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A Clamping Force Estimation Method Based on a Joint Torque Disturbance Observer Using PSO-BPNN for Cable-Driven

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This study introduces a novel clamping force estimation method for minimally-invasive surgical robots (MISRs) without internal sensors. The technique achieves high-resolution force detection, enhancing surgical precision and safety.

Keywords:
PSO-BPNNcable tension measurementclamping force estimationjoint torque disturbance observersurgical robot end-effector

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Area of Science:

  • Robotics
  • Surgical Technology
  • Sensor Technology

Background:

  • Minimally-invasive surgical robots (MISRs) require precise force sensing for safe and effective operation.
  • Current MISRs often lack integrated force sensors in their end-effectors, limiting tactile feedback.
  • Accurate clamping force sensing is crucial for delicate surgical manipulations.

Purpose of the Study:

  • To develop a one-dimensional clamping force sensing method for cable-driven MISR end-effectors.
  • To enable force sensing without requiring internal force sensors within the forceps.
  • To enhance the safety and precision of surgical procedures through improved force feedback.

Main Methods:

  • Proposed a joint torque disturbance observer (JTDO) for cable-driven surgical robot end-effectors.
  • Utilized a Particle Swarm Optimization Back Propagation Neural Network (PSO-BPNN) to estimate cable tension variations.
  • Developed a clamping force estimator based on the forceps' JTDO and mechanical relationships.

Main Results:

  • Achieved a detection resolution of 0.11 N for both collision and clamping forces.
  • Experimental studies verified the feasibility and effectiveness of the proposed method.
  • Demonstrated accurate clamping force estimation without internal end-effector sensors.

Conclusions:

  • The proposed JTDO-based method effectively estimates clamping force in cable-driven MISRs.
  • This approach enhances force sensing capabilities without complex internal sensor integration.
  • The findings contribute to safer and more precise minimally-invasive surgeries.