Open tracheostomy (OT) is considered the traditional way and golden standard for treating airway obstruction patients. However, OT has many unavoidable drawbacks, including strict performing scenarios, significant scarring, and the risk of surgeon infection. Percutaneous dilation tracheostomy (PDT) emerges, with advantages including a lower cost, smaller scarring, and better protection of surgeons from inflecting by aerosol. However, the outside-in puncture manner of PDT has a risk of piercing the post-tracheal wall and the esophagus with uncontrolled force. Additionally, locating tracheal rings and determining the puncture site externally can be challenging for certain patients, such as those who are obese or have undergone neck surgery, while this procedure typically relies on palpation and the surgeon's expertise. Hence, to improve the safety and simplicity of tracheostomy, a minimally-invasive endotracheal inside-out flexible needle-driving system towards microendoscope-guided robotic tracheostomy (MERT) has been proposed in this paper. Guided by an optical coherence tomography (OCT) probe and a microendoscope, the robot inserts into the trachea and performs an inside-out puncture using a flexible needle. The robot can work through a standard endotracheal tube (ETT), and the puncture direction of the flexible needle is variable. Kinematics and statics models of the flexible needle have been derived, and the minimum position errors generated in the kinematics and statics validation experiments are$0.57 \pm 0.21 \mathbf{~ m m}$and$0.27 \pm 0.21 \mathbf{~ m m}$. Finally, a porcine trachea puncture experiment is carried out, and the feasibility of the proposed system is verified.

Nasotracheal intubation (NTI) is critical for establishing artificial airways in clinical anesthesia and critical care. Current manual methods face significant challenges, including cross-infection, especially during respiratory infection care, and insufficient control of endoluminal contact forces, increasing the risk of mucosal injuries. While existing studies have focused on automated endoscopic insertion, the automation of NTI remains unexplored despite its unique challenges: Nasotracheal tubes exhibit greater diameter and rigidity than standard endoscopes, substantially increasing insertion complexity and patient risks. We propose a novel autonomous NTI system with two key components to address these challenges. First, an autonomous NTI system is developed, incorporating a prosthesis embedded with force sensors, allowing for safety assessment and data filtering. Then, the Recurrent Action-Confidence Chunking with Transformer (RACCT) model is developed to handle complex tube-tissue interactions and partial visual observations. Experimental results demonstrate that the RACCT model outperforms the ACT model in all aspects and achieves a 66% reduction in average peak insertion force compared to manual operations while maintaining equivalent success rates. This validates the system’s potential for reducing infection risks and improving procedural safety.

Robot-assisted gastrointestinal endoscopic surgery (GES) as a kind of natural orifice transluminal endoscopic surgery (NOTES) is the next-generation minimally invasive surgery (MIS). Besides, rendering certain autonomy to a Gas-trointestinal Endoscopic Surgical Robot (GESR) is promising but highly challenging. Therefore, to accelerate the development and augment the autonomy of GESR, we use CoppeliaSim to develop the first robotic simulator for the GESR system (GESRsim) based on our previous design. The GESRsim provides several 3D models and kinematics of our designed manipulators and endoscopic snake bone. Additionally, we build several scenes for robotic GES training and then utilize different programming interfaces to perform teleoperation. Furthermore, several advanced control algorithms, including visual servoing (VS) and deep reinforcement learning (DRL), are implemented to verify the performance of the GESRsim.