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Related Experiment Video

Updated: Oct 27, 2025

Rod-based Fabrication of Customizable Soft Robotic Pneumatic Gripper Devices for Delicate Tissue Manipulation
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Dynamic Modeling of Cable Driven Elongated Surgical Instruments for Sensorless Grip Force Estimation.

Yangming Li1, Muneaki Miyasaka2, Mohammad Haghighipanah1

  • 1Department of Electrical Engineering, University of Washington, Seattle, WA, USA 98195.

IEEE International Conference on Robotics and Automation : ICRA : [Proceedings]. IEEE International Conference on Robotics and Automation
|July 22, 2021
PubMed
Summary

This study introduces a sensorless method for estimating grip force in robotic minimally invasive surgeries, enhancing surgeon haptic feedback using only motor data.

Keywords:
Dynamic ModelingElongated Cable Driven InstrumentMinimally Invasive SurgerySensorless Grasp Force EstimationSurgical RobotUnscented Kalman Filter

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Area of Science:

  • Robotics
  • Surgical Technology
  • Control Systems

Background:

  • Haptic feedback is crucial in surgery but is currently lacking in robotic minimally invasive surgery (MIS).
  • Elongated cable-driven surgical instruments are commonly used in MIS, but their grip force is difficult to measure directly.

Purpose of the Study:

  • To propose and validate a dynamic model-based sensorless method for estimating grip force in cable-driven surgical instruments for MIS.
  • To enhance haptic perception for surgeons operating robotic surgical systems.

Main Methods:

  • Dynamic modeling of cable and cable-pulley properties.
  • Joint estimation of grip forces, motor positions/velocities, and gripper jaw positions/velocities using Unscented Kalman Filter.
  • Utilizing only motor encoder readings and output torques as known observations.
  • Employing a bounding filter to address model inaccuracies and improve robustness.

Main Results:

  • The proposed sensorless method achieved sufficiently accurate grip force estimation.
  • Validation was performed on a 10mm gripper integrated with the Raven-II surgical robot.
  • Experimental results confirmed the method's effectiveness using only motor encoder and torque data.

Conclusions:

  • The developed dynamic model-based sensorless approach effectively estimates grip force in robotic MIS.
  • This method can significantly improve haptic feedback in robotic surgery without requiring additional force sensors.
  • The technique offers a robust solution for enhancing surgeon's sense of touch during minimally invasive procedures.