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workflow-t
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master
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a0f9d219f5 | |
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@ -0,0 +1,26 @@
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name: Upload Python Package
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on:
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release:
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types: [created]
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jobs:
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deploy:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v2
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- name: Set up Python 3.6
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uses: actions/setup-python@v2
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with:
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python-version: '3.6'
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install setuptools wheel twine
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- name: Build and publish
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env:
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TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
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TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
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run: |
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python setup.py bdist_wheel
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twine upload dist/*
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20
README.md
20
README.md
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@ -17,8 +17,8 @@ Due to use only basic libralies (scipy, numpy), this library is easy to extend f
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|:----------|:---------------: |:----------------:|:----------------:|:----------------:|:----------------:|
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| Linear Model Predictive Control (MPC) | ✓ | x | x | x | x |
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| Cross Entropy Method (CEM) | ✓ | ✓ | x | x | x |
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| Model Preidictive Path Integral Control of Nagabandi, A. (MPPI) | ✓ | ✓ | x | x | x |
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| Model Preidictive Path Integral Control of Williams, G. (MPPIWilliams) | ✓ | ✓ | x | x | x |
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| Model Predictive Path Integral Control of Nagabandi, A. (MPPI) | ✓ | ✓ | x | x | x |
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| Model Predictive Path Integral Control of Williams, G. (MPPIWilliams) | ✓ | ✓ | x | x | x |
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| Random Shooting Method (Random) | ✓ | ✓ | x | x | x |
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| Iterative LQR (iLQR) | x | ✓ | x | ✓ | x |
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| Differential Dynamic Programming (DDP) | x | ✓ | x | ✓ | ✓ |
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@ -36,10 +36,10 @@ Following algorithms are implemented in PythonLinearNonlinearControl
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- [Cross Entropy Method (CEM)](https://arxiv.org/abs/1805.12114)
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- Ref: Chua, K., Calandra, R., McAllister, R., & Levine, S. (2018). Deep reinforcement learning in a handful of trials using probabilistic dynamics models. In Advances in Neural Information Processing Systems (pp. 4754-4765)
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- [script](PythonLinearNonlinearControl/controllers/cem.py)
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- [Model Preidictive Path Integral Control of Nagabandi, A. (MPPI)](https://arxiv.org/abs/1909.11652)
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- [Model Predictive Path Integral Control of Nagabandi, A. (MPPI)](https://arxiv.org/abs/1909.11652)
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- Ref: Nagabandi, A., Konoglie, K., Levine, S., & Kumar, V. (2019). Deep Dynamics Models for Learning Dexterous Manipulation. arXiv preprint arXiv:1909.11652.
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- [script](PythonLinearNonlinearControl/controllers/mppi.py)
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- [Model Preidictive Path Integral Control of Williams, G. (MPPIWilliams)](https://ieeexplore.ieee.org/abstract/document/7989202)
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- [Model Predictive Path Integral Control of Williams, G. (MPPIWilliams)](https://ieeexplore.ieee.org/abstract/document/7989202)
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- Ref: Williams, G., Wagener, N., Goldfain, B., Drews, P., Rehg, J. M., Boots, B., & Theodorou, E. A. (2017, May). Information theoretic MPC for model-based reinforcement learning. In 2017 IEEE International Conference on Robotics and Automation (ICRA) (pp. 1714-1721). IEEE.
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- [script](PythonLinearNonlinearControl/controllers/mppi_williams.py)
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- [Random Shooting Method (Random)](https://arxiv.org/abs/1805.12114)
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@ -83,25 +83,19 @@ You could know abount our environmets more in [Environments.md](Environments.md)
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## To install this package
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```
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python setup.py install
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```
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or
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```
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pip install .
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$ pip install PythonLinearNonlinearControl
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```
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## When developing the package
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```
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python setup.py develop
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$ python setup.py develop
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```
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or
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```
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pip install -e .
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$ pip install -e .
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```
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# Basic concepts
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2
setup.py
2
setup.py
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@ -14,7 +14,7 @@ setup(
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install_requires=install_requires,
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url='https://github.com/Shunichi09/PythonLinearNonlinearControl',
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license='MIT License',
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packages=find_packages(exclude=('tests')),
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packages=find_packages(exclude=('tests', 'scripts')),
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setup_requires=setup_requires,
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test_suite='tests',
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tests_require=tests_require
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