Synthetic Simulation Pipelines for Embodied AI

Synthetic data must be managed like any critical dataset.

• Log raw trajectories (states, actions, rewards) along with high-level summaries.
• Annotate automatically using ground-truth from the simulation (object poses, collision events, semantic labels).
• Version datasets, capturing generator seed, simulator build, and scenario scripts.
• Maintain lineage graphs linking simulations to trained models and downstream evaluations.

Adopt data quality checks: spot-check scenes for artifacts, run anomaly detection on telemetry, and validate annotation accuracy through random audits.