{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T10:01:06Z","timestamp":1766138466968,"version":"3.41.2"},"reference-count":47,"publisher":"World Scientific Pub Co Pte Ltd","issue":"03n04","funder":[{"name":"Technology & Advanced Telemedicine Research Center","award":["W81XWH-19-C-0096"],"award-info":[{"award-number":["W81XWH-19-C-0096"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Med. Robot. Res."],"published-print":{"date-parts":[[2023,12]]},"abstract":"<jats:p> Vascular shunt insertion is a common surgical procedure performed to restore blood flow to damaged tissues temporarily. It usually requires a surgeon and a surgical assistant. We consider three scenarios: (1) a surgeon is available locally; (2) a remote surgeon is available via teleoperation; (3) no surgeon is available. In each scenario, a minimally invasive surgical-assistant da Vinci robot operates in a different mode either by teleoperation or automation. Robotic assistance for this procedure is challenging due to precision and control uncertainty. The role of the robot in this task depends on the availability of a human surgeon. We propose a trimodal framework for vascular shunt insertion assisted by a da Vinci Research Kit (dVRK) robotic surgical assistant (RSA). To help further study for the community, we also present a physics-based simulated environment for shunt insertion built on top of the NVIDIA Isaac ORBIT simulator. We collect a large dataset of trajectories for the shunt insertion environment using ORBIT and implement these trajectories to show the simulator\u2019s realism, showcasing the possibility for future work to use the simulator for policy learning. Physical experiments demonstrate a success rate of 65\u2013100% for mode (1), 100% for mode (2), and 75\u201395% for mode (3) across vessel phantoms with different sizes, color, and material properties. For dataset and videos, see https:\/\/sites.google.com\/berkeley.edu\/ravsi . <\/jats:p>","DOI":"10.1142\/s2424905x23400068","type":"journal-article","created":{"date-parts":[[2023,11,3]],"date-time":"2023-11-03T04:18:05Z","timestamp":1698985085000},"source":"Crossref","is-referenced-by-count":3,"title":["Robot-Assisted Vascular Shunt Insertion with the dVRK Surgical Robot"],"prefix":"10.1142","volume":"08","author":[{"given":"Karthik","family":"Dharmarajan","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA 94709, USA"}]},{"given":"Will","family":"Panitch","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA 94709, USA"}]},{"given":"Baiyu","family":"Shi","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA 94709, USA"}]},{"given":"Huang","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA 94709, USA"}]},{"given":"Lawrence Yunliang","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Operations Research, University of California, Berkeley, Berkeley, CA 94709, USA"}]},{"given":"Masoud","family":"Moghani","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8, Canada"}]},{"given":"Qinxi","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G8, Canada"}]},{"given":"Kush","family":"Hari","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Computer Sciences, University of 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