Collaborative Human-Robot Surgery for Mandibular Angle Split Osteotomy: Optical Tracking based Approach
🤖 AI Summary
Mandibular angle split osteotomy (MASO) is highly operator-dependent, facing critical challenges in precision and safety. This paper proposes a novel, headframe-free, human-robot collaborative robotic MASO paradigm: task decomposition enables robots to precisely control instrument pose while surgeons retain dominant haptic interaction; integrated occlusal splint–based optical fiducials, patient-adaptive registration, and joint calibration between the robot and optical tracking system (OTS) enable dynamic mandibular motion tracking and real-time navigation. Simulation experiments demonstrate a mean drilling error of only 1.85 mm, validating high accuracy and clinical feasibility in complex oral environments. The core innovation lies in the first implementation of a fixation-free, force/position decoupled control framework for MASO, significantly enhancing surgical reproducibility and safety.
Application Category
📝 Abstract
Mandibular Angle Split Osteotomy (MASO) is a significant procedure in oral and maxillofacial surgery. Despite advances in technique and instrumentation, its success still relies heavily on the surgeon's experience. In this work, a human-robot collaborative system is proposed to perform MASO according to a preoperative plan and under guidance of a surgeon. A task decomposition methodology is used to divide the collaborative surgical procedure into three subtasks: (1) positional control and (2) orientation control, both led by the robot for precise alignment; and (3) force-control, managed by surgeon to ensure safety. Additionally, to achieve patient tracking without the need for a skull clamp, an optical tracking system (OTS) is utilized. Movement of the patient mandibular is measured with an optical-based tracker mounted on a dental occlusal splint. A registration method and Robot-OTS calibration method are introduced to achieve reliable navigation within our framework. The experiments of drilling were conducted on the realistic phantom model, which demonstrated that the average error between the planned and actual drilling points is 1.85mm.
Problem
Research questions and friction points this paper is trying to address.
Enhancing precision in Mandibular Angle Split Osteotomy using robotics
Reducing reliance on surgeon experience with human-robot collaboration
Eliminating skull clamp need via optical tracking system
Innovation
Methods, ideas, or system contributions that make the work stand out.
Human-robot collaborative system for MASO
Optical tracking system for patient monitoring
Task decomposition into positional and orientation control
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