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Sim-to-Real Transfer
Deploying a policy trained entirely in simulation on a physical robot. The simulation-reality gap (differences in physics, rendering, and sensor models) is bridged through domain randomization, system identification, and domain adaptation. Sim-to-real is the dominant paradigm for RL-based locomotion and increasingly for manipulation. Success depends on simulation fidelity and randomization strategy.