A Sim2Real2Sim learning pipeline enables a real-world dexterous robot to play piano pieces including Happy Birthday and Ode to Joy with an average F1-score of 0.881.
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HTT learns shared representations across heterogeneous tactile sensors using a new paired dataset and pretraining objectives, enabling transfer to unseen sensors and tasks.
Tactile-WAM with TAAM improves mean success rate by 38.9% overall and 86% on contact-rich tasks on ManiFeel by using VideoClean mask and touch-aware bias to prevent tactile pollution in world action models.
Tac-DINO constructs a large tactile dataset and Vis-Tac Holographic Matching Benchmark, then proposes Vision-Tactile Patch Alignment (VTPA) methods that outperform non-aligned baselines on local-to-global feature matching.
citing papers explorer
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Learning to Play Piano in the Real World
A Sim2Real2Sim learning pipeline enables a real-world dexterous robot to play piano pieces including Happy Birthday and Ode to Joy with an average F1-score of 0.881.
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Heterogeneous Tactile Transformer
HTT learns shared representations across heterogeneous tactile sensors using a new paired dataset and pretraining objectives, enabling transfer to unseen sensors and tasks.
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Tactile-WAM: Touch-Aware World Action Model with Tactile Asymmetric Attention
Tactile-WAM with TAAM improves mean success rate by 38.9% overall and 86% on contact-rich tasks on ManiFeel by using VideoClean mask and touch-aware bias to prevent tactile pollution in world action models.