NDLI: Computational Analysis of Motionese Toward Scaffolding Robot Action Learning

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Computational Analysis of Motionese Toward Scaffolding Robot Action Learning

Content Provider	IEEE Xplore Digital Library
Author	Nagai, Y. Rohlfing, K.J.
Copyright Year	2009
Abstract	A difficulty in robot action learning is that robots do not know where to attend when observing action demonstration. Inspired by human parent-infant interaction, we suggest that parental action demonstration to infants, called motionese, can scaffold robot learning as well as infants'. Since infants' knowledge about the context is limited, which is comparable to robots, parents are supposed to properly guide their attention by emphasizing the important aspects of the action. Our analysis employing a bottom-up attention model revealed that motionese has the effects of highlighting the initial and final states of the action, indicating significant state changes in it, and underlining the properties of objects used in the action. Suppression and addition of parents' body movement and their frequent social signals to infants produced these effects. Our findings are discussed toward designing robots that can take advantage of parental teaching.
Starting Page	44
Ending Page	54
Page Count	11
File Size	1013151
File Format	PDF
ISSN	19430604
Volume Number	1
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Motion analysis Pediatrics Robot sensing systems Human robot interaction Educational robots Education Acceleration Europe Cognition Cognitive robotics robot action learning Bottom-up visual attention motionese parental scaffolding
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Software

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