Abstract

Augmented Reality's (AR) scope and capabilities have grown considerably in the last few years. AR applications can be run across devices such as phones, wearables, and head-mounted displays (HMDs). The increasing research and commercial efforts in HMDs capabilities allow end users to map a 3D environment and interact with virtual objects that can respond to the physical aspects of the scene. Within this context, AR is an ideal format for in-situ training scenarios. However, building such AR scenarios requires proficiency in game engine development environments and programming expertise. These difficulties can make it challenging for domain experts to create training content in AR. To combat this problem, this thesis presents strategies and guidelines for building authoring tools to generate scenario-based training experiences in AR. The authoring tools were built leveraging concepts from the 3D user interfaces and interaction techniques literature. We found from early research in the field and our experimentation that scenario and object behavior authoring are substantial aspects needed to create a training experience by an author. This work also presents a technique to author object component behaviors with high usability scores, followed by an analysis of the different aspects of authoring object component behaviors across AR, VR, and Desktop. User studies were run to evaluate authoring strategies, and the results provide insights into future directions for building AR/VR immersive authoring tools. Finally, we discuss how this knowledge can influence the development, guidelines, and strategies in the direction of a more compelling set of tools to author augmented reality SBT experiences.

Notes

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Graduation Date

2022

Semester

Fall

Advisor

Laviola II, Joseph

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Computer Science

Degree Program

Computer Science

Format

application/pdf

Identifier

CFE0009420; DP0027143

URL

https://purls.library.ucf.edu/go/DP0027143

Language

English

Release Date

December 2022

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

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