• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2025, Vol. 61 ›› Issue (3): 212-224.doi: 10.3901/JME.2025.03.212

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Dual-robot Surgical System for Collaborative Maxillofacial Osteotomy

LUO Xuejin1, ZHANG Runshi1, DENG Yingyan1, MO Hao1, ZHU Jiayu1, LIU Xinyu2, HE Yang2, WANG Junchen1   

  1. 1. Robotics Institute, Beihang University, Beijing 100191;
    2. Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology, Beijing 100081
  • Received:2024-04-03 Revised:2024-06-13 Published:2025-03-12

Abstract: The complex craniomaxillofacial anatomy and narrow surgical field pose significant challenges for surgical procedures. These challenges include high surgical difficulty, cooperation between surgeons and assistants, and over-reliance on the surgeon’s experience. The fatigue of surgeons is reduced and the accuracy of operation is improved via the intelligent image analysis technology and high precision robotic system. To promote efficiency, a dual-robot surgical system for maxillofacial osteotomy is proposed. The self-supervised pre-training learning network is used to realize segmentation and reconstruction. The iterative closest point algorithm is employed for image alignment. The planning trajectory is realized and mapped from the image space to the robotic task space via the optical tracking and registration. The hybrid osteotomy control method combining admittance control and visual servo tracking is proposed in the 1 kHz real-time framework based on the EtherCAT. The dual-robot system is tested with a skull model. The human-machine interaction is demonstrated. The experimental results show that the dice of mandible segmentation is 94.95% and the osteotomy error is 1.68±0.26 mm, confirming the effectiveness of the proposed method.

Key words: dual-robot system, craniomaxillofacial surgery, admittance control, robot navigation

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