Personalizing VR Training Experiences through Optimization

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2021

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Abstract

In view of the emerging technologies in the virtual reality industry, VR provides a practical platform to train people in a safe and time-saving manner through serious virtual training tasks. Recent researches validate the effectiveness of virtual training, especially, it has been proved that personalized training in virtual reality is efficient enough to emphasize users' specific skills. Inspired by the recent works that automatically synthesize different training scenarios to achieve different personalized training targets through optimization techniques that can be applied to substitute manual configuration. My dissertation focuses on three interdisciplinary areas including personalized wheelchair training, exertion-aware path generation, and construction safety training. We first introduce an optimization-based approach for automatically generating virtual scenarios for wheelchair training in virtual reality. We then illustrate a novel approach for generating paths with desired exertion properties. After this, we will present a novel approach to synthesize construction safety training scenarios to train the users on how toproficiently inspect the potential hazards within the construction sites in virtual reality. In the end, we will draw a conclusion on existing research results and prospect the future trend of synthesizing personalized training scenarios in virtual reality.

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