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Rhythm Patterns Interaction - Synchronization Behavior for Human-Robot Joint Action

Author

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  • Alexander Mörtl
  • Tamara Lorenz
  • Sandra Hirche

Abstract

Interactive behavior among humans is governed by the dynamics of movement synchronization in a variety of repetitive tasks. This requires the interaction partners to perform for example rhythmic limb swinging or even goal-directed arm movements. Inspired by that essential feature of human interaction, we present a novel concept and design methodology to synthesize goal-directed synchronization behavior for robotic agents in repetitive joint action tasks. The agents’ tasks are described by closed movement trajectories and interpreted as limit cycles, for which instantaneous phase variables are derived based on oscillator theory. Events segmenting the trajectories into multiple primitives are introduced as anchoring points for enhanced synchronization modes. Utilizing both continuous phases and discrete events in a unifying view, we design a continuous dynamical process synchronizing the derived modes. Inverse to the derivation of phases, we also address the generation of goal-directed movements from the behavioral dynamics. The developed concept is implemented to an anthropomorphic robot. For evaluation of the concept an experiment is designed and conducted in which the robot performs a prototypical pick-and-place task jointly with human partners. The effectiveness of the designed behavior is successfully evidenced by objective measures of phase and event synchronization. Feedback gathered from the participants of our exploratory study suggests a subjectively pleasant sense of interaction created by the interactive behavior. The results highlight potential applications of the synchronization concept both in motor coordination among robotic agents and in enhanced social interaction between humanoid agents and humans.

Suggested Citation

  • Alexander Mörtl & Tamara Lorenz & Sandra Hirche, 2014. "Rhythm Patterns Interaction - Synchronization Behavior for Human-Robot Joint Action," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-17, April.
  • Handle: RePEc:plo:pone00:0095195
    DOI: 10.1371/journal.pone.0095195
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