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

  • Amir Sadeghipour
  • Ramin Yaghoubzadeh
  • Andreas Rüter
  • Stefan Kopp
Part of the Cognitive Systems Monographs book series (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.

Keywords

Forward Model Inverse Model Motor Command Hand Gesture Motor Program 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Amir Sadeghipour
    • 1
  • Ramin Yaghoubzadeh
    • 1
  • Andreas Rüter
    • 1
  • Stefan Kopp
    • 1
  1. 1.Sociable Agents Group, CITECBielefeld University 

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