Distances to objects of interest in Virtual Reality (VR) are often systematically misperceived, and these perceived spatial distortions cause difficulties in the operators' ability to execute fine motor actions, increased errors in interaction and user frustration, thereby diminishing the effectiveness of task performance and psychomotor skills training in VR simulations, especially in applications such as simulated robot manipulations, flight and driving simulation, and surgical training and rehabilitation simulations. This project addresses the problem of depth perception in VR by examining: (a) how properties of the virtual self-representations or embodiment (also known as self-avatars) in VR affects depth perception in personal space, which is the region of space extending to the limits of the operator's reach; (b) how longitudinal or long-term experiences in VR influences or calibrates the effects of self-avatars on depth perception in personal space VR interactions. This research will directly address a grand challenge for engineering, as determined by the National Academy of Engineering, which is to enhance VR. The empirical data, measurement protocols, case studies and application guidelines derived from this project will substantially augment the much-needed body of knowledge in understanding the relationship between embodiment, visuo-motor recalibration to self-avatar properties, and depth perception in VR. The longitudinal research component will foster the exposure of undergraduate and graduate students to advanced VR development and the process of conducting rigorous user evaluation. The research and educational activities of the project will lead to enhanced consumer experiences in VR by improving user experience and usability of interactive applications for entertainment, psychomotor skills learning and rehabilitation.

The project is among the first to thoroughly investigate visuo-motor recalibration to anthropomorphic and anthropometric properties of self-avatars on near-field or personal space depth perception in VR, and how their impact with calibration changes over time with increased VR experience. The specific goals of this project are: (1) Investigate the effects of the anthropomorphic and anthropometric properties of self-avatars on scaling depth perception, body ownership and perceived reach capabilities in VR. (2) Empirically evaluate to what extent self-avatar based interaction in VR calibrates users' depth perception, body ownership and body schema. (3) Investigate how the effects of self-avatars on calibration of depth perception varies over time in longitudinal exposures, as users gain more experience with the task and VR in general. (4) Integrate VR development, user study design, quantitative and qualitative research methods in undergraduate and graduate education. The empirical investigation of self-avatars in personal space VR interactions and data from longitudinal experiences will generate a rich set of guidelines and recommendations for VR developers, researchers and consumers in utilizing the project?s derived techniques, metrics and measurement protocols to enhance user performance and validate research findings. This project will also enable students to experience hands-on and at-home learning and experimentation of VR systems, gathering much needed data on how longitudinal experiences affect spatial perception and enabling students to develop a strong sense of what constitutes a good VR design.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Division of Information and Intelligent Systems (IIS)
Type
Standard Grant (Standard)
Application #
2007435
Program Officer
Balakrishnan Prabhakaran
Project Start
Project End
Budget Start
2020-08-01
Budget End
2023-07-31
Support Year
Fiscal Year
2020
Total Cost
$498,982
Indirect Cost
Name
Clemson University
Department
Type
DUNS #
City
Clemson
State
SC
Country
United States
Zip Code
29634