Robotic technologies are increasingly investigated for craniofacial and dental surgical procedures where sub-millimeter positional accuracy and stable instrument trajectories are essential. This structured review evaluates the current landscape of robotic systems applied to craniofacial surgical interventions and analyzes their technical architectures, validation approaches, and reported surgical accuracy. A structured literature search of PubMed and IEEE Xplore identified 27 studies published between 2015 and 2025 that met predefined inclusion criteria. The included systems were analyzed with respect to robotic control architecture, surgical application domain, validation model, and quantitative performance metrics. To facilitate cross-study interpretation, the review introduces a unified engineering classification framework linking robotic control paradigms, mechanical configurations, and clinical application domains. Most platforms employed master–slave teleoperation, image-guided hybrid control, task-autonomous execution, or cooperative haptic-guided architectures designed to stabilize surgical trajectories and reduce surgeon-dependent variability. Across representative investigations, robotic systems demonstrated entry-point deviations typically ranging from approximately 0.6–1.5 mm and angular deviations between 1.2° and 3.5°, indicating improved reproducibility compared with conventional freehand techniques. Dental implant robotics currently represents the most clinically mature application, whereas sinus, skull base, and microsurgical systems remain largely in experimental or early translational stages. Overall, craniofacial surgical robotics demonstrates substantial potential to enhance surgical precision and procedural standardization; however, broader clinical validation and improved workflow integration remain necessary for widespread clinical adoption.
Clark et al. (Mon,) studied this question.