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A Multimodal Emotional Human-Robot Interaction Architecture for Social Robots Engaged in Bidirectional Communication.

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    Social robots require emotional intelligence for effective human-robot interaction (HRI). An innovative architecture enables robots to display emotions, enhancing user engagement and positive experiences in HRI.

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    Area of Science:

    • Robotics
    • Human-Computer Interaction
    • Affective Computing

    Background:

    • Social robots need to interpret and respond to human emotions for natural interaction.
    • Bidirectional emotional communication is key for engaging human-robot interaction (HRI).

    Purpose of the Study:

    • To present a novel multimodal emotional HRI architecture for natural, engaging bidirectional emotional communication.
    • To implement and evaluate an Emotionally Expressive Robot compared to a Neutral Robot in HRI.

    Main Methods:

    • User affect detection using body language and vocal intonation, classified via Bayesian Network.
    • A two-layer emotional model (deliberative and reactive) for robot emotional response generation.
    • Implementation on a humanoid robot for diet and fitness counseling, with a between-subjects experiment.

    Main Results:

    • Both robots effectively detected user affect in real-time HRI.
    • The Emotionally Expressive Robot appropriately determined its emotional response.
    • The Emotionally Expressive Robot induced more positive user valence and less negative arousal than the Neutral Robot.

    Conclusions:

    • The proposed architecture enables effective emotional expression in social robots.
    • Emotionally expressive robots enhance user experience and emotional state during HRI.
    • This work advances natural and engaging human-robot emotional communication.