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Proceedings Paper

An interdisciplinary taxonomy of social cues and signals in the service of engineering robotic social intelligence
Author(s): Travis J. Wiltshire; Emilio J. Lobato; Jonathan Velez; Florian Jentsch; Stephen M. Fiore
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Paper Abstract

Understanding intentions is a complex social-cognitive task for humans, let alone machines. In this paper we discuss how the developing field of Social Signal Processing, and assessing social cues to interpret social signals, may help to develop a foundation for robotic social intelligence. We describe a taxonomy to further R&D in HRI and facilitate natural interactions between humans and robots. This is based upon an interdisciplinary framework developed to integrate: (1) the sensors used for detecting social cues, (2) the parameters for differentiating and classifying differing levels of those cues, and (3) how sets of social cues indicate specific social signals. This is necessarily an iterative process, as technologies improve and social science researchers better understand the complex interactions of vast quantities of social cue combinations. As such, the goal of this paper is to advance a taxonomy of this nature to further stimulate interdisciplinary collaboration in the development of advanced social intelligence that mutually informs areas of robotic perception and intelligence.

Paper Details

Date Published: 3 June 2014
PDF: 15 pages
Proc. SPIE 9084, Unmanned Systems Technology XVI, 90840F (3 June 2014); doi: 10.1117/12.2049933
Show Author Affiliations
Travis J. Wiltshire, Univ. of Central Florida (United States)
Emilio J. Lobato, Univ. of Central Florida (United States)
Jonathan Velez, Univ. of Central Florida (United States)
Florian Jentsch, Univ. of Central Florida (United States)
Stephen M. Fiore, Univ. of Central Florida (United States)


Published in SPIE Proceedings Vol. 9084:
Unmanned Systems Technology XVI
Robert E. Karlsen; Douglas W. Gage; Charles M. Shoemaker; Grant R. Gerhart, Editor(s)

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