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.
RP1M: A Large-Scale Motion Dataset for Piano Playing with Bi-Manual Dexterous Robot Hands
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Adversarial Posture Regularization matches RL policy posture distributions to casual human piano-playing data to enforce human-like kinematics in dexterous hands, outperforming baselines on cPSI, BSE, and FAC metrics.
HandelBot refines simulation policies via physical rollouts and residual RL to achieve precise bimanual piano playing, outperforming direct sim transfer by 1.8x with only 30 minutes of real data across five songs.
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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Enforcing Human-like Kinematics in Dexterous Piano Playing via Adversarial Posture Regularization
Adversarial Posture Regularization matches RL policy posture distributions to casual human piano-playing data to enforce human-like kinematics in dexterous hands, outperforming baselines on cPSI, BSE, and FAC metrics.
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HandelBot: Real-World Piano Playing via Fast Adaptation of Dexterous Robot Policies
HandelBot refines simulation policies via physical rollouts and residual RL to achieve precise bimanual piano playing, outperforming direct sim transfer by 1.8x with only 30 minutes of real data across five songs.