Skip to main content

Social Motorics – Towards an Embodied Basis of Social Human-Robot Interaction

  • Chapter
Human Centered Robot Systems

Part of the book series: Cognitive Systems Monographs ((COSMOS,volume 6))

Abstract

In this paper we present a biologically-inspired model for social behavior recognition and generation. Based on an unified sensorimotor representation, it integrates hierarchical motor knowledge structures, probabilistic forward models for predicting observations, and inverse models for motor learning. With a focus on hand gestures, results of initial evaluations against real-world data are presented.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Amit, R., Mataric, M.: Learning movement sequences from demonstration. In: ICDL 2002: Proceedings of the 2nd International Conference on Development and Learning, pp. 203–208 (2002)

    Google Scholar 

  2. Botvinick, M.M.: Hierarchical models of behavior and prefrontal function. Trends in Cognitive Sciences 12(5), 201–208 (2008), http://www.sciencedirect.com/science/article/B6VH9-4S95WHD-1/2/f02cfdf1fde7f8df4f4d2d52da7acd7b

    Article  Google Scholar 

  3. Breazeal, C., Buchsbaum, D., Gray, J., Gatenby, D., Blumberg, B.: Learning from and about others: Towards using imitation to bootstrap the social understanding of others by robots. Artificial Life 11(1-2), 31–62 (2005), http://dx.doi.org/10.1162/1064546053278955

    Article  Google Scholar 

  4. Calinon, S., Billard, A.: Recognition and Reproduction of Gestures using a Probabilistic Framework Combining PCA, ICA and HMM. In: 22nd International Conference on Machine Learning, pp. 105–112 (2005)

    Google Scholar 

  5. Dautenhahn, K.: Socially intelligent robots: Dimensions of human - robot interaction. Philosophical Transactions of the Royal Society B: Biological Sciences 362(1480), 679–704 (2007)

    Article  Google Scholar 

  6. Dijksterhuis, A., Bargh, J.: The perception-behavior expressway: Automatic effects of social perception on social behavior. Advances in Experimental Social Psychology 33, 1–40 (2001)

    Article  Google Scholar 

  7. Chen, F.-S., Fu, C.-M., Huang, C.L.: Hand gesture recognition using a real-time tracking method and hidden markov models. Image and Vision Computing 21, 745–758 (2003)

    Article  Google Scholar 

  8. Hamilton, A., Grafton, S.: The motor hierarchy: From kinematics to goals and intentions. In: Attention and Performance, vol. 22. Oxford University Press, Oxford (2007)

    Google Scholar 

  9. Haruno, M., Wolpert, D.M., Kawato, M.: Mosaic model for sensorimotor learning and control. Neural Computation 13(10), 2201–2220 (2001), http://www.mitpressjournals.org/doi/abs/10.1162/089976601750541778

    Article  MATH  Google Scholar 

  10. Haruno, M., Wolpert, D.M., Kawato, M.: Hierarchical mosaic for movement generation. International Congress Series 1250, 575–590 (2003), http://www.sciencedirect.com/science/article/B7581-49N7DHR-1J/2/83e9a135a8a183a9f18da5a66dcd3bbf ; Cognition and emotion in the brain. Selected topics of the International Symposium on Limbic and Association Cortical Systems

    Article  Google Scholar 

  11. Johnson, M., Demiris, Y.: Hierarchies of coupled inverse and forward models for abstraction in robot action planning, recognition and imitation. In: Proceedings of the AISB 2005 Symposium on Imitation in Animals and Artifacts (2005)

    Google Scholar 

  12. Kopp, S., Graeser, O.: Imitation learning and response facilitation in embodied agents. In: Gratch, J., Young, M., Aylett, R.S., Ballin, D., Olivier, P. (eds.) IVA 2006. LNCS (LNAI), vol. 4133, pp. 28–41. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  13. Kopp, S., Wachsmuth, I.: Synthesizing multimodal utterances for conversational agents. Journal of Computer Animation and Virtual Worlds 15(1), 39–52 (2004)

    Article  Google Scholar 

  14. Kopp, S., Wachsmuth, I., Bonaiuto, J., Arbib, M.: Imitation in embodied communication – from monkey mirror neurons to artificial humans. In: Wachsmuth, I., Lenzen, M., Knoblich, G. (eds.) Embodied Communication in Humans and Machines, pp. 357–390. Oxford University Press, Oxford (2008)

    Google Scholar 

  15. Natalie Sebanz, G.K.: The role of the mirror system in embodied communication. In: Wachsmuth, I., Lenzen, M., Knoblich, G. (eds.) Embodied Communication in Humans and Machines, ch. 7, pp. 129–149. Oxford University Press, Oxford (2008)

    Google Scholar 

  16. Schutz-Bosbach, S., Prinz, W.: Perceptual resonance: action-induced modulation of perception. Journal of Trends in Cognitive Sciences 11(8), 349–355 (2007)

    Article  Google Scholar 

  17. Wolpert, D.M., Doya, K., Kawato, M.: A unifying computational framework for motor control and social interaction. Philos Trans. R. Soc. Lond. B. Biol. Sci. 358(1431), 593–602 (2003), http://dx.doi.org/10.1098/rstb.2002.1238

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Sadeghipour, A., Yaghoubzadeh, R., Rüter, A., Kopp, S. (2009). Social Motorics – Towards an Embodied Basis of Social Human-Robot Interaction. In: Ritter, H., Sagerer, G., Dillmann, R., Buss, M. (eds) Human Centered Robot Systems. Cognitive Systems Monographs, vol 6. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10403-9_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-10403-9_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10402-2

  • Online ISBN: 978-3-642-10403-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics