robopianist
[CoRL '23] Dexterous piano playing with deep reinforcement learning.
Science Score: 44.0%
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○Scientific vocabulary similarity
Low similarity (14.3%) to scientific vocabulary
Keywords
Repository
[CoRL '23] Dexterous piano playing with deep reinforcement learning.
Basic Info
- Host: GitHub
- Owner: google-research
- License: apache-2.0
- Language: Python
- Default Branch: main
- Homepage: https://kzakka.com/robopianist/
- Size: 2.18 MB
Statistics
- Stars: 665
- Watchers: 13
- Forks: 50
- Open Issues: 7
- Releases: 6
Topics
Metadata Files
README.md
RoboPianist: Dexterous Piano Playing with Deep Reinforcement Learning
RoboPianist is a new benchmarking suite for high-dimensional control, targeted at testing high spatial and temporal precision, coordination, and planning, all with an underactuated system frequently making-and-breaking contacts. The proposed challenge is mastering the piano through bi-manual dexterity, using a pair of simulated anthropomorphic robot hands.
This codebase contains software and tasks for the benchmark, and is powered by MuJoCo.
- Latest Updates
- Getting Started
- Installation
- MIDI Dataset
- CLI
- Contributing
- FAQ
- Citing RoboPianist
- Acknowledgements
- Works that have used RoboPianist
- License and Disclaimer
Latest Updates
- [24/12/2023] Updated install script so that it checks out the correct Menagerie commit. Please re-run
bash scripts/install_deps.shto update your installation. - [17/08/2023] Added a pixel wrapper for augmenting the observation space with RGB images.
- [11/08/2023] Code to train the model-free RL policies is now public, see robopianist-rl.
Getting Started
We've created an introductory Colab notebook that demonstrates how to use RoboPianist. It includes code for loading and customizing a piano playing task, and a demonstration of a pretrained policy playing a short snippet of Twinkle Twinkle Little Star. Click the button below to get started!
Installation
RoboPianist is supported on both Linux and macOS and can be installed with Python >= 3.8. We recommend using Miniconda to manage your Python environment.
Install from source
The recommended way to install this package is from source. Start by cloning the repository:
bash
git clone https://github.com/google-research/robopianist.git && cd robopianist
Next, install the prerequisite dependencies:
bash
git submodule init && git submodule update
bash scripts/install_deps.sh
Finally, create a new conda environment and install RoboPianist in editable mode:
```bash conda create -n pianist python=3.10 conda activate pianist
pip install -e ".[dev]" ```
To test your installation, run make test and verify that all tests pass.
Install from PyPI
First, install the prerequisite dependencies:
bash
bash <(curl -s https://raw.githubusercontent.com/google-research/robopianist/main/scripts/install_deps.sh) --no-soundfonts
Next, create a new conda environment and install RoboPianist:
```bash conda create -n pianist python=3.10 conda activate pianist
pip install --upgrade robopianist ```
Optional: Download additional soundfonts
We recommend installing additional soundfonts to improve the quality of the synthesized audio. You can easily do this using the RoboPianist CLI:
bash
robopianist soundfont --download
For more soundfont-related commands, see docs/soundfonts.md.
MIDI Dataset
The PIG dataset cannot be redistributed on GitHub due to licensing restrictions. See docs/dataset for instructions on where to download it and how to preprocess it.
CLI
RoboPianist comes with a command line interface (CLI) that can be used to download additional soundfonts, play MIDI files, preprocess the PIG dataset, and more. For more information, see docs/cli.md.
Contributing
We welcome contributions to RoboPianist. Please see docs/contributing.md for more information.
FAQ
See docs/faq.md for a list of frequently asked questions.
Citing RoboPianist
If you use RoboPianist in your work, please use the following citation:
bibtex
@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},
}
Acknowledgements
We would like to thank the following people for making this project possible:
- Philipp Wu and Mohit Shridhar for being a constant source of inspiration and support.
- Ilya Kostrikov for constantly raising the bar for RL engineering and for invaluable debugging help.
- The Magenta team for helpful pointers and feedback.
- The MuJoCo team for the development of the MuJoCo physics engine and their support throughout the project.
Works that have used RoboPianist
License and Disclaimer
MuJoco Menagerie's license can be found here. Soundfont licensing information can be found here. MIDI licensing information can be found here. All other code is licensed under an Apache-2.0 License.
This is not an officially supported Google product.
Owner
- Name: Google Research
- Login: google-research
- Kind: organization
- Location: Earth
- Website: https://research.google
- Repositories: 226
- Profile: https://github.com/google-research
Citation (CITATION.cff)
cff-version: 1.2.0
authors:
- family-names: Zakka
given-names: Kevin
- family-names: Philipp
given-names: Wu
- family-names: Smith
given-names: Laura
- family-names: Gileadi
given-names: Nimrod
- family-names: Howell
given-names: Taylor
- family-names: Peng
given-names: Xue Bin
- family-names: Singh
given-names: Sumeet
- family-names: Tassa
given-names: Yuval
- family-names: Florence
given-names: Pete
- family-names: Zeng
given-names: Andy
- family-names: Abbeel
given-names: Pieter
date-released: "2023-04-01"
message: "If you use this software, please cite it as below."
title: "RoboPianist: Dexterous Piano Playing with Deep Reinforcement Learning"
url: "https://github.com/google-research/robopianist"
GitHub Events
Total
- Issues event: 1
- Watch event: 79
- Issue comment event: 2
- Push event: 2
- Pull request review event: 1
- Pull request event: 2
- Fork event: 6
Last Year
- Issues event: 1
- Watch event: 79
- Issue comment event: 2
- Push event: 2
- Pull request review event: 1
- Pull request event: 2
- Fork event: 6
Committers
Last synced: 9 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Kevin Zakka | k****a@g****m | 56 |
| zhaoyi11 | y****3@g****m | 1 |
| robopianist | r****y@g****m | 1 |
| Edward Hu | h****d@g****m | 1 |
Issues and Pull Requests
Last synced: 7 months ago
All Time
- Total issues: 15
- Total pull requests: 11
- Average time to close issues: 1 day
- Average time to close pull requests: 1 day
- Total issue authors: 10
- Total pull request authors: 6
- Average comments per issue: 1.67
- Average comments per pull request: 0.27
- Merged pull requests: 8
- Bot issues: 0
- Bot pull requests: 1
Past Year
- Issues: 3
- Pull requests: 2
- Average time to close issues: N/A
- Average time to close pull requests: 4 days
- Issue authors: 2
- Pull request authors: 2
- Average comments per issue: 1.67
- Average comments per pull request: 1.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- kevinzakka (3)
- hueds (3)
- hturner08 (2)
- zhaoyi11 (2)
- CBlagden (1)
- hail-mary (1)
- Minyoung1005 (1)
- boshi-an (1)
- tkaunlaky10 (1)
- SherAlex1998 (1)
Pull Request Authors
- kevinzakka (8)
- zhaoyi11 (2)
- dependabot[bot] (2)
- Sedkian (2)
- hueds (1)
- eltociear (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- pypi 82 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 11
- Total maintainers: 1
pypi.org: robopianist
A benchmark for high-dimensional robot control
- Homepage: https://github.com/google-research/robopianist
- Documentation: https://robopianist.readthedocs.io/
- License: Apache License 2.0
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Latest release: 1.0.10
published about 2 years ago