EmbodiedSmith: Scaling Embodied Data through Recursive Self-Improvement Flywheel in Simulation

EmbodiedSmith implements a recursive self-improvement flywheel to unify asset, scene, and task generation within a single simulation pipeline. The agentic refinement loop enables scene generation to anticipate task requirements, using language-driven customization to iteratively improve environment complexity and task diversity for robotic foundation model training.