https://github.com/myohub/myosuite
MyoSuite is a collection of environments/tasks to be solved by musculoskeletal models simulated with the MuJoCo physics engine and wrapped in the OpenAI gym API.
Science Score: 49.0%
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○CITATION.cff file
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✓.zenodo.json file
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✓DOI references
Found 1 DOI reference(s) in README -
✓Academic publication links
Links to: arxiv.org -
○Academic email domains
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○Scientific vocabulary similarity
Low similarity (15.3%) to scientific vocabulary
Keywords
Repository
MyoSuite is a collection of environments/tasks to be solved by musculoskeletal models simulated with the MuJoCo physics engine and wrapped in the OpenAI gym API.
Basic Info
- Host: GitHub
- Owner: MyoHub
- License: apache-2.0
- Language: Python
- Default Branch: main
- Homepage: https://sites.google.com/view/myosuite
- Size: 396 MB
Statistics
- Stars: 1,013
- Watchers: 28
- Forks: 139
- Open Issues: 42
- Releases: 12
Topics
Metadata Files
README.md
MyoSuite is a collection of musculoskeletal environments and tasks simulated with the MuJoCo physics engine and wrapped in the OpenAI gym API to enable the application of Machine Learning to bio-mechanic control problems.
Documentation | Tutorials | Task specifications
Below is an overview of the tasks in the MyoSuite.
Installations
You will need Python 3.9 or later versions.
It is recommended to use Miniconda and to create a separate environment with:
bash
conda create --name myosuite python=3.9
conda activate myosuite
It is possible to install MyoSuite with:
bash
pip install -U myosuite
for advanced installation, see here.
Test your installation using the following command (this will return also a list of all the current environments):
bash
python -m myosuite.tests.test_myo
You can also visualize the environments with random controls using the command below:
bash
python -m myosuite.utils.examine_env --env_name myoElbowPose1D6MRandom-v0
NOTE: On MacOS, we moved to mujoco native launch_passive which requires that the Python script be run under mjpython:
bash
mjpython -m myosuite.utils.examine_env --env_name myoElbowPose1D6MRandom-v0
It is possible to take advantage of the latest MyoSkeleton. Once added (follow the instructions prompted by python -m myosuite_init), run:
bash
python -m myosuite.utils.examine_sim -s myosuite/simhive/myo_model/myoskeleton/myoskeleton.xml
Examples
It is possible to create and interface with MyoSuite environments just like any other OpenAI gym environments. For example, to use the myoElbowPose1D6MRandom-v0 environment, it is possible simply to run:
python
from myosuite.utils import gym
env = gym.make('myoElbowPose1D6MRandom-v0')
env.reset()
for _ in range(1000):
env.mj_render()
env.step(env.action_space.sample()) # take a random action
env.close()
You can find our tutorials on the general features and the ICRA2023 Colab Tutorial ICRA2024 Colab Tutorial
on how to load MyoSuite models/tasks, train them, and visualize their outcome. Also, you can find baselines to test some pre-trained policies.
License
MyoSuite is licensed under the Apache License.
Citation
If you find this repository useful in your research, please consider giving a star ⭐ and cite our arXiv paper by using the following BibTeX entrys.
BibTeX
@Misc{MyoSuite2022,
author = {Vittorio, Caggiano AND Huawei, Wang AND Guillaume, Durandau AND Massimo, Sartori AND Vikash, Kumar},
title = {MyoSuite -- A contact-rich simulation suite for musculoskeletal motor control},
publisher = {arXiv},
year = {2022},
howpublished = {\url{https://github.com/myohub/myosuite}},
year = {2022}
doi = {10.48550/ARXIV.2205.13600},
url = {https://arxiv.org/abs/2205.13600},
}
Owner
- Name: MyoHub
- Login: MyoHub
- Kind: organization
- Repositories: 1
- Profile: https://github.com/MyoHub
GitHub Events
Total
- Create event: 15
- Release event: 4
- Issues event: 30
- Watch event: 150
- Delete event: 6
- Member event: 1
- Issue comment event: 80
- Push event: 47
- Pull request review event: 107
- Pull request review comment event: 89
- Pull request event: 60
- Fork event: 36
Last Year
- Create event: 15
- Release event: 4
- Issues event: 30
- Watch event: 150
- Delete event: 6
- Member event: 1
- Issue comment event: 80
- Push event: 47
- Pull request review event: 107
- Pull request review comment event: 89
- Pull request event: 60
- Fork event: 36
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 15
- Total pull requests: 26
- Average time to close issues: 3 months
- Average time to close pull requests: 6 days
- Total issue authors: 12
- Total pull request authors: 7
- Average comments per issue: 1.2
- Average comments per pull request: 0.62
- Merged pull requests: 13
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 14
- Pull requests: 26
- Average time to close issues: about 2 months
- Average time to close pull requests: 6 days
- Issue authors: 11
- Pull request authors: 7
- Average comments per issue: 1.29
- Average comments per pull request: 0.62
- Merged pull requests: 13
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- Vittorio-Caggiano (6)
- andreh1111 (5)
- XiaobenLi00 (5)
- vikashplus (4)
- P-Schumacher (4)
- Ming-Start (3)
- llll111111 (2)
- LoFull (2)
- JudyYe (2)
- YusseffRuiz (2)
- abhishekpatil32 (2)
- Baliencasia (2)
- ViktorM (2)
- LyesBesylex (2)
- anjugopinath (2)
Pull Request Authors
- Vittorio-Caggiano (30)
- elladyr (11)
- cherylwang20 (11)
- vikashplus (9)
- fl0fischer (6)
- P-Schumacher (5)
- raku-slyu (4)
- Balint-H (3)
- siyuan-liu-casia (3)
- jamesheald (3)
- Yingfan99327 (2)
- andreh1111 (1)
- kywch (1)
- v9joshi (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 3
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Total downloads:
- pypi 825 last-month
-
Total dependent packages: 0
(may contain duplicates) -
Total dependent repositories: 1
(may contain duplicates) - Total versions: 116
- Total maintainers: 1
proxy.golang.org: github.com/myohub/myosuite
- Documentation: https://pkg.go.dev/github.com/myohub/myosuite#section-documentation
- License: apache-2.0
-
Latest release: v2.10.0+incompatible
published 6 months ago
Rankings
proxy.golang.org: github.com/MyoHub/myosuite
- Documentation: https://pkg.go.dev/github.com/MyoHub/myosuite#section-documentation
- License: apache-2.0
-
Latest release: v2.10.0+incompatible
published 6 months ago
Rankings
pypi.org: myosuite
Musculoskeletal environments simulated in MuJoCo
- Homepage: https://sites.google.com/view/myosuite
- Documentation: https://myosuite.readthedocs.io/
- License: Apache 2.0
-
Latest release: 2.10.0
published 6 months ago
Rankings
Maintainers (1)
Dependencies
- actions/checkout main composite
- actions/setup-python v3 composite
- pypa/gh-action-pypi-publish master composite
- sphinx ==4.0.2
- sphinx-autobuild *
- sphinx-rtd-theme ==0.5.2
- hydra-core *
- hydra-submitit-launcher *
- matplotlib *
- six *
- tabulate *
- torch *
- actions/checkout v3 composite
- actions/setup-python v3 composite
- conda-incubator/setup-miniconda v2 composite
- Pillow *
- click *
- dm-control ==1.0.14
- flatten_dict *
- gym ==0.13
- h5py *
- mujoco ==2.3.7
- numpy *
- pink-noise-rl *
- sk-video *
- termcolor *