In-Situ Automated Robotic Crown Preparation with MPC-Based Adaptive Control

Abstract

Crown preparation aims to create an optimal foundation for durable and functional restoration by reshaping the tooth with a cutting tool. Robotic crown preparation has emerged as a promising approach to overcome the inherent limitations of manual procedures, yet challenges remain in achieving efficient cutting path generation, collision-free orientation adjustment and precise cutting path following, since the oral cavity is a confined space with the target tooth tightly surrounded by other teeth. This paper introduces a novel, in-situ automated robotic full crown preparation system comprising (1) Preoperative Path Planning: generating high-efficiency universal cutting paths based on tooth morphological features; (2) Intraoral Collision Avoidance: optimizing the cutting tool's orientation within the constrained oral cavity; (3) MPC-Based Adaptive Control: modulating the path-following feed rate using model predictive control (MPC) according to intraoperative force feedback. The proposed system was thoroughly validated on a human head phantom targeting a permanent tooth to simulate a real clinical scenario, yielding an average root-mean-square (RMS) error (tooth shape after preparation) of 0.17 mm and an overall mean execution time of 347.77 s, achieving a 74.2% improvement in cutting efficiency over state-of-the-art methods. A comparative evaluation against conventional dental guides further demonstrates its technical feasibility and significant potential for clinical translation.