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RoboPianist: Dexterous Piano Playing with Deep Reinforcement Learning (2023)
@inproceedings{robopianist2023, author = {Zakka, Kevin and Wu, Philipp and Smith, Laura and Gileadi, Nimrod and Howell, Taylor and Peng, Xue Bin and Singh, Sumeet and Tassa, Yuval and Florence, Pete and Zeng, Andy and Abbeel, Pieter}, title = {RoboPianist: Dexterous Piano Playing with Deep Reinforcement Learning}, booktitle = {Conference on Robot Learning (CoRL)}, year = {2023}, } TLDR We train anthropomorphic robot hands to play the piano using deep RL and release a simulated benchmark and dataset to advance high-dimensional control. This is a demo of our simulated piano playing agent trained with reinforcement learning.
@inproceedings{robopianist2023, author = {Zakka, Kevin and Wu, Philipp and Smith, Laura and Gileadi, Nimrod and Howell, Taylor and Peng, Xue Bin and Singh, Sumeet and Tassa, Yuval and Florence, Pete and Zeng, Andy and Abbeel, Pieter}, title = {RoboPianist: Dexterous Piano Playing with Deep Reinforcement Learning}, booktitle = {Conference on Robot Learning (CoRL)}, year = {2023}, } TLDR We train anthropomorphic robot hands to play the piano using deep RL and release a simulated benchmark and dataset to advance high-dimensional control. In RoboPianist, we found that the agent struggled to learn to play the piano with a sparse reward signal due to the exploration challenge associated with the high-dimensional action space.
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