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Related Experiment Video

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Sliding Mode Control of Steerable Needles.

D Caleb Rucker1, Jadav Das2, Hunter B Gilbert3

  • 1Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235 USA ( daniel.c.rucker@vanderbilt.edu ).

IEEE Transactions on Robotics : a Publication of the IEEE Robotics and Automation Society
|November 18, 2014
PubMed
Summary

A new control law enables precise steering of flexible needles for medical diagnosis and therapy. This method accurately guides needles to targets within tissue, even with movement, enhancing robotic surgery capabilities.

Keywords:
Image-guided interventionsmedical roboticsneedle steeringnonholonomic systemssliding mode controlsurgical robotics

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Area of Science:

  • Robotics
  • Medical Imaging
  • Control Systems

Background:

  • Steerable needles offer improved accuracy for minimally invasive procedures.
  • Precise control of needle tip trajectory is crucial for effective diagnosis and therapy delivery.
  • Current methods may require extensive model knowledge or computational resources.

Purpose of the Study:

  • To propose a novel sliding mode control law for steerable needles.
  • To enable accurate delivery of a flexible needle tip to a desired point or trajectory within tissue.
  • To demonstrate robustness and minimal computational requirements of the control strategy.

Main Methods:

  • Development of a sliding mode control law for a flexible asymmetric-tipped needle.
  • Utilizing medical image information for real-time needle guidance.
  • Testing the control law on phantom tissue and ex vivo liver models.
  • Evaluating performance for target point delivery and trajectory tracking.

Main Results:

  • The proposed control law successfully guided the needle tip to desired targets and trajectories.
  • Experimental validation was achieved in phantom and ex vivo liver tissues.
  • The control strategy demonstrated robustness against disturbances from moving targets and tissue deformation.
  • The method requires no prior model parameter knowledge and has bounded input speeds.

Conclusions:

  • The novel sliding mode control law provides accurate and robust steering of flexible needles.
  • This approach enhances the potential for image-guided needle-based interventions.
  • The control strategy is computationally efficient and adaptable to dynamic environments.