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Creating Expressive Social Robots That Convey Symbolic and Spontaneous Communication.

Enrique Fernández-Rodicio1, Álvaro Castro-González1, Juan José Gamboa-Montero1

  • 1RoboticsLab, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, Av. de la Universidad 30, 28911 Madrid, Spain.

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Summary
This summary is machine-generated.

This study introduces a new method for robot expressiveness, combining symbolic and spontaneous communication. Modulating robot emotions enhances human-robot interaction and user perception.

Keywords:
affective state expressionexpressiveness managementhuman–robot interactionmultimodal interaction

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Area of Science:

  • Robotics
  • Human-Computer Interaction
  • Affective Computing

Background:

  • Robots are increasingly used in human-interacting roles.
  • Effective human-robot interaction (HRI) requires robots to communicate both information and emotional states.
  • Current robots often lack the ability to convey spontaneous emotional expressions.

Purpose of the Study:

  • To present a novel method for modeling robot expressiveness by combining symbolic and spontaneous communication dimensions.
  • To develop an expressiveness architecture integrating predefined multimodal expressions and mood modulation strategies.
  • To experimentally validate the impact of spontaneous communication on human perception of social robots.

Main Methods:

  • A method for modeling robot expressiveness using independent symbolic and spontaneous dimensions.
  • An architecture employing predefined multimodal expressions for symbolic communication.
  • Integration of modulation strategies to convey robot mood and emotions.
  • Experimental validation of the proposed architecture's performance.

Main Results:

  • The proposed expressiveness architecture effectively conveys both symbolic and spontaneous communication.
  • Modulation strategies significantly improve users' perception of social robots.
  • The fusion of symbolic and spontaneous dimensions leads to recognizable affective states in robots.

Conclusions:

  • The developed method and architecture enhance robot expressiveness by integrating symbolic and spontaneous communication.
  • Modulation strategies are crucial for improving user perception and conveying robot emotions in HRI.
  • This work advances the development of more engaging and relatable social robots.