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dc.contributor.authorAlissandrakis, A.
dc.contributor.authorNehaniv, C.L.
dc.contributor.authorDautenhahn, K.
dc.contributor.authorSaunders, J.
dc.date.accessioned2007-07-09T14:40:57Z
dc.date.available2007-07-09T14:40:57Z
dc.date.issued2005
dc.identifier.citationAlissandrakis , A , Nehaniv , C L , Dautenhahn , K & Saunders , J 2005 , An Approach for Programming Robots by Demonstration: Generalization Across Different Initial Configurations of Manipulated Objects . in In: Procs of the IEEE Computational Intelligence in Robotics and Automata CIRA 2005, Proceedings . Institute of Electrical and Electronics Engineers (IEEE) , pp. 61-66 . https://doi.org/10.1109/CIRA.2005.1554255
dc.identifier.otherdspace: 2299/186
dc.identifier.urihttp://hdl.handle.net/2299/186
dc.descriptionCopyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. DOI : 10.1109/CIRA.2005.1554255
dc.description.abstractImitation is a powerful learning tool that can be used by a robotic agent to socially learn new skills and tasks. One of the fundamental problems in imitation is the correspondence problem, how to map between the actions, states and effects of the model and imitator agents, when the embodiment of the agents is dissimilar. In our approach, the matching depends on different metrics and granularity. Focusing on object manipulation and arrangement demonstrated by a human, this paper presents JABBERWOCKY, a system that uses different metrics and granularity to produce action command sequences that when executed by an imitating agent can achieve corresponding effects (manipulandum absolute/relative position, displacement, rotation and orientation). Based on a single demonstration of an object manipulation task by a human and using a combination of effect metrics, the system is shown to produce correspondence solutions that are then performed by an imitating agent, generalizing with respect to different initial object positions and orientations in the imitator's workspace. Depending on the particular metrics and granularity used, the corresponding effects will differ (shown in examples), making the appropriate choice of metrics and granularity depend on the task and context.en
dc.format.extent5128604
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartofIn: Procs of the IEEE Computational Intelligence in Robotics and Automata CIRA 2005, Proceedings
dc.subjectComputer Science
dc.titleAn Approach for Programming Robots by Demonstration: Generalization Across Different Initial Configurations of Manipulated Objectsen
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionScience & Technology Research Institute
rioxxterms.versionofrecord10.1109/CIRA.2005.1554255
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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