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This work presents RebarSim, a visual sim-to-real system trained entirely in simulation, a privileged state-based teacher is trained with reinforcement learning over procedurally generated rebar geometries, then distilled into a multi-view student that maps raw RGB and proprioception directly to actions under extensive domain randomization.
WorldScape Policy 2.0 achieves unprecedented long-horizon autonomous planning by integrating reasoning-augmented memory with multimodal instruction processing.
