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Visual appearance modulates motor control in social interactions.

Stephan de la Rosa1, Tobias Meilinger2, Stephan Streuber3

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Human motor control adapts to an interaction partner's visual appearance, even when movements are identical. This suggests distinct motor control principles for human versus robot interactions.

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Area of Science:

  • Human-Computer Interaction
  • Robotics
  • Motor Control

Background:

  • Adaptive technologies aim for natural human-device interaction.
  • Understanding factors influencing natural interaction is crucial.
  • Current motor control theories prioritize kinematics over visual appearance.

Purpose of the Study:

  • To investigate if human motor control is influenced by the visual appearance of an interaction partner.
  • To determine if visual cues affect movement execution during social interactions.

Main Methods:

  • A novel mixed reality setup was used.
  • Participants performed a high-five interaction with human-like and robot-like avatars.
  • Movement trajectories and responses to perturbations were analyzed.

Main Results:

  • Movement trajectories and adjustments to perturbations differed based on avatar visual appearance.
  • Identical movements by both avatars did not yield identical motor responses.
  • Established motor control theories (minimum jerk, two-thirds power law) better predicted robot interaction trajectories.

Conclusions:

  • Human motor control is sensitive to the visual likeness of an interaction partner.
  • This sensitivity suggests different motor control principles apply to human-directed versus object-directed interactions.
  • Findings have implications for designing more natural and intuitive human-robot interactions.