A neural model reduces high-resolution tactile elastomer simulation cost by over 65% while improving geometric fidelity and enabling differentiable inference.
Efficient tactile simulation with differentiability for robotic manipulation
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
DOT-Sim uses MPM physics plus learned residual optics to simulate deformable tactile sensors, supporting zero-shot sim-to-real transfer for classification and control tasks.
citing papers explorer
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Reduced-order Neural Modeling with Differentiable Simulation for High-Detail Tactile Perception
A neural model reduces high-resolution tactile elastomer simulation cost by over 65% while improving geometric fidelity and enabling differentiable inference.
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DOT-Sim: Differentiable Optical Tactile Simulation with Precise Real-to-Sim Physical Calibration
DOT-Sim uses MPM physics plus learned residual optics to simulate deformable tactile sensors, supporting zero-shot sim-to-real transfer for classification and control tasks.