Abstract
The paper presents an affective model for social robotics, where the robot is capable of behavior adaptation, in accordance with the needs and preferences of a particular user. The proposed approach differs from other studies in human-robot interaction as these usually have been using the ‘Wizard of Oz’ technique, where a person remotely operates a robot. On the other side, simulated robots are not able of personalized behaviors and behave according to the preprogrammed set of rules. We provide a tool to personalize affective artificial behaviors in cooperative human—robot scenarios, where human emotion recognition, appropriate robotic behavior selection and expression of robotic emotions play a key role. The preliminary experiments show that the personalized affective robotic behavior can achieve better results in a scenario in which a robot motivates children in learning. We believe that human—robot interfaces which mimic how humans interact with one another in an empathic way could ultimately lead to robots being accepted in the wider domain.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Ros, R., Nalin, M., Wood, R., Baxter, P., Looije, R., Demiris, Y., Pozzi, C.: Child—robot interaction in the wild: advice to the aspiring experimenter. In: Proceedings of the 13th International Conference on Multimodal Interfaces, pp. 335–342. ACM (2011)
Gates, B.: A robot in every home. Scientific American 296(1), 58–65 (2007)
Keen, S.: Empathy and the Novel. Oxford University Press (2007)
Kozima, H., Nakagawa, C., Yano, H.: Can a robot empathize with people? Artificial Life and Robotics 8, 83–88 (2004)
Cramer, H., Goddijn, J., Wielinga, B., Evers, V.: Effects of (in)accurate empathy and situational valence on attitudes towards robots. In: ACM/IEEE Int. Conf. on Human— Robot Interaction, pp. 141–142. ACM (2010)
Hoffman, M.: Empathy and moral development: Implications for caring and justice. Cambridge Univ. Press (2001)
Goleman, D.: The Brain and Emotional Intelligence: New Insights, More Than Sound (2011) ISBN 978-1-93444-115-2
Vircikova, M., Pala, M., Smolar, P., Sincak, P.: Neural Approach for Personalised Emotional Model in Human-Robot Interaction. In: WCCI 2012: IEEE World Congress on Computational Intelligence, Brisbane, Australia, June 10-15, pp. 970–977. IEEE (2012) ISBN 978-1-4673-1489-3
Hess, U., Blairy, S.: Facial mimicry and emotional contagion to dynamic emotional facial expressions and their influence on decoding accuracy. International Journal of Psychophysiology 40, 129–141 (2001)
Bernieri, F.J., Rosenthal, R.: Interpersonal coordination: behavior matching and interactional syn-chrony. In: Feldman, R.S., Rimé, B. (eds.) Fundamentals of Nonverbal Behavior, pp. 401–432. Cambridge University Press, Cambridge (1991)
Chartrand, T.L., Bargh, J.A.: The chameleon effect: the perception–behavior link and social interac-tion. Journal of Personality and Social Psychology 76, 893–910 (1999)
LaFrance, M., Broadbent, M.: Group report: posture sharing as a nonverbal indicator. Group and Organization Studies 1, 328–333 (2009)
Yabar, Y., Hess, C., Display, U.: of empathy and perception of out—group members. New Zealand Journal of Psychology 36, 42–50 (2006)
Bourgeois, P., Hess, U.: The impact of social context on mimicry. Biological Psychology 77, 343–352 (2008)
Lanzetta, J., Englis, T., Expectations, B.G.: of cooperation and competition and their effects on observ-ers’ vicarious emotional responses. Journal of Personality and Social Psychology 56, 543–554 (1989)
Weyers, P., Muehlberger, A., Kund, A., Hess, U., Pauli, P.: Modulation of facial reactions to avatar emotional faces by nonconscious competition priming. Psychophysiology 46, 328–335 (2009)
Oh, K., Kim, M.: Social Attributes of Robotic Products: Observations of Child— Robot Interactions in a School Environment. International Journal of Design 4(1) (2010)
Vircikova, M.: Machine Empathy: Towards Artificial Emotional Intelligence with Active Personalization in Social Human Robot Interaction. PhD. Thesis, Technical University of Kosice, Slovakia (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Vircikova, M., Magyar, G., Sincak, P. (2015). The Affective Loop: A Tool for Autonomous and Adaptive Emotional Human-Robot Interaction. In: Kim, JH., Yang, W., Jo, J., Sincak, P., Myung, H. (eds) Robot Intelligence Technology and Applications 3. Advances in Intelligent Systems and Computing, vol 345. Springer, Cham. https://doi.org/10.1007/978-3-319-16841-8_23
Download citation
DOI: https://doi.org/10.1007/978-3-319-16841-8_23
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16840-1
Online ISBN: 978-3-319-16841-8
eBook Packages: EngineeringEngineering (R0)