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Iterative Learning Control for Motion Trajectory Tracking of a Circular Soft Crawling Robot.

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Summary

This study introduces a dielectric elastomer actuator (DEA) soft robot for unstructured environments. An iterative learning control (ILC) method achieves excellent motion tracking despite model uncertainties.

Keywords:
ILCdielectric elastomer actuatorelectro-adhesion actuatorknowledge-guided data-driven modelingsoft crawling robot

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Area of Science:

  • Robotics
  • Materials Science
  • Control Systems

Background:

  • Soft robots offer adaptability in unstructured environments due to their deformable structures.
  • Dielectric elastomer actuators (DEAs) are promising soft actuators with large deformation and high energy density.
  • Accurate modeling of DEAs is challenging due to nonlinear electromechanical coupling and viscoelasticity.

Purpose of the Study:

  • To design and develop a soft robot utilizing dielectric elastomer actuators (DEAs).
  • To address the challenge of motion trajectory tracking for DEA-based soft robots with uncertain models.
  • To propose and validate an iterative learning control (ILC) algorithm for precise DEA robot control.

Main Methods:

  • Development of a DEA-based soft robot.
  • Application of a D^2 type iterative learning control (ILC) algorithm for motion trajectory tracking.
  • Utilizing a knowledge-based model framework with kinematic analysis to prove ILC convergence.

Main Results:

  • The proposed D^2 type ILC algorithm demonstrated effective motion trajectory tracking for the DEA soft robot.
  • Simulations and experiments confirmed the excellent tracking performance of the ILC method.
  • The soft crawling robot achieved precise control in its movements.

Conclusions:

  • The developed iterative learning control (ILC) method is effective for DEA-based soft robots.
  • The study validates the use of DEAs in soft robotics for enhanced adaptability and performance.
  • Precise motion control is achievable even with complex nonlinearities and model uncertainties in soft robots.