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dc.contributor.author Hülse, Martin Siegfried
dc.contributor.author McBride, Sebastian Daryl
dc.contributor.author Lee, Mark Howard
dc.date.accessioned 2009-08-14T10:31:05Z
dc.date.available 2009-08-14T10:31:05Z
dc.date.issued 2010-03
dc.identifier.citation Hülse , M S , McBride , S D & Lee , M H 2010 , ' Fast learning mapping schemes for robotic hand-eye coordination ' Cognitive Computation , vol 2 , no. 1 , pp. 1 - 16 . , 10.1007/s12559-009-9030-y en
dc.identifier.issn 1866-9956
dc.identifier.other PURE: 114954
dc.identifier.other dspace: 2160/2861
dc.identifier.uri http://hdl.handle.net/2160/2861
dc.description Huelse, M., McBride, S. D., Lee, M. (2010). Fast learning mapping schemes for robotic hand-eye coordination. Cognitive Computation, 2 (1), 1 - 16. Sponsorship: This work was supported by EU-FP7 projects IM-CLeVeR and ROSSI,and by EPSRC, UK through grant EP/C516303/1. en
dc.description.abstract In aiming for advanced robotic systems that autonomously and permanently readapt to changing and uncertain environments,we introduce a scheme of fast learning and readaptation of robotic sensorimotor mappings based on biological mechanisms underpinning the development and maintenance of accurate human reaching. The study presents a range of experiments, using two distinct computational architectures, on both learning and realignment of robotic hand-eye coordination. Analysis of the results provide insights into the putative parameters and mechanisms required for fast readaptation and generalization from both a robotic and biological perspective. en
dc.format.extent 16 en
dc.language.iso eng
dc.relation.ispartof Cognitive Computation en
dc.subject Hand–eye coordination en
dc.subject Mapping en
dc.subject Cross-modal en
dc.subject Robotics en
dc.subject Realignment en
dc.subject Learning en
dc.title Fast learning mapping schemes for robotic hand-eye coordination en
dc.type Text en
dc.type.publicationtype Article (Journal) en
dc.identifier.doi http://dx.doi.org/10.1007/s12559-009-9030-y
dc.contributor.institution Intelligent Robotics Group en
dc.contributor.institution Department of Computer Science en
dc.description.status Peer reviewed en


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