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Title:	Joining high-level symbolic planning with low-level motion primitives in adaptive HRI: application to dressing assistance
Author:	Canal Camprodon, Gerard; Pignat, Emmanuel; Alenyà Ribas, Guillem; Calinon, Sylvain; Torras, Carme
Other authors:	Institut de Robòtica i Informàtica Industrial; Universitat Politècnica de Catalunya. ROBiri - Grup de Robòtica de l'IRI
Abstract:	© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Abstract:	For a safe and successful daily living assistance, far from the highly controlled environment of a factory, robots should be able to adapt to ever-changing situations. Programming such a robot is a tedious process that requires expert knowledge. An alternative is to rely on a high-level planner, but the generic symbolic representations used are not well suited to particular robot executions. Contrarily, motion primitives encode robot motions in a way that can be easily adapted to different situations. This paper presents a combined framework that exploits the advantages of both approaches. The number of required symbolic states is reduced, as motion primitives provide
Abstract:	Peer Reviewed
Subject(s):	-Àrees temàtiques de la UPC::Informàtica::Robòtica -intelligent robots -service robots -Physical Human-Robot Interaction -Learning from Demonstration -Symbolic Task Planning -Shoe fitting. -Classificació INSPEC::Automation::Robots::Intelligent robots
Rights:	Attribution-NonCommercial-NoDerivs 3.0 Spain http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Document type:	Article - Submitted version Conference Object
Published by:	Institute of Electrical and Electronics Engineers (IEEE)
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