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HydroShear: Hydroelastic Shear Simulation for Tactile Sim-to-Real Reinforcement Learning
arXiv – CS AI|An Dang, Jayjun Lee, Mustafa Mukadam, X. Alice Wu, Bernadette Bucher, Manikantan Nambi, Nima Fazeli||7 views
🤖AI Summary
HydroShear is a new tactile simulation system for robotics that enables zero-shot sim-to-real transfer of reinforcement learning policies by accurately modeling force, shear, and stick-slip transitions. The system achieved 93% success rate across four dexterous manipulation tasks, significantly outperforming existing vision-based tactile simulation methods.
Key Takeaways
- →HydroShear introduces advanced tactile simulation modeling stick-slip transitions and path-dependent force buildup for robotics applications.
- →The system enables zero-shot sim-to-real transfer without additional training on real hardware.
- →Testing on four manipulation tasks showed 93% success rate versus 34% for vision-based methods and 58-61% for alternative shear simulations.
- →The approach uses hydroelastic contact models with Signed Distance Functions to track surface point displacements during sensor interactions.
- →HydroShear remains physics engine agnostic while generating computationally efficient force fields from arbitrary geometries.
#robotics#reinforcement-learning#simulation#tactile-sensing#sim-to-real#manipulation#machine-learning#hydroelastic#contact-modeling
Read Original →via arXiv – CS AI
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