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Related Experiment Video

Updated: Jun 5, 2026

Rod-based Fabrication of Customizable Soft Robotic Pneumatic Gripper Devices for Delicate Tissue Manipulation
07:49

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Published on: August 2, 2016

Mechanics of Flexible Needles Robotically Steered through Soft Tissue.

S Misra1, K B Reed, B W Schafer

  • 1University of Twente, Enschede, The Netherlands.

The International Journal of Robotics Research
|December 21, 2010
PubMed
Summary

This study presents a mechanics-based model for robotic needle steering, predicting how bevel-tip needles bend in soft tissue. This model uses fundamental properties, enabling more accurate path planning for medical procedures.

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Area of Science:

  • Robotics
  • Biomedical Engineering
  • Mechanical Engineering

Background:

  • Robotic needle steering utilizes bevel-tip needle asymmetry for controlled insertion into soft tissues.
  • Accurate modeling of needle-tissue interaction is crucial for effective robotic needle steering in medical procedures.
  • Existing kinematic models often require empirical parameter fitting for specific needle-tissue combinations.

Purpose of the Study:

  • To develop a mechanics-based model for predicting robotic needle steering behavior.
  • To enable optimization of needle steering systems based on fundamental properties.
  • To reduce reliance on empirical observations for modeling needle-tissue interactions.

Main Methods:

  • Developed an analytical model for tip loads based on bevel geometry and tissue simulant material properties.
  • Formulated a mechanics-based model incorporating tissue-specific parameters, needle geometry, and material properties.
  • Utilized microscopic observations of needle-gel interactions to guide model design.

Main Results:

  • The mechanics-based model predicts needle deflection and radius of curvature during insertion.
  • Simulation results align with experimental observations from robotic needle insertion studies.
  • The model provides a framework for understanding and predicting needle-tissue mechanics.

Conclusions:

  • A mechanics-based model offers a more fundamental approach to robotic needle steering than previous empirical methods.
  • This model can predict needle behavior and optimize system design using intrinsic properties.
  • The developed model advances the capability for precise subsurface targeting in medical interventions.