Utsav Shah

Graduation Semester and Year

2016

Language

English

Document Type

Thesis

Degree Name

Master of Science in Mechanical Engineering

Department

Mechanical and Aerospace Engineering

First Advisor

Panayiotis S Shiakolas

Abstract

This research investigated Human Robot Interaction modalities. The performance of a robotic prosthetic hand (RPH) was used as a test bed robot. A user wearable glove was fitted with sensors to provide tele-control of the RPH. An open hardware control and easily expandable research platform based on LabVIEW software and myRIO control hardware was developed. LabVIEW graphical programming platform provides the tools for the development to customized interfaces for visualization purposes which is desired in research. The research platform was used to calibrate and control the operation of the artificial hand using various modalities such as open loop, glove master-slave setup and knowledge base interaction. Mapping algorithms between the motion of the master glove and slave RPH were developed. The knowledge based modality was based on artificial neural networks (ANN), where supervised learning identified appropriate grasping patterns for a set of objects based on a training data set. The training data set was developed using manual and glove control of the RPH and consists of the object geometric features and object location relative to the RPH. The training data set is then processed using the LabVIEW ANN toolkit to identify in real-time, the grasping patterns for other similar objects that include the desired motion for each RPH finger. The developed research platform and tools have been demonstrated through manual, glove and ANN control of the RPH and display of system information on the LabVIEW GUI in real-time.

Keywords

Human-robot interaction, Machine learning, LabVIEW

Disciplines

Aerospace Engineering | Engineering | Mechanical Engineering

Comments

Degree granted by The University of Texas at Arlington

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