Model-Free Catheter Delivery Strategy for Robotic Transcatheter Tricuspid Valve Replacement
Haichuan Lin, Yiping Xie, Ziqi Wang, Dong Chen, Longyue Tan, Weizhao Wang, Yuen Chiu Ng, Xilong Hou
Abstract
Transcatheter tricuspid valve replacement (TTVR) has emerged as a promising minimally invasive procedure for treating severe tricuspid regurgitation (TR). However, accurate catheter delivery remains a significant challenge, primarily due to the reliance on 2D vision feedback, complex catheter kinematics, camera-to-robot pose calibration, which are difficult to generalize across patients. To address these issues, this paper presents a model-free robotic catheter delivery strategy for TTVR using Data-Enabled Predictive Control (DeePC). This approach leverages data-driven control to optimize catheter positioning without the need for prior knowledge of the system’s dynamics, eliminating the need for complex kinematic models or camera calibration. The proposed method incorporates environmental constraints to ensure the safety of the procedure, delivering the catheter to the desired location with high accuracy across varying catheters and camera poses. Experimental results demonstrate the effectiveness and versatility of the approach, suggesting its potential for broader applications in robotic-assisted surgeries. This work presents a new perspective for vision based robotic TTVR, as well as other clinical interventions involving robotic catheter control.
BibTeX
@inproceedings{iros2025_modelfreecathete,
title = {Model-Free Catheter Delivery Strategy for Robotic Transcatheter Tricuspid Valve Replacement},
author = {Haichuan Lin and Yiping Xie and Ziqi Wang and Dong Chen and Longyue Tan and Weizhao Wang and Yuen Chiu Ng and Xilong Hou and Chen Chen and Xiao-Hu Zhou and Zeng-Guang Hou and Shuangyi Wang},
booktitle = {IROS 2025},
year = {2025}
}