Show simple item record Wilson, James 2010-05-19T09:04:09Z 2010-05-19T09:04:09Z 2010-05-19
dc.identifier.citation Wilson , J 2010 , ' A System for Affordance Based learning of Object Grasping in a Robot ' . en
dc.identifier.other PURE: 149888
dc.identifier.other PURE UUID: 459e5eab-c9d6-42bc-bea1-582b6533500f
dc.identifier.other dspace: 2160/4647
dc.identifier.other DSpace_20121128.csv: row: 3606
dc.description null Sponsorship: ROSSI en
dc.description.abstract A system is described which takes synergies extracted from human grasp experiments and maps these onto a robot vision and hand-arm platform to facilitate the transfer of skills \cite{tao2010}. This system forms part of a framework which is extended by adding a self organizing map based affordance learning system. This affordance system learns the correlations between perceived object features and relevant motor outputs expressed in the form of synergies, and comes to guide grasping of an object by predicting the appropriate synergy outputs for a given object. It does so online and autonomously. Preliminary results test its effectiveness in this role and show that it is capable of learning fast and in spite of noise. en
dc.language.iso eng
dc.rights en
dc.title A System for Affordance Based learning of Object Grasping in a Robot en
dc.type /dk/atira/pure/researchoutput/researchoutputtypes/contributiontoconference/paper en
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Intelligent Robotics Group en
dc.description.status Non peer reviewed en

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