2026-09-20T07:40:00Zhttps://digital.lib.washington.edu/server/oai/request

oai:digital.lib.washington.edu:1773/405482026-02-15T22:39:34Zcom_1773_4888col_1773_4915

Hannaford, Blake Su, Yun-Hsuan 2017-10-26T20:49:20Z 2017-10-26T20:49:20Z 2017-10-26 2017-08 Su_washington_0250O_17733.pdf http://hdl.handle.net/1773/40548 Thesis (Master's)--University of Washington, 2017-08 Robot assisted minimally invasive surgery combines the skill and techniques of highly-trained surgeons with the robustness and precision of machines. Through a teleoperation scheme, surgeons can execute high-level surgical tasks by commanding instruments controlled by precise robotic devices. Several advantages arise. To name a few: (1) achieved precision is beyond that of human dexterity alone (2) a greater number of kinematic degrees of freedom are possible at the surgical tool tip (3) surgeons are able to operate remotely, i.e. agnostic of patient location given a suitable communication line. Despite the numerous advantages over traditional key-hole or laparoscopic surgery, the lack of realistic and real-time force feedback is a major drawback --- discerning tool-tissue interactions can be unintuitive and can ultimately result in unintentional tissue damage. Directly sensing forces at the tool-tissue interface is theoretically possible using tool tip mounted force sensors, but this approach is not amenable to required sterilization procedures. Thus, a vision based force estimation method is proposed to infer the applied force based on real-time analysis of tissue deformation. application/pdf en_US First stage result.mp4; video; Demo video for first stage: image segmentation. slide.pptx; presentation; This is the slide for my MS thesis defense. Produce.wmv; video; Demo video for second stage: depth rendering. CC BY Image Segmentation Raven Surgical Robot Surgical Instrument Tracking Surgical Robotics Engineering Electrical engineering Vision Based Surgical Tool Tracking with Robot Kinematics Prior Thesis Open Access open.access