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Perception of a Social Robot’s Mood Based on Different Types of Motions and Coloured Heart

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 12483)


Roboticists in the field of Social Robotics try to find ways to develop robots that are able to create emotional bonds with the users and interact in natural ways. In order to achieve this, one of the features that the robot requires is the ability to convey different moods. This can be done by changing how the robot uses its output interfaces, like motors or LED. In this paper, we present a user study in which 164 participants rated their perception of a robot’s mood considering different types of body movements and heartbeat. Also, because verbal communication can convey a lot of information about the robot’s mood, we try to measure the relevance of verbal communication in relation to the perceived robot’s mood. Participants were divided in five groups where the speed and amplitude of the robot’s movements, as well as the LED configuration of the robot’s heart, changed. Results show that the modulation of the interfaces had an effect on the intensity of the mood perceived, but not big enough to change which mood the participants perceived.


  • Emotion expression
  • Expressiveness modulation
  • Human-robot interaction
  • Multimodal interaction

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Fig. 2.


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    A playlist with all the videos used in the experiment can be seen here:


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The research leading to these results has received funding from the projects: Development of social robots to help seniors with cognitive impairment (ROBSEN), funded by the Ministerio de Economía y Competitividad; and Robots Sociales para Estimulación Física, Cognitiva y Afectiva de Mayores (ROSES), funded by the Ministerio de Ciencia, Innovación y Universidades.

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Correspondence to Enrique Fernández-Rodicio .

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Fernández-Rodicio, E., Castro-González, Á., Gamboa-Montero, J.J., Salichs, M.A. (2020). Perception of a Social Robot’s Mood Based on Different Types of Motions and Coloured Heart. In: , et al. Social Robotics. ICSR 2020. Lecture Notes in Computer Science(), vol 12483. Springer, Cham.

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