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A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics

Author

Listed:
  • Lorenzo Cominelli

    (Research Center “E. Piaggio”, Faculty of Engineering, University of Pisa, 56122 Pisa, Italy)

  • Nicola Carbonaro

    (Research Center “E. Piaggio”, Faculty of Engineering, University of Pisa, 56122 Pisa, Italy
    Department of Information Engineering, University of Pisa, 56122 Pisa, Italy)

  • Daniele Mazzei

    (Research Center “E. Piaggio”, Faculty of Engineering, University of Pisa, 56122 Pisa, Italy
    Department of Computer Science, University of Pisa, 56127 Pisa, Italy)

  • Roberto Garofalo

    (Research Center “E. Piaggio”, Faculty of Engineering, University of Pisa, 56122 Pisa, Italy)

  • Alessandro Tognetti

    (Research Center “E. Piaggio”, Faculty of Engineering, University of Pisa, 56122 Pisa, Italy
    Department of Information Engineering, University of Pisa, 56122 Pisa, Italy)

  • Danilo De Rossi

    (Research Center “E. Piaggio”, Faculty of Engineering, University of Pisa, 56122 Pisa, Italy
    Department of Information Engineering, University of Pisa, 56122 Pisa, Italy)

Abstract

In this work, we present an unobtrusive and non-invasive perception framework based on the synergy between two main acquisition systems: the Touch-Me Pad, consisting of two electronic patches for physiological signal extraction and processing; and the Scene Analyzer, a visual-auditory perception system specifically designed for the detection of social and emotional cues. It will be explained how the information extracted by this specific kind of framework is particularly suitable for social robotics applications and how the system has been conceived in order to be used in human-robot interaction scenarios.

Suggested Citation

  • Lorenzo Cominelli & Nicola Carbonaro & Daniele Mazzei & Roberto Garofalo & Alessandro Tognetti & Danilo De Rossi, 2017. "A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics," Future Internet, MDPI, vol. 9(3), pages 1-17, August.
    • Handle: RePEc:gam:jftint:v:9:y:2017:i:3:p:42-:d:106567
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