Beyond Binary: Sim-to-Real Dexterous Manipulation with Physics-Grounded Contact Representation

ArXi:2605.28812v1 Announce Type: cross A primary bottleneck in contact-rich manipulation is the difficulty of collecting real-world data. Sim-to-real reinforcement learning offers a scalable alternative, but the simulation-reality gap prevents information-dense modalities like touch from being effectively used. Existing sim-to-real methods often mitigate this gap by simplifying tactile data into coarse low-dimensional features -- sacrificing the richness required for complex manipulation. In this work, we.