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Real-world vs simulation datasets
Compare real-world and simulation datasets for robotics, including where each is strong and where teams usually need blended data strategies.
Most teams do not need to choose only one. They need to understand where simulation accelerates iteration and where real-world data becomes non-negotiable.
Simulation strengths
- Cheap scaleFast coverage for policy warm starts and ablations.
- Perfect labelsUseful for controlled evaluation and debugging.
- Controlled resetsBetter for scenario sweeps than live operations.
Real-world strengths
- Sensor noise and calibration drift
- Contact variation and wear
- Human corrections and interventions
- Operational edge cases
Best use
Use this page to frame a blended strategy: simulation for coverage, real-world for truth, and evaluation data for deployment confidence.