  Vascular shunt insertion is a fundamental surgical procedure used to
temporarily restore blood flow to tissues. It is often performed in the field
after major trauma. We formulate a problem of automated vascular shunt
insertion and propose a pipeline to perform Automated Vascular Shunt Insertion
(AVSI) using a da Vinci Research Kit. The pipeline uses a learned visual model
to estimate the locus of the vessel rim, plans a grasp on the rim, and moves to
grasp at that point. The first robot gripper then pulls the rim to stretch open
the vessel with a dilation motion. The second robot gripper then proceeds to
insert a shunt into the vessel phantom (a model of the blood vessel) with a
chamfer tilt followed by a screw motion. Results suggest that AVSI achieves a
high success rate even with tight tolerances and varying vessel orientations up
to 30{\deg}. Supplementary material, dataset, videos, and visualizations can be
found at https://sites.google.com/berkeley.edu/autolab-avsi.
