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Paper · arXiv

HydroShear: Hydroelastic Shear Simulation for Tactile Sim-to-Real Reinforcement Learning

In this paper, we address the problem of tactile sim-to-real policy transfer for contact-rich tasks. Existing methods primarily focus on vision-based sensors and emphasize image rendering quality while providing overly simplistic models of force and shear. Consequently, these models exhibit a large sim-to-real gap for many dexterous tasks. Here, we present HydroShear, a non-holonomic hydroelastic tactile simulator that advances the state-of-the-art by modeling: a) stick-slip transitions, b) path-dependent force and shear build up, and c) full SE(3) object-sensor interactions. HydroShear extends hydroelastic contact models using Signed Distance Functions (SDFs) to track the displacements o...

AuthorsAn Dang, Jayjun Lee, Mustafa Mukadam et al.
Primary categorycs.RO
Published28 February 2026
Last updated at source28 February 2026
cs.ROcs.AI
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