SceneSmith: Agentic Generation of Simulation-Ready Indoor Scenes
SceneSmith is a new AI framework that generates realistic, physics-accurate indoor environments from natural language descriptions for robot simulation and training. The system produces 3-6x more objects than existing methods with minimal collisions, achieving 92% realism in user evaluations and enabling automated robot policy testing.