Bab_Sak Robotic Intubation System (BRIS): A Learning-Enabled Control Framework for Safe Fiberoptic Endotracheal Intubation

TL;DR

BRIS presents a compact, human-in-the-loop robotic system for fiberoptic intubation that couples independent endotracheal tube advancement with real-time depth awareness. It integrates a four-way steerable FOB, a camera-augmented mouthpiece, and a learning-enabled closed-loop controller using real-time shape sensing, plus monocular depth estimation for anatomy-aware guidance via passive visual servoing. The framework combines a data-driven forward dynamics model with a nonlinear MPC to achieve robust, constraint-aware trajectory tracking under tendon friction and airway contact, validated on high-fidelity mannequins with standard and challenging airways. Experimental results show 100% success, mean depth error $2.4\pm1.1$ mm, and significant improvements in navigation stability and safety cues, indicating BRIS as a clinically compatible solution for safer robotic airway management.

Abstract

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.

Figures (7)

• Figure 1: Proposed Robotic Fiberoptic Intubation System featuring the Actual Setup (Left) and its 3D Rendered Model (Right)
• Figure 2: Manufactured Four-way Fiberoptic Bronchoscope showcasing Detailed Design and Functional Features.
• Figure 3: Cross section and Design of the manufactured Mouth Piece
• Figure 4: Detailed View of the Proposed End Effector for Intubation, Highlighting Its Design and Functional Specifications
• Figure 5: Anatomy-aware visual guidance using monocular depth estimation for airway zone classification and passive lumen-alignment during fiberoptic intubation.