A 2D Image Feedback-Based Autonomous Endovascular Navigation Method: A Perception and Control Framework

Abstract:In endovascular interventions, physicians rely on planar DSA and X-ray fluoroscopy to interpret vessel anatomy and device motion, yet converting these images into feedback for autonomous navigation remains difficult. A perception and control method is formulated for two-dimensional image feedback. Vessel masks are converted into a labeled centerline graph, and device-tip estimates are projected onto a planned path to obtain progress, deviation, and direction. A rule-based controller uses these quantities for delivery, branch selection, probing, rollback, and recovery. The method was evaluated on a physical dual-device robotic platform in 65 closed-loop runs using simulator-rendered planar images across three paths. All runs reached at least 0.95 maximum observed guidewire progress; two runs (3.1%) met the prespecified failure rule of three or more autonomous stop events. The results establish route-level performance on the tested platform; clinical image sequences and broader anatomy remain to be evaluated.

Robotics (cs.RO)

arXiv:2610.21481 [cs.RO]

(or arXiv:2610.21481v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2610.21481 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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