Graduation Year
2020
Document Type
Thesis
Degree
M.S.M.E.
Degree Name
MS in Mechanical Engineering (M.S.M.E.)
Degree Granting Department
Mechanical Engineering
Major Professor
Redwan Alqasemi, Ph.D.
Co-Major Professor
Rajiv Dubey, Ph.D.
Committee Member
Sudeep Sarkar, Ph.D.
Keywords
Eye Fixation, Jacobian, Prosthesis, Resolved Rate, Singularity Robust
Abstract
There are more than 350000 amputees in the US who suffer loss of functionality in their daily living activities, and roughly 100000 of them are upper arm amputees. Many of these amputees use prostheses to compensate part of their lost arm function, including power prostheses. Research on 6-7 degree of freedom powered prostheses is still relatively new, and most commercially available powered prostheses are typically limited to 1 to 3 degrees of freedom. Due to the myriad of possible options for various powered protheses from different manufacturers, each configuration is governed by a distinct control scheme typically specific to the manufacturer. The user will then have to be accustomed to its custom control scheme to be able to use such protheses for ADL tasks. Control of available powered prosthesis options utilize different strategies such as individual joint control, partial endpoint control, or switching between different modes that is mentally demanding for the user leading to possible abandonment of such devices in favor of more passive systems. To overcome such issues, a novel resolved rate algorithm using Cartesian control was developed for universal use by having the user specify where the end effector must go through visual targeting. This is achieved by utilizing an augmented reality device “Magic Leap” to provide the spatial targeting information to the controller, which will then autonomously move the end effector to the targeted location. This controller system is simulated on a virtual humanoid arm model and tested on a Human Arm Robotic Unit, which is the hardware version of the arm model.
Scholar Commons Citation
Canezo, Carlo, "Control of a Human Arm Robotic Unit Using Augmented Reality and Optimized Kinematics" (2020). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/8519