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A Novel Point Set Registration-Based Hand-Eye Calibration Method for Robot-Assisted Surgery.
Wenyuan Sun1, Jihao Liu1, Yuyun Zhao1
1Institute of Medical Robotics, School of Medical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Sensors (Basel, Switzerland)
|November 11, 2022
Summary
A novel registration-based hand-eye calibration (RHC) method enhances robot-assisted pedicle screw insertion accuracy. This method improves surgical precision and safety compared to manual methods, achieving minimal deviations in experiments.
Area of Science:
- Robotics in Surgery
- Medical Imaging
- Surgical Navigation
Background:
- Robot-assisted surgery offers improved accuracy and safety.
- Accurate hand-eye calibration is crucial for robot-assisted surgical systems.
- Existing calibration methods often rely on solving the AX=XB equation.
Purpose of the Study:
- To propose an effective hand-eye calibration method, Registration-based Hand-eye Calibration (RHC).
- To enable accurate robot-assisted, image-guided pedicle screw insertion.
- To verify the efficacy of the RHC method through comprehensive experiments.
Main Methods:
- Developed RHC method using point set registration, avoiding the AX=XB equation.
- Incorporated tool-tip pivot calibrations in two coordinate systems.
- Generated paired-point matching through steady robot arm movement.
Main Results:
- Achieved a mean distance deviation of 0.70 mm and mean angular deviation of 0.68° with the RHC method.
- Experiments on plastic and pig vertebrae demonstrated the system's efficacy.
- Drilling trajectory deviations on pig vertebrae were 1.01 mm (distance) and 1.11° (angular).
Conclusions:
- The proposed RHC method is effective for robot-assisted pedicle screw insertion.
- The RHC method significantly enhances surgical accuracy and safety.
- The system demonstrates high precision for image-guided surgical procedures.
