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A Concurrent Framework for Constrained Inverse Kinematics of Minimally Invasive Surgical Robots.

Jacinto Colan1, Ana Davila2, Khusniddin Fozilov1

  • 1Department of Micro-Nano Mechanical Science and Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Aichi, Japan.

Sensors (Basel, Switzerland)
|March 30, 2023
PubMed
Summary

A new concurrent inverse kinematics (IK) framework improves robotic surgery by combining methods to solve complex motion control problems. This approach enhances accuracy and speed in robot-assisted minimally invasive surgery (RMIS).

Keywords:
concurrent solvingconstrained motion planninghierarchical quadratic programminginverse kinematicsminimally invasive surgerynonlinear optimizationsurgical robot

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Area of Science:

  • Robotics
  • Surgical Technology
  • Control Systems Engineering

Background:

  • Minimally invasive surgery (MIS) reduces patient trauma, but robotic systems introduce motion control challenges.
  • Accurate robot movement is crucial in robot-assisted minimally invasive surgery (RMIS), particularly satisfying the remote center of motion (RCM) constraint.
  • Existing inverse kinematics (IK) methods for RMIS have limitations and vary in performance based on robot configuration.

Purpose of the Study:

  • To develop a novel concurrent IK framework for RMIS that integrates classical and optimization-based approaches.
  • To explicitly incorporate remote center of motion (RCM) constraints and joint limits into the IK optimization process.
  • To validate the performance of the concurrent IK solvers through simulation and real-world experiments.

Main Methods:

  • Design and implementation of concurrent IK solvers combining iterative inverse Jacobian and hierarchical quadratic programming methods.
  • Integration of remote center of motion (RCM) constraints and joint limits within the optimization framework.
  • Experimental validation in both simulated environments and practical robotic surgery scenarios.

Main Results:

  • Concurrent IK solvers achieved a 100% solve rate, outperforming single-method solvers.
  • IK solving time was reduced by up to 85% for endoscope positioning and 37% for tool pose control.
  • The combined iterative inverse Jacobian and hierarchical quadratic programming method demonstrated the highest solve rate and lowest computation time in real-world tests.

Conclusions:

  • The proposed concurrent IK framework offers an effective solution for the constrained IK problem in RMIS.
  • This approach enhances the accuracy and efficiency of robotic movements in minimally invasive procedures.
  • Concurrent IK solving represents a significant advancement for the control of robotic systems in surgery.