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Deep Koopman Approach for Nonlinear Dynamics and Control of Tendon-Driven Continuum Robots.

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This summary is machine-generated.

This study introduces a novel deep Koopman approach for efficient modeling of tendon-driven continuum robots (TDCRs). The method enables accurate real-time control for medical applications, overcoming complex nonlinear dynamics.

Keywords:
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Area of Science:

  • Robotics
  • Control Theory
  • Applied Mathematics

Background:

  • Tendon-driven continuum robots (TDCRs) are valuable in medicine for their flexibility.
  • Modeling TDCR dynamics is challenging due to nonlinear, computationally intensive continuum mechanics.
  • Real-time control of TDCRs is hindered by these complex models.

Purpose of the Study:

  • To develop an efficient, control-oriented model for TDCR nonlinear dynamics.
  • To leverage the deep Koopman approach for linearizing complex system dynamics.
  • To enable precise real-time position control of TDCRs.

Main Methods:

  • Applied the deep Koopman approach to transform TDCR states into a nonlinear manifold.
  • Approximated autonomous dynamics linearly with a bilinear input term within the Koopman framework.
  • Implemented position control using a linear quadratic controller on the linearized Koopman model.

Main Results:

  • The proposed model accurately captures nonlinearities and space-dependent spectral variations.
  • Experimental validation on a dual-tendon robotic catheter showed low position tracking errors (1.64 mm and 0.60 mm).
  • The approach demonstrated effectiveness for both multi-sinusoidal and sinusoidal trajectories.

Conclusions:

  • The deep Koopman approach offers an efficient and accurate method for modeling TDCR dynamics.
  • This technique facilitates real-time control of TDCRs in medical applications.
  • The study highlights the potential for broad applicability across various TDCR systems.