Endotracheal intubation is a critical yet technically demanding procedure, with failure or improper tube placement leading to severe complications. Existing robotic and teleoperated intubation systems primarily focus on airway navigation and do not provide integrated control of endotracheal tube advancement or objective verification of tube depth relative to the carina. This paper presents the Robotic Intubation System (BRIS), a compact, human-in-the-loop platform designed to assist fiberoptic-guided intubation while enabling real-time, objective depth awareness. BRIS integrates a four-way steerable fiberoptic bronchoscope, an independent endotracheal tube advancement mechanism, and a camera-augmented mouthpiece compatible with standard clinical workflows. A learning-enabled closed-loop control framework leverages real-time shape sensing to map joystick inputs to distal bronchoscope tip motion in Cartesian space, providing stable and intuitive teleoperation under tendon nonlinearities and airway contact. Monocular endoscopic depth estimation is used to classify airway regions and provide interpretable, anatomy-aware guidance for safe tube positioning relative to the carina. The system is validated on high-fidelity airway mannequins under standard and difficult airway configurations, demonstrating reliable navigation and controlled tube placement. These results highlight BRIS as a step toward safer, more consistent, and clinically compatible robotic airway management.

翻译：气管插管是一项关键但技术要求高的操作，其失败或插管位置不当会导致严重并发症。现有的机器人和遥操作插管系统主要关注气道导航，未能提供气管导管推进的集成控制，也缺乏导管尖端相对于隆突深度的客观验证。本文提出机器人插管系统（BRIS），这是一种紧凑的人机协同平台，旨在辅助光纤引导插管，同时实现实时、客观的深度感知。BRIS集成了四向可操纵光纤支气管镜、独立的气管导管推进机构，以及与标准临床工作流程兼容的摄像头增强型咬口器。一个学习赋能的闭环控制框架利用实时形状传感，将操纵杆输入映射到笛卡尔空间中的支气管镜远端尖端运动，在肌腱非线性和气道接触条件下提供稳定直观的遥操作。单目内窥镜深度估计用于对气道区域进行分类，并为相对于隆突的安全导管定位提供可解释的、基于解剖结构的引导。该系统在高保真气道模型上，于标准及困难气道配置下进行了验证，展示了可靠的导航和可控的导管放置。这些结果突显了BRIS作为迈向更安全、更一致且临床兼容的机器人气道管理的一步。