Spatial Learning and Localization in Animals: A Computational Model and Its Implications for Mobile Robots

dc.contributor.author Balakrishnan, Karthik
dc.contributor.author Bousquet, Olivier
dc.contributor.department Computer Science
dc.date 2018-02-13T22:08:43.000
dc.date.accessioned 2020-06-30T01:56:31Z
dc.date.available 2020-06-30T01:56:31Z
dc.date.issued 1997-09-24
dc.description.abstract <p>The ability to acquire a representation of spatial environment and the ability to localize within it are essential for successful navigation in a-priori unknown environments. The hippocampal formation is believed to play a key role in spatial learning and navigation in animals. This paper briefly reviews the relevant neurobiological and cognitive data and their relation to computational models of spatial learning and localization used in mobile robots. It also describes a hippocampal model of spatial learning and navigation and analyzes it using Kalman filter based tools for information fusion from multiple uncertain sources. The resulting model allows a robot to learn a place-based, metric representation of space in a-priori unknown environments and to localize itself in a stochastically optimal manner. The paper also describes an algorithmic implementation of the model and results of several experiments that demonstrate its capabilities.</p>
dc.identifier archive/lib.dr.iastate.edu/cs_techreports/30/
dc.identifier.articleid 1019
dc.identifier.contextkey 5239470
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath cs_techreports/30
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/20128
dc.source.bitstream archive/lib.dr.iastate.edu/cs_techreports/30/TR97_20.pdf|||Fri Jan 14 23:26:48 UTC 2022
dc.subject.disciplines Artificial Intelligence and Robotics
dc.subject.disciplines Theory and Algorithms
dc.subject.keywords spatial learning
dc.subject.keywords spatial localization
dc.subject.keywords place learning
dc.subject.keywords place recognition
dc.subject.keywords navigation
dc.subject.keywords animal navigation
dc.subject.keywords hippocampus
dc.subject.keywords Kalman filter
dc.subject.keywords probabilistic localization
dc.subject.keywords dead-reckoning
dc.subject.keywords spatial maps
dc.subject.keywords topological maps
dc.subject.keywords metric maps
dc.title Spatial Learning and Localization in Animals: A Computational Model and Its Implications for Mobile Robots
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isOrgUnitOfPublication f7be4eb9-d1d0-4081-859b-b15cee251456
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