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Updated: Jan 18, 2026

Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs
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Force-velocity coupling limits human adaptation in physical human-robot interaction.

Mahdiar Edraki1, Hélène Serré2, Pauline Maurice3

  • 1Department of Mechanical and Industrial Engineering, Northeastern University, Boston, USA. edraki.m@northeastern.edu.

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|January 16, 2026
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Summary
This summary is machine-generated.

Humans adapt to robot movement, but non-biological velocity profiles increase interaction forces. Learning and visual feedback help humans compensate for these forces in physical human-robot interaction.

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Area of Science:

  • Robotics
  • Human-Computer Interaction
  • Biomechanics

Background:

  • Physical human-robot interaction requires mutual adaptation for synergistic behavior.
  • Human movement naturally scales velocity with trajectory curvature.
  • Understanding human responses to robot motion is crucial for safe and efficient collaboration.

Purpose of the Study:

  • To investigate human responses to robots employing different velocity profiles during physical interaction.
  • To determine how robot velocity impacts interaction forces and human adaptation.
  • To explore the role of biomechanical constraints and learning in human-robot force modulation.

Main Methods:

  • Two experiments involved humans tracking a robot moving along an elliptical path with varying velocity profiles.
  • Participants were instructed to minimize interaction forces.
  • Data analysis focused on involuntary forces, angular velocities, and adaptation over practice sessions with and without visual feedback.

Main Results:

  • Higher involuntary forces were observed when robots moved at constant velocity or exaggerated biological velocity-curvature scaling.
  • Increased robot angular velocity correlated with greater tangential and normal interaction forces.
  • Interaction forces decreased for non-biological profiles with real-time visual feedback, indicating learned compensation for inertial forces.

Conclusions:

  • Robot velocity profiles significantly influence human interaction forces and adaptation.
  • Biomechanical constraints play a minor role; human motor learning and prediction are key factors.
  • Designing robots with adaptable velocity profiles considering human motor capabilities is essential for effective physical human-robot interaction, especially in collaborative and wearable robotics.