A model of the user's proximity for bayesian inference

E. Torta, R.H. Cuijpers, J.F. Juola

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

8 Citations (Scopus)
114 Downloads (Pure)

Abstract

Embodied nonverbal cues are fundamental for regulating human-human social iteractions. The physical embodiment of robots makes it likely that they will have to exhibit appropriate nonverbal interactive behaviors. In this paper we propose a model of the user's proximity based on a superposition of quasi-Gaussian probability distributions which allows to express findings from HRI trials regarding distances and direction of approach in a human-robot interaction scenario. The way the model is formulated is suitable for well-established Bayesian filtering techniques, and thus the inference of the preferred distance and direction of approach in a human robot interaction scenario can be regarded as a state estimation problem. Results derived from simulations show the effectiveness of the inference process.
Original languageEnglish
Title of host publicationProceedings of the 6th International Conference on Human-Robot Interaction (HRI 2011), March 6-9, 2011
EditorsA. Billard, P. Kahn, J.A, Adams, G. Trafton
Place of PublicationNew York
PublisherAssociation for Computing Machinery, Inc
Pages273-274
ISBN (Print)978-1-4503-0561-7
DOIs
Publication statusPublished - 2011
Event6th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2011) - Lausanne, Switzerland
Duration: 6 Mar 20119 Mar 2011
Conference number: 6

Conference

Conference6th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2011)
Abbreviated titleHRI 2016
Country/TerritorySwitzerland
CityLausanne
Period6/03/119/03/11

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