ACROSS translates BioTac tactile signals to DIGIT images via 3D deformation meshes to enable cross-sensor dataset reuse.
Sim-to-Real for Robotic Tactile Sensing Via Physics-Based Simulation and Learned Latent Projections
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
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cs.RO 2years
2024 2verdicts
UNVERDICTED 2representative citing papers
XGBoost and transformer models trained without temperature data outperform feed-forward neural networks in predicting BioTac sensor outputs when using force and contact inputs.
citing papers explorer
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ACROSS: A Deformation-Based Cross-Modal Representation for Robotic Tactile Perception
ACROSS translates BioTac tactile signals to DIGIT images via 3D deformation meshes to enable cross-sensor dataset reuse.
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Optimizing BioTac Simulation for Realistic Tactile Perception
XGBoost and transformer models trained without temperature data outperform feed-forward neural networks in predicting BioTac sensor outputs when using force and contact inputs.