Journal of Intelligent & Robotic Systems

, Volume 82, Issue 1, pp 101–133

A Survey of Autonomous Human Affect Detection Methods for Social Robots Engaged in Natural HRI

  • Derek McColl
  • Alexander Hong
  • Naoaki Hatakeyama
  • Goldie Nejat
  • Beno Benhabib
Article

DOI: 10.1007/s10846-015-0259-2

Cite this article as:
McColl, D., Hong, A., Hatakeyama, N. et al. J Intell Robot Syst (2016) 82: 101. doi:10.1007/s10846-015-0259-2

Abstract

In Human-Robot Interactions (HRI), robots should be socially intelligent. They should be able to respond appropriately to human affective and social cues in order to effectively engage in bi-directional communications. Social intelligence would allow a robot to relate to, understand, and interact and share information with people in real-world human-centered environments. This survey paper presents an encompassing review of existing automated affect recognition and classification systems for social robots engaged in various HRI settings. Human-affect detection from facial expressions, body language, voice, and physiological signals are investigated, as well as from a combination of the aforementioned modes. The automated systems are described by their corresponding robotic and HRI applications, the sensors they employ, and the feature detection techniques and affect classification strategies utilized. This paper also discusses pertinent future research directions for promoting the development of socially intelligent robots capable of recognizing, classifying and responding to human affective states during real-time HRI.

Keywords

Human-robot interactions Affect classification models Automated affect detection Facial expressions Body language Voice Physiological signals Multi-modal 

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Derek McColl
    • 2
  • Alexander Hong
    • 1
    • 2
  • Naoaki Hatakeyama
    • 2
  • Goldie Nejat
    • 2
  • Beno Benhabib
    • 1
  1. 1.Computer Integrated Manufacturing Laboratory, Department of Mechanical and Industrial EngineeringUniversity of TorontoTorontoCanada
  2. 2.Autonomous Systems and Biomechatronics Laboratory, Department of Mechanical and Industrial EngineeringUniversity of TorontoTorontoCanada

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