Modelling and Experiment Based on a Navigation System for a Cranio-Maxillofacial Surgical Robot

Area of Science:

• Neurosurgery
• Robotics
• Medical Imaging

Background:

• Cranio-maxillofacial surgery demands high precision due to anatomical complexity and critical structures.
• Existing robotic systems may have limitations in accuracy and adaptability for diverse cranio-maxillofacial procedures.

Purpose of the Study:

• To develop and validate a novel surgical robot system for cranio-maxillofacial surgery.
• To enhance surgical accuracy and safety through advanced navigation and control strategies.
• To demonstrate the system's applicability in procedures such as biopsy, radiofrequency thermocoagulation, and radioactive particle implantation.

Main Methods:

• Development of a surgical robot system integrating navigation technology.
• Modeling subsystem transformations using quaternion and iterative closest point registration.
• Establishment of a hand-eye coordination model based on optical navigation.
• Implementation of a "kinematics + optics" hybrid closed-loop control for enhanced positioning accuracy.
• Experimental validation using skull models to assess system feasibility and accuracy.

Main Results:

• Accurate transformation relationships between subsystems were achieved.
• The hybrid motion control method significantly improved system positioning accuracy.
• Skull model experiments confirmed the surgical robot system's feasibility.
• System performance was consistent with preoperative surgical planning.

Conclusions:

• The novel surgical robot system demonstrates feasibility and high accuracy for cranio-maxillofacial surgery.
• The "kinematics + optics" hybrid control method is effective in improving positioning precision.
• This system offers a promising solution for complex cranio-maxillofacial interventions.