Degree Type

Thesis

Date of Award

2014

Degree Name

Master of Science

Department

Mechanical Engineering

Major

Human Computer Interaction

First Advisor

Eliot Winer

Abstract

Designers and engineers working in the computer-aided drafting (CAD) and computer-aided engineering (CAE) domains routinely interact with specialized computer software featuring three dimensional (3D) work environments. These professionals must manipulate virtual objects or components within this 3D work environment, but typically use traditional interaction devices with outdated technology that are more suitable for 2D work tasks. Current CAD and CAE software is designed to accommodate outdated interaction technology, but this functionality comes at the cost of efficiency in the virtual workspace. A new class of affordable interaction devices with characteristics and specifications of high-end virtual reality interaction devices is now available to consumers. These commodity VR interaction devices monitor the position and orientation of a user's hands through space to control aspects of desktop software in ways that are impossible with the traditional mouse and keyboard pair. They can be integrated with CAD or CAE software to allow gestural control of objects throughout a 3D work environment.

To evaluate the feasibility of gestural control for 3D work environments, a commercially available commodity VR interaction device was selected and integrated with specific 3D software. Gestures to control aspects of the software are developed and organized into a taxonomy. Select gestures are integrated with the software and evaluated against traditional interaction methods, using the Natural Goals Operators Methods Selection Rules Language (NGOMSL) concept. The evaluation results show that gestural interaction is efficient for object manipulation tasks, but a traditional keyboard or mouse is more efficient for basic tool selection tasks. Estimated learning times for each input method indicate gestural control takes about 30 seconds longer to learn than traditional interaction methods.

Copyright Owner

Frederick Victor Thompson III

Language

en

File Format

application/pdf

File Size

82 pages

interaction_example.mp4 (34169 kB)
Video of the implemented gestural interaction

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