A computationally efficient method for hand-eye calibration

Area of Science:

• Robotics
• Computer Vision
• Surgical Technology

Background:

• Surgical robots with cooperative control offer significant clinical potential for image-guided, repetitive tasks.
• Accurate hand-eye calibration is crucial for autonomous surgical tasks, defining the transformation between robot and camera coordinates.
• Frequent online hand-eye calibration is necessary due to instrument changes, impacting surgical workflow.

Purpose of the Study:

• To develop a computationally efficient iterative method for online hand-eye calibration.
• To enable fast and seamless execution of surgical procedures without workflow disruption.
• To improve the accuracy and reliability of surgical robot systems.

Main Methods:

• A novel iterative hand-eye calibration method utilizing dual quaternions to represent rigid transformations.
• A two-step iterative process to simultaneously recover real and dual parts of the dual quaternion.
• Estimation of rotation and translation for precise robot-camera coordinate transformation.

Main Results:

• The method was successfully applied to calibrate the transformation between a stereo laparoscope and a robot manipulator.
• Experimental and simulation results demonstrated a significant improvement in convergence speed, reducing iterations from over 30 to just 3.
• The proposed method proved effective and efficient for hand-eye calibration.

Conclusions:

• The developed iterative dual quaternion method offers a computationally efficient solution for surgical robot hand-eye calibration.
• The significant speed improvement in convergence validates the method's effectiveness and efficiency.
• This technique facilitates more reliable and seamless autonomous surgical procedures.