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Optical CMOS sensors tracked endoscopic tool paths in surgical experiments, enabling accurate kinematic modeling of surgical robots. This research provides a realistic basis for understanding surgical robot dynamics and safety.

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Area of Science:

  • Surgical Robotics
  • Biomechanics
  • Optical Sensing Technology

Background:

  • Surgical robotics requires precise tracking of instrument motion for accurate control and modeling.
  • Existing methods for capturing endoscopic tool trajectories can be limited in accuracy and scope.
  • Developing robust kinematic and dynamic models is crucial for surgical robot design and performance evaluation.

Purpose of the Study:

  • To investigate the use of optical CMOS sensors for capturing endoscopic tool trajectories during simulated surgical procedures.
  • To derive kinematic inputs for a computational dynamics model of surgical robots.
  • To validate the inverse kinematics of a remote center of motion (RCM) surgical robot and analyze its dynamic behavior.

Main Methods:

  • Utilized four optical CMOS sensors to track reflective markers on endoscopic tools.
  • Employed Ariel Performance Analysis System (APAS) software and the direct linear transformation (DLT) algorithm for trajectory acquisition.
  • Developed a computational dynamics model using finite element analysis and block diagrams for torque and PID control simulation.
  • Conducted experiments with a cardiac surgeon using conventional endoscopic instruments and robotic systems.

Main Results:

  • Successfully captured endoscopic tool trajectories with an accuracy of ±2 mm.
  • Solved the inverse kinematics problem for an RCM surgical robot.
  • Generated numerical dynamics models for transient states, including driving torques, stresses, and displacements.
  • Demonstrated the feasibility of using optical sensor data to accurately represent real-world surgical robot dynamics.

Conclusions:

  • Optical CMOS sensors are effective for capturing surgical tool motion, providing essential inputs for realistic dynamics modeling.
  • The developed methodology enables the derivation of analogous motion and analysis of surgical robot performance.
  • This approach lays the groundwork for enhanced design, control, and safety assessment of surgical robots.