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

نویسندگان

  • Amir Sadeghipour
  • Ramin Yaghoubzadeh
  • Andreas Rüter
  • Stefan Kopp
چکیده

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.

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تاریخ انتشار 2009