Atlas-GS: An End-to-End Implementation of Gaussian World Modeling for Embodied Robotics
We present Atlas-GS v1, the first end-to-end implementation of a 3D Gaussian world-modeling pipeline within the Nature Foundation Models (NFM) hierarchy. Atlas-GS ingests RGB-D observations, constructs a persistent Gaussian field, localizes against that map, persists world state across sessions, and logs state–action–state transitions. The system implements Phases 0–6 as a modular Python package with CLI tools and demo video generation—without requiring GPU hardware for v1 validation. We report empirical results on TUM RGB-D (4,018 Gaussians, 0.0102 m localization RMSE) and synthetic sequences.