AI-Driven Procedural Content Generation for VR/AR Environments
Yu Nong, Jia-Qiang Sun, Kai You Wang · 2025
This research paper explores the cutting-edge domain of AI-driven procedural content generation (PCG) for virtual reality (VR) and augmented reality (AR) environments. We investigate the synergy between artificial intelligence techniques and PCG methodologies to create dynamic, adaptive, and immersive content for VR/AR applications. The paper presents novel algorithms, frameworks, and case studies that demonstrate the potential of AI-PCG in enhancing user experiences, reducing development costs, and enabling personalized content creation at scale. We also address the unique challenges posed by VR/AR environments, such as real-time performance requirements, spatial coherence, and user interaction complexities. Our findings suggest that AI-driven PCG has the potential to revolutionize content creation for VR/AR, opening new avenues for interactive storytelling, adaptive game design, and immersive training simulations.