Surgical Automation for Multilateral Multi-Throw Suturing
نویسنده
چکیده
Surgical Automation for Multilateral Multi-Throw Suturing by Siddarth Sen Master of Science in Electrical Engineering and Computer Science University of California, Berkeley Professor Ken Goldberg, Chair For supervised automation of multi-throw suturing in Robot-Assisted Minimally Invasive Surgery, we present a novel mechanical needle guide and a framework for optimizing needle size, trajectory, and control parameters using sequential convex programming. The Suture Needle Angular Positioner (SNAP) results in a 3x error reduction in the needle pose estimate in comparison with the standard actuator. We evaluate the algorithm and SNAP on a da Vinci Research Kit using tissue phantoms and compare completion time with that of humans from the JIGSAWS dataset [6]. Initial results suggest that the dVRK can perform suturing at 30% of human speed while completing 86% suture throws attempted.
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Automating Multiple-Throw Multilateral Surgical Suturing with a Mechanical Needle Guide and Sequential Convex Optimization
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