Date of Award
Doctor of Philosophy (PhD)
Mechanical & Aerospace Engineering
Frederic D. McKenzie
Stacie I. Ringleb
Robotic surgery is one of the most demanding and challenging applications in the field of automatic control. One of the conventional surgeries, the dental implantation, is the standard methodology to place the artificial tooth root composed of titanium material into the upper or lower jawbone. During the dental implant surgery, mechanical removal of the bone material is the most critical procedure because it may affect the patient's safety including damage to the mandibular canal nerve and/or piercing the maxillary sinus. With this problem, even though short term survival rates are greater than 95%, long term success rate of the surgery is as low as 41.9% in 5 years. Since criteria of bone loss should be less than 0.2 mm per year, a high degree of anatomical accuracy is required. Considering the above issues leads to the employment of more precise surgery using computer assisted medical robots.
In this dissertation, a computer-aided open-loop intra-operative robotic system with pre-operative planning is presented to improve the success rate of the dental implantation using different types of milling algorithms that also incorporate natural root-shaped implants.
This dissertation also presents the refinement and optimization of three-dimensional (3D) dental implants with the complex root shapes of natural teeth. These root shapes are too complex to be drilled manually like current commercial implants and are designed to be conducive to robotic drilling utilizing milling algorithms. Due to the existence of sharp curvatures and undercuts, anatomically correct models must be refined for 3D robotic milling, and these refined shapes must be shown to be optimized for load bearing. Refinement of the anatomically correct natural tooth-shaped models for robotic milling was accomplished using Computer-Aided-Design (CAD) tools for smoothing the sham curvatures and undercuts. The load bearing optimization algorithm is based on the Soft-Kill Option (SKO) method, and the geometries are represented using non-uniform rational B-spline (NURBS) curves and surfaces. Based on these methods, we present optimized single and double root-shaped dental implants for use with robotic site preparation.
Evaluation of phantom experiment has led us to investigate how the position, orientation, and depth of the robotic drilling defined with the dental tool exhibit accuracy and efficiency.
"Evaluation of Autonomous Robotic Milling Methodology for Natural Tooth-Shaped Implants Based on SKO Optimization"
(2012). Doctor of Philosophy (PhD), dissertation, Mechanical & Aerospace Engineering, Old Dominion University, DOI: 10.25777/ere2-w598