Preoperative Planning Framework for Robot-Assisted Dental Implant Surgery: Finite-Parameter Surrogate Model and Optimization of Instrument Placement

Abstract

For robot-assisted dental implant surgery, it is necessary to feed the instrument into a specified position to perform surgery. To improve safety and efficiency, a preoperative planning framework, including a finite-parameter surrogate model (FPSM) and an automatic instrument-placement method, is proposed in this paper. This framework is implemented via two-stage optimization. In the first stage, a group of closed curves in polar coordinates is used to represent the oral cavity. By optimizing a finite number of parameters for these curves, the oral structure is simplified to form the FPSM. In the second stage, the FPSM serves as a fast safety estimator with which the target position/orientation of the instrument for the feeding motion is automatically determined through particle swarm optimization (PSO). The optimized feeding target can be used to generate a virtual fixture (VF) to avoid undesired operations and to lower the risk of collision. This proposed framework has the advantages of being safe, fast, and accurate, overcoming the computational burden and insufficient real-time performance of complex 3D models. The framework has been developed and tested, preliminarily verifying its feasibility, efficiency, and effectiveness.