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An adaptive spinal-like controller: tunable biomimetic behavior for a robotic limb.

Filip Stefanovic1, Henrietta L Galiana

  • 1Department of Biomedical Engineering, McGill University, 3775, rue University, Room 316, Montréal, QC H3A 2B4, Canada. filip.stefanovic@mail.mcgill.ca.

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Summary

This study introduces an adaptive spinal-like controller for robotic limbs, enabling human-like movements and adaptable control for complex motor tasks. The controller successfully achieves goal-oriented reaching, even with perturbations, advancing artificial limb technology.

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Area of Science:

  • Robotics
  • Biomimetics
  • Neuroscience

Background:

  • Spinal-like regulators influence complex behaviors in volitional goal-oriented reaching.
  • An adaptive spinal-like controller is developed for robotic limb control.
  • This controller enables biological-like limb movements in simulated robotic arms.

Purpose of the Study:

  • To demonstrate that a simulated robot arm can achieve biological-like limb movements using an adaptive spinal-like controller.
  • To show that controller programmability allows independent spatial and temporal changes for movement tasks.
  • To present the first adaptive spinal-like controller demonstrating complex motor behaviors in multi-joint limb movements.

Main Methods:

  • Evaluation of the controller using a simulated robotic apparatus.
  • Testing with three goal-oriented reaching paradigms: trajectory shaping, perturbation sensitivity, and moving target tracking.
  • Focus on complex motor tasks omitted in earlier studies for improved artificial limb control.

Main Results:

  • The controller achieved targets without a priori planning of trajectories, with dynamics evolving from architecture and spatial error.
  • Curvature amplitude in hand trajectories reduced by up to 98% via gain scaling.
  • Adaptive network behavior enabled successful adaptation to perturbations and tracking of moving targets, producing human-like movements.

Conclusions:

  • The controller demonstrates adaptability to diverse behavioral contexts beyond previous biomimetic studies.
  • This research examines the tunability of the spinal-like controller for complex reaching tasks.
  • The work represents a step towards developing more robust controllers for powered artificial limbs.