Synthetic Simulation Pipelines for Embodied AI

Simulation becomes useful when agents learn from it.

• Provide standardized APIs (Python, C++, Rust) for connecting policies to the simulator.
• Support reinforcement learning (RL), imitation learning, and hybrid approaches.
• Implement vectorized environments for RL to accelerate experience collection.
• Integrate curriculum learning: start with simplified tasks, ramp up complexity, and track mastery.

Tooling#

• Use orchestration frameworks to manage experiment configurations, hyperparameter sweeps, and logging.
• Store models, checkpoints, and evaluation metrics in centralized registries for reproducibility.