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Repetitive Control for Multi-Joint Arm Movements Based on Virtual Trajectories.

Yoji Uno1, Takehiro Suzuki2, Takahiro Kagawa3

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This study introduces a new virtual trajectory control method for multi-joint arm reaching movements. The algorithm effectively updates virtual trajectories, achieving desired arm movements within 10 trials using repetitive control.

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Area of Science:

  • Robotics
  • Biomechanics
  • Control Systems

Background:

  • The neuromuscular model explains limb movement via muscle equilibrium.
  • Virtual trajectory control is key for accurate robotic arm movements.
  • Designing effective virtual trajectories is a significant challenge.

Purpose of the Study:

  • To develop and evaluate a virtual trajectory control algorithm for multi-joint arm reaching movements.
  • To implement a proportional-derivative feedback control scheme within the virtual trajectory framework.
  • To propose an iterative method for updating virtual trajectories without explicit arm dynamics calculation.

Main Methods:

  • Developed a novel algorithm for updating virtual trajectories in repetitive control, inspired by Newton-like methods.
  • Implemented a proportional-derivative feedback control scheme for multi-joint arm reaching.
  • Validated the approach using computer simulations of a two-link arm trajectory tracking task.

Main Results:

  • The proposed repetitive control method successfully updated virtual trajectories.
  • Desired arm trajectories were achieved with high accuracy within approximately 10 iterative trials.
  • Performance was contingent on sufficiently high feedback gains and small sampling times.

Conclusions:

  • The developed virtual trajectory control algorithm enables accurate trajectory tracking for multi-joint arms.
  • The method demonstrates effective convergence to desired trajectories through iterative updates.
  • A modification technique allows for flexible control by adapting to changing feedback gains.