Mechanical & Materials Engineering, Department of

 

First Advisor

Shane Farritor

Date of this Version

12-2016

Citation

Lou Cubrich. Design of a Flexible Control Platform and Miniature in vivo Robots for Laparo-Endoscopic Single-Site Surgeries. Mechanical (and Materials) Engineering – Dissertations, Theses, and Student Research, December 2016.

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfilment of Requirements For the Degree of Master of Science, Major: Mechanical Engineering and Applied Mechanics, Under the Supervision of Professor Shane Farritor, Lincoln, Nebraska: December, 2016

Copyright 2016 Lou Cubrich

Abstract

Minimally-invasive laparoscopic procedures have proven efficacy for a wide range of surgical procedures as well as benefits such as reducing scarring, infection, recovery time, and post-operative pain. While the procedures have many advantages, there are significant shortcomings such as limited instrument motion and reduced dexterity. In recent years, robotic surgical technology has overcome some of these limitations and has become an effective tool for many types of surgeries. These robotic platforms typically have an increased workspace, greater dexterity, improved ergonomics, and finer control than traditional laparoscopic methods. This thesis presents the designs of both a four degree-of-freedom (DOF) and 5-DOF miniature in vivo surgical robot as well as a software architecture for development and control of such robots. The proposed surgical platform consists of a two-armed robotic prototype, distributed motor control modules, custom robot control software, and remote surgeon console. A plug-in architecture in the control software provides the user a wide range of user input devices and control algorithms, including a numerical inverse kinematics solver, to allow intuitive control and rapid development of future robot prototypes. A variety of experiments performed by a surgeon at the University of Nebraska Medical Center were used to evaluate the performance of the robotic platform.

Adviser: Shane Farritor

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