Automatic system calibration for orthognathic robot system

System calibration, including hand-robot and robot-world calibration, is an essential step that directly influences the location accuracy of surgical robots. Conventional calibration methods for orthognathic robot systems (ORSs) face significant challenges in handling irregularly shaped end tools, leading to manual intervention and compromised accuracy. Therefore, an automatic method has been proposed to improve the calibration efficiency and accuracy of ORSs.

The core innovation of the proposed method lies in enabling automation of both pre-intraoperative image registration and robotic hand-eye calibration, via aligning the 3D model of irregularly shaped tools to the preoperative CT space. It can effectively minimize errors caused by manual intervention. firstly, the equations of hand-eye-tool calibration were reconstructed using the preoperative graphic information to define tool endpoints (TEPs). Then, the transformation matrices were solved via a robust optimization method based on least squares. finally, the whole calibration process was completed automatically with robot path planning without human involvement.

A group of simulated robot-assisted orthognathic surgery experiments was performed. The proposed method achieved a calibration error of 1.04 ± 0.54 mm, and the total execution error were reduced to 1.56 ± 0.61 mm.

The experimental results proved that the proposed calibration method could not only automate the calibration process, but also effectively improve the accuracy and stability of the system. It is expected to pave the way for more autonomous and efficient surgical procedures. Also, there are some limitations need to be overcome, including dependency on marker-based tracking and small sample size. Future work will integrate markerless tracking and machine learning for further optimization.