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Achieve a 50% boost in real-world control of tendon-driven robots by training RL policies in simulation with a learned tendon force model, bridging the sim-to-real gap.
Forget computationally expensive fluid dynamics: this work shows that a simple, stateless model, carefully calibrated to real-world data, can create surprisingly effective digital twins for soft underwater robots.
Forget hand-tuning your robot simulator: this system uses paired real-world videos and language models to automatically diagnose and fix physics mismatches with interpretable rationales.
