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Applying Depth-Sensing to Automated Surgical Manipulation with a da Vinci Robot
[article]
2020
arXiv
pre-print
Recent advances in depth-sensing have significantly increased accuracy, resolution, and frame rate, as shown in the 1920x1200 resolution and 13 frames per second Zivid RGBD camera. In this study, we explore the potential of depth sensing for efficient and reliable automation of surgical subtasks. We consider a monochrome (all red) version of the peg transfer task from the Fundamentals of Laparoscopic Surgery training suite implemented with the da Vinci Research Kit (dVRK). We use calibration
arXiv:2002.06302v1
fatcat:wedfovymn5d6dgfli6ll6sro7y