Synthetic Simulation Pipelines for Embodied AI

Asset Libraries#

• Curate reusable meshes, textures, and materials representing everyday objects, tools, and environments.
• Maintain metadata describing physical properties (mass, friction), semantic labels, and usage rights.

Procedural Generation#

• Use rule-based systems to assemble scenes (e.g., home interiors, warehouses) with randomized layouts.
• Apply domain randomization: vary lighting, textures, object placement, clutter, and weather to improve robustness.
• Integrate constraint solvers to ensure physically plausible configurations (no overlapping objects, reachable targets).

Language-Driven Scripting#

• Employ natural-language templates to specify scenarios (“Set up a kitchen counter with utensils, randomize lighting, place two fragile items”).
• Convert scripts into structured representations (JSON, scene graphs) for the simulator.
• Allow domain experts to author scenarios without deep 3D tool expertise.