Modeling of honest signals for human robot interaction

Muhammad Attamimi, Yusuke Katakami, Kasumi Abe, Takayuki Nagai, Tomoaki Nakamura

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Recent studies have shown that human beings unconsciously use signals that represent their thoughts and/or intentions when communicating with each other. These signals are known as honest signals. This study involves the use of a sociometer to capture multimodal data resulting from the interaction between humans. These data are then used to model the interaction using a multimodal hierarchical Dirichlet process hidden Markov model, which is then implemented in the robot. The model enables robots to generate honest signals and to interact in a natural manner.

Original languageEnglish
Title of host publicationHRI 2016 - 11th ACM/IEEE International Conference on Human Robot Interaction
PublisherIEEE Computer Society
Pages415-416
Number of pages2
ISBN (Electronic)9781467383707
DOIs
Publication statusPublished - 12 Apr 2016
Externally publishedYes
Event11th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2016 - Christchurch, New Zealand
Duration: 7 Mar 201610 Mar 2016

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
Volume2016-April
ISSN (Electronic)2167-2148

Conference

Conference11th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2016
Country/TerritoryNew Zealand
CityChristchurch
Period7/03/1610/03/16

Keywords

  • Honest signals
  • Multimodal categorization
  • Robot behavior design
  • Unsupervised learning

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