SIM1: Physics-Aligned Simulator as Zero-Shot Data Scaler in Deformable Worlds

arXiv:2604.08544v2 Announce Type: replace-cross Abstract: Robotic manipulation with deformable objects represents a data-intensive regime in embodied learning, where shape, contact, and topology co-evolve in ways that far exceed the variability of rigids. Although simulation promises relief from the cost of real-world data acquisition, prevailing sim-to-real pipelines remain rooted in rigid-body abstractions, producing mismatched geometry, fragile soft dynamics, and motion primitives poorly suit