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PhD Defense by Yash Chitalia
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Title: Design, Modeling and Control of Micro-scale and Meso-scale Tendon-driven Surgical Robots
Date: Wednesday, June 30, 2021
Time: 11:00 AM – 1:00 PM (EST)
Location: Pettit Microelectronics Building, Room 102B
Yash Chitalia
Robotics Ph.D. Candidate
The George W. Woodruff School of Mechanical Engineering
Georgia Institute of Technology
Committee:
Dr. Jaydev P. Desai (Advisor) - Department of Biomedical Engineering, Georgia Institute of Technology
Dr. Frank Hammond - Department of Mechanical Engineering, Georgia Institute of Technology
Dr. Ellen Yi Chen Mazumdar - Department of Mechanical Engineering, Georgia Institute of Technology
Dr. Joshua J. Chern - Department of Neurosurgery, Emory University
Dr. Zachary L. Bercu - Department of Radiology and Imaging Sciences, Emory University
Abstract:
Manual manipulation of passive surgical tools is time consuming with uncertain results in cases of navigating tortuous anatomy, avoiding critical anatomical landmarks, and reaching targets not located in the linear range of these tools. This work introduces the design of a micro-scale COaxially Aligned STeerable (COAST) guidewire robot that demonstrates variable and independently controlled bending length and curvature of the distal end. The design of the robot involves three coaxially aligned superelastic micromachined tubes with a single tendon running centrally through the length of the robot. Varying the lengths of the tubes, tendon, and insertion and retraction of the robot base can allow for follow-the-leader motion. Large-deflection beam bending models of the individual pre-curved tubes are considered for design optimization. Kinematic and static models, and a controller for this robot are presented. The capability of the robot to accurately navigate through phantom anatomical bifurcations is demonstrated in 3D phantom vasculature. This work also introduces the design, analysis, and control of a meso-scale two degree-of-freedom robotic bipolar electrocautery tool that increases the workspace of a pediatric neurosurgical procedure. Pure kinematic modeling and control for this tool may not provide precise control performance due to kinematic uncertainties arising from tendon elongation, tendon slacking, gear backlash, etc. A static model is proposed for each of the joints of the handheld robotic tool that avoids several of these problems. A control system is developed that comprises of a disturbance observer to provide precise force control and compensate for joint hysteresis. To allow the clinician to estimate the shape of the steerable tools within the anatomy for both micro-scale and meso-scale tools, a miniature tendon force sensor and a high deflection shape sensor are proposed and demonstrated.
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Status
- Workflow Status:Published
- Created By:Tatianna Richardson
- Created:06/16/2021
- Modified By:Tatianna Richardson
- Modified:06/16/2021
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