Existing tracheal tumor resection methods often lack the precision required for effective airway clearance, and robotic advancements offer new potential for autonomous resection. We present a vision-guided, autonomous approach for palliative resection of tracheal tumors. This system models the tracheal surface with a fifth-degree polynomial to plan tool trajectories, while a custom Faster R-CNN segmentation pipeline identifies the trachea and tumor boundaries. The electrocautery tool angle is optimized using handheld surgical demonstrations, and trajectories are planned to maintain a 1 mm safety clearance from the tracheal surface. We validated the workflow successfully in five consecutive experiments on ex-vivo animal tissue models, successfully clearing the airway obstruction without trachea perforation in all cases (with more than 90% volumetric tumor removal). These results support the feasibility of an autonomous resection platform, paving the way for future developments in minimally-invasive autonomous resection.
View on arXiv@article{smith2025_2502.18586,
title={ Autonomous Vision-Guided Resection of Central Airway Obstruction },
author={ M. E. Smith and N. Yilmaz and T. Watts and P. M. Scheikl and J. Ge and A. Deguet and A. Kuntz and A. Krieger },
journal={arXiv preprint arXiv:2502.18586},
year={ 2025 }
}