International Conference on Social Robotics

Social Robotics pp 31-40 | Cite as

A Reactive Competitive Emotion Selection System

  • Julian M. Angel Fernandez
  • Andrea Bonarini
  • Lola Cañamero
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9388)

Abstract

We present a reactive emotion selection system designed to be used in a robot that needs to respond autonomously to relevant events. A variety of emotion selection models based on “cognitive appraisal” theories exist, but the complexity of the concepts used by most of these models limits their use in robotics. Robots have physical constrains that condition their understanding of the world and limit their capacity to built the complex concepts needed for such models. The system presented in this paper was conceived to respond to “disturbances” detected in the environment through a stream of images, and use this low-level information to update emotion intensities. They are increased when specific patterns, based on Tomkins’ affect theory, are detected or reduced when it is not. This system could also be used as part of (or as first step in the incremental design of) a more cognitively complex emotional system for autonomous robots.

Keywords

Social robotics Human Robot Interaction Emotional models Emotion production 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Angel F., J.M., Bonarini, A.: Towards an autonomous theatrical robot. In: ACII 2013, pp. 689–694 (2013)Google Scholar
  2. 2.
    Angel Fernandez, J.M., Bonarini, A.: TheatreBot: a software architecture for a theatrical robot. In: Natraj, A., Cameron, S., Melhuish, C., Witkowski, M. (eds.) TAROS 2013. LNCS, vol. 8069, pp. 446–457. Springer, Heidelberg (2014) Google Scholar
  3. 3.
    Breazeal, C.: Affective interaction between humans and robots. In: Sosík, P., Kelemen, J. (eds.) ECAL 2001. LNCS (LNAI), vol. 2159, pp. 582–591. Springer, Heidelberg (2001) CrossRefGoogle Scholar
  4. 4.
    Breazeal, C.: Designing Sociable Robots. MIT Press, Cambridge (2002) Google Scholar
  5. 5.
    Canamero, L., Fredslund, J.: I show you how I like you-can you read it in my face? IEEE Transactions on Systems, Man and Cybernetics, Part A 31(5) (2001)Google Scholar
  6. 6.
    Caamero, L.: Emotion understanding from the perspective of autonomous robots research. Neural Networks 18(4), 445–455 (2005). emotion and BrainCrossRefGoogle Scholar
  7. 7.
    Dias, J., Mascarenhas, S., Paiva, A.: FAtiMA modular: towards an agent architecture with a generic appraisal framework. In: Bosse, T., Broekens, J., Dias, J., van der Zwaan, J. (eds.) Emotion Modeling. LNCS, vol. 8750, pp. 43–55. Springer, Heidelberg (2014) Google Scholar
  8. 8.
    Ekman, P.: Emotions Revealed : Recognizing Faces and Feelings to Improve Communication and Emotional Life. Owl Books, March 2004Google Scholar
  9. 9.
    Esau, N., Kleinjohann, L., Kleinjohann, B.: Emotional communication with the robot head MEXI. In: Proceedings of Ninth International Conference on Control, Automation, Robotics and Vision, ICARCV 2006, Singapore, December 5–8, 2006, pp. 1–7 (2006)Google Scholar
  10. 10.
    Gratch, J., Marsella, S.: A domain-independent framework for modeling emotion. Journal of Cognitive Systems Research 5, 269–306 (2004)CrossRefGoogle Scholar
  11. 11.
    Izard, C.: Four systems for emotion activation: cognitive and noncognitive processes. Psychological Review, 68–90 (1993)Google Scholar
  12. 12.
  13. 13.
    Lee-Johnson, C.P., Carnegie, D.A.: Emotion-based parameter modulation for a hierarchical mobile robot planning and control architecture. In: 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, October 29 – November 2, 2007. Sheraton Hotel and Marina, San Diego, pp. 2839–2844 (2007)Google Scholar
  14. 14.
    Malfaz, M., Salichs, M.A.: A new approach to modeling emotions and their use on a decision-making system for artificial agents. IEEE Transactions on Affective Computing 3(1), 56–68 (2012)CrossRefGoogle Scholar
  15. 15.
    Marsella, S.C., Gratch, J., Petta, P.: Computational models of emotion. In: Scherer, K.R., Bnziger, T., Roesch, T. (eds.) A blueprint for an affectively competent agent: Cross-fertilization between Emotion Psychology, Affective Neuroscience, and Affective Computing. Oxford University Press, Oxford (2010)Google Scholar
  16. 16.
    Ortony, A., Clore, G.L., Collins, A.: The cognitive structure of emotions. Cambridge Univ. Press, Cambridge (1994). http://opac.inria.fr/record=b1125551, autre tirage: 1999Google Scholar
  17. 17.
    Russell, J.A.: A circumplex model of affect. Journal of Personality and Social Psychology 39, 1161–1178 (1980)CrossRefGoogle Scholar
  18. 18.
    Scherer, K.R.: Appraisal considered as a process of multi-level sequential checking, pp. 92–120. Oxford University Press, New York (2001)Google Scholar
  19. 19.
    Scherer, K.R.: A Blueprint for Affective Computing, chap. Theoretical approaches to teh study of emotion in humans and machines, pp. 21–46. Oxford University Press (2010)Google Scholar
  20. 20.
    Tomkins, S.S.: Affect theory. Approaches to emotion, pp. 163–195 (1984)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Julian M. Angel Fernandez
    • 1
    • 2
  • Andrea Bonarini
    • 1
  • Lola Cañamero
    • 2
  1. 1.Dipartimento di Elettronica, Informazione e BioingegneriaPolitecnico di MilanoMilanoItaly
  2. 2.Embodied Emotion, Cognition and (Inter-)Action Lab, School of Computer ScienceUniversity of HertfordshireHatfield, HertsUK

Personalised recommendations