	1099 Other Technology	en_US
utslib.for	090904 Navigation and Position Fixing	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 Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CBI - Centre for Built Infrastructure
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	8681 LNCS	en_US

Abstract:

Grid cells in the dorsocaudal medial entorhinal cortex (dMEC) of the rat provide a metric representation of the animal's local environment. The collective firing patterns in a network of grid cells forms a triangular mesh that accurately tracks the location of the animal. The activity of a grid cell network, similar to head direction cells, displays path integration characteristics. Classical robotics use path integrators in the form of inertial navigation systems to track spatial information of an agent as well. In this paper, we describe an implementation of a network of grid cells as a dead reckoning system for the PR2 robot. © 2014 Springer International Publishing Switzerland.

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http://hdl.handle.net/10453/121082