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Towards A Physics-based Model for Steerable Eversion Growing Robots.

Zicong Wu1, Mikel De Iturrate Reyzabal1, S M Hadi Sadati1

  • 1School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.

IEEE Robotics and Automation Letters
|February 3, 2023
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Summary
This summary is machine-generated.

This study introduces a physics-based model for miniature steerable growing robots that navigate delicate spaces. Simulations and experiments show accurate control for medical applications like mammary duct inspection.

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Area of Science:

  • Robotics
  • Biomedical Engineering
  • Soft Robotics

Background:

  • Soft robots capable of growth via eversion/apical extension offer potential for navigating complex and fragile internal human body environments.
  • Existing methods for internal navigation often lack the adaptability and gentleness required for delicate biological structures.

Purpose of the Study:

  • To present a physics-based model for a miniature steerable eversion growing robot.
  • To investigate the robot's capabilities in growth, steering, stiffening, and interaction within confined spaces.

Main Methods:

  • Development of a physics-based model for a tendon-driven, steerable, eversion growing robot.
  • Simulation of robot behavior under varying internal pressures and external forces using the SOFA framework.
  • Experimental validation of the model using a physical robot prototype.

Main Results:

  • Demonstrated the robot's capacity for controlled growth, steering, and stiffening.
  • Quantified the interaction between the steerable catheter and the growing sheath for precise control.
  • Achieved 10-20% mean absolute error in curvature values between simulations and experiments.

Conclusions:

  • The developed physics-based model accurately predicts the behavior of steerable eversion growing robots.
  • This approach is the first to model tendon-driven steerable eversion growing robots, offering a foundation for future advancements.
  • The methodology is applicable to various growing robot designs and medical inspection tasks, including mammary duct inspection for early breast cancer detection.