Overview
This project aims to turn real-world spatial models into diverse, interactive environments for embodied AI. Combining procedural generation, physics-based simulation, and synthetic data, it explores indoor public spaces, outdoor environments, and the transitions between them. The goal is to support training and reproducible evaluation of how embodied agents perceive, navigate, and interact with complex physical environments.