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2016 | OriginalPaper | Buchkapitel

Personalization Framework for Adaptive Robotic Feeding Assistance

verfasst von : Gerard Canal, Guillem Alenyà, Carme Torras

Erschienen in: Social Robotics

Verlag: Springer International Publishing

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Abstract

The deployment of robots at home must involve robots with pre-defined skills and the capability of personalizing their behavior by non-expert users. A framework to tackle this personalization is presented and applied to an automatic feeding task. The personalization involves the caregiver providing several examples of feeding using Learning-by-Demostration, and a ProMP formalism to compute an overall trajectory and the variance along the path. Experiments show the validity of the approach in generating different feeding motions to adapt to user’s preferences, automatically extracting the relevant task parameters. The importance of the nature of the demonstrations is also assessed, and two training strategies are compared.

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Vorheriges Kapitel Adaptive Robot Assisted Therapy Using Interactive Reinforcement Learning

Nächstes Kapitel A Framework for Modelling Local Human-Robot Interactions Based on Unsupervised Learning

A video showing the process of the personalized feeding task can be found at www.iri.upc.edu/groups/perception/frameworkFUTE.

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Titel: Personalization Framework for Adaptive Robotic Feeding Assistance
verfasst von: Gerard Canal
Guillem Alenyà
Carme Torras
Verlag: Springer International Publishing
Buch: Social Robotics
Print ISBN: 978-3-319-47436-6

Electronic ISBN: 978-3-319-47437-3

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-47437-3_3

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