Implementation of a virtual reality radiation protection game in Unity for Oculus Quest – UROP Spring Symposium 2021

Implementation of a virtual reality radiation protection game in Unity for Oculus Quest

Xinyi Zheng

Xinyi Zheng

Pronouns: She/hers

Research Mentor(s): Kimberlee Kearfott, Professor
Research Mentor School/College/Department: Nuclear Engineering and Radiological Sciences/Biomedical Engineering, College of Engineering
Presentation Date: Thursday, April 22, 2021
Session: Session 3 (1pm-1:50pm)
Breakout Room: Room 15
Presenter: 6

Event Link

Abstract

At its core, virtual reality (VR) technology seeks to create virtual experiences that reflect as closely as possible the movements and responses users would have to reality. While commonly used for entertainment, it has also found use in virtual training for jobs or tasks that require hands-on experience. This is especially relevant for radiation protection training, which requires familiarity with a variety of equipment, sources, and emergency procedures. The main question is how to implement this VR training effectively. On the most basic level, the core physics and user movement must be as realistic as possible. These objectives can be achieved by choosing a game engine that supports VR development, and a target VR device with a wide range of user mobility. For this project, Unity was chosen for its versatile VR support, including support for specific devices (Oculus Quest) and more generalized support systems that allow the game to be run on any device with the proper movement controls. Care was also taken in making in-game detector models and radiation physics scripts as realistic as possible. A well-designed VR game recreates and even exceeds the limits of hands-on training, as the player can be placed in complex and potentially dangerous situations without worries of cost or potential harm. A game which fully takes advantage of the VR platform teaches players proper handling of equipment and procedures while also providing more open-ended scenes (i.e. emergencies, high-risk scenarios) that are difficult to simulate in real life.

Authors: Xinyi Zheng, Daniel Calco, Nikita Abbaraju, Aiden Sable, Braden Saltus, Marlee Trager, Jordan Noey, Kimberlee Kearfott
Research Method: Computer Programming

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