Paper
3 June 2014 An interdisciplinary taxonomy of social cues and signals in the service of engineering robotic social intelligence
Travis J. Wiltshire, Emilio J. Lobato, Jonathan Velez, Florian Jentsch, Stephen M. Fiore
Author Affiliations +
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.
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Travis J. Wiltshire, Emilio J. Lobato, Jonathan Velez, Florian Jentsch, and Stephen M. Fiore "An interdisciplinary taxonomy of social cues and signals in the service of engineering robotic social intelligence", Proc. SPIE 9084, Unmanned Systems Technology XVI, 90840F (3 June 2014); https://doi.org/10.1117/12.2049933
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Cited by 7 scholarly publications.
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KEYWORDS
Sensors

Taxonomy

Robots

Imaging systems

Robotics

Signal detection

Eye

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