Collaborative Human-Robot Surgery for Mandibular Angle Split Osteotomy: Optical Tracking based Approach

TL;DR

This paper presents a collaborative human-robot system for mandibular angle split osteotomy that combines preoperative planning, optical tracking, and task decomposition to improve surgical accuracy and safety.

Contribution

It introduces a novel task decomposition methodology and an optical tracking system for patient movement, enabling precise robot-assisted surgery without skull clamps.

Findings

Average drilling error of 1.85mm on phantom models

Effective patient tracking without skull clamps

Successful implementation of task-specific control in surgery

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.