Automating multi-throw multilateral surgical suturing with a mechanical needle guide and sequential convex optimization
Siddarth Sen, Animesh Garg, David V. Gealy, Stephen McKinley, Yiming Jen, Ken Goldberg
Abstract
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 [5]. Initial results suggest that the dVRK can perform suturing at 30% of human speed while completing 86% suture throws attempted. Videos and data are available at: berkeleyautomation.github.io/amts.
BibTeX
@inproceedings{icra2016_automatingmultit,
title = {Automating multi-throw multilateral surgical suturing with a mechanical needle guide and sequential convex optimization},
author = {Siddarth Sen and Animesh Garg and David V. Gealy and Stephen McKinley and Yiming Jen and Ken Goldberg},
booktitle = {ICRA 2016},
year = {2016}
}