ORCID Identifier(s)

0000-0002-0582-9657

Graduation Semester and Year

2016

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Electrical Engineering

Department

Electrical Engineering

First Advisor

Dan Popa

Abstract

Automated systems have progressed to begin allowing for Human-robot interaction and collaboration in the workplace and rehabilitation settings. Seamless collaboration between robotic systems and users requires intuitive modes of interaction and systems with advanced sensing capabilities. The research presented below focuses on identifying human intent through safe, intuitive and optimized input method and sensing. In this dissertation novel sensor input modalities for Human-Robot Interaction (HRI) are discussed, fundamental research regarding physical Human-Robot Interaction (pHRI) is presented, and solutions towards optimal placement of sensors to facilitate intuitive interfaces are shown. EMG and Pressure: EMG and intrasocket pressure sensors are used in combination with a classifier to create a novel set of input modalities for low encumbrance input to robotic and prosthetic systems. Grip Pressure and Wrist Joint Angle and Human Intent Modeling: fundamental research provided insights in to grip-strategies during human robot interaction, grip-pressure, wrist angle during activities of daily living, and provided data to construct an intent model based on pre-grip arm configuration data. Wrist Velocity: Wrist velocity during activities of daily living is classified in order to improve human-robot interaction. Optimization of Sensor Placement: optimal placement of accelerometers is studied in order to provide compensation for compliant manipulators and control systems. The objective of this dissertation is to present tools and models which make use of gathered data to guide further development of sensorized robotic skin and improve physical interaction between human users and robotic systems. These tools will allow for more optimal placement of sensors on robotic systems. Improved intent models will be applied in the areas of powered prosthetic devices and rehabilitation robotics as well as industrial systems.

Keywords

Human-robot interaction, Robotics, Prosthetic devices, Surface electromyography, Force myography, Acclerometers

Disciplines

Electrical and Computer Engineering | Engineering

Comments

Degree granted by The University of Texas at Arlington

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