Assess
Why?
- Bridging the gap between simulated environments and real-world deployment is crucial for Physical AI and robotics.
- Effective sim2real can reduce costly real-world data collection and speed up development cycles.
What?
- Invest in domain randomization, system identification, and validation approaches to improve real-world transfer.
- Build pipelines for closed-loop validation that include simulation, hardware-in-the-loop, and staged rollouts.
- Track sim2real metrics as part of model validation and release criteria.