Model Predictive Path-Integral (MPPI) Control [G. Williams et al., 2018] is a promising sampling-based optimal control algorithm.
This repository is for understanding the basic idea of the algorithm.
-
- version 3.10 or higher is recommended.
-
- setting up python environment easily and safely.
- only
numpy
,matplotlib
,notebook
are needed to run all scripts in this repository.
-
-
mp4 movie writer
-
git clone https://github.com/MizuhoAOKI/python_simple_mppi.git
cd python_simple_mppi
poetry install
-
Run simulation
cd python_simple_mppi poetry run python scripts/mppi_pathtracking.py
-
Run jupyter notebook if you would like to check mathematical explanations on the algorithm.
cd python_simple_mppi poetry run jupyter notebook notebooks/mppi_pathtracking.ipynb
-
Run simulation
cd python_simple_mppi poetry run python scripts/mppi_pathtracking_obav.py
-
Run jupyter notebook if you would like to check mathematical explanations on the algorithm.
cd python_simple_mppi poetry run jupyter notebook notebooks/mppi_pathtracking_obav.ipynb
-
Run simulation to swing up a pendulum.
cd python_simple_mppi poetry run python scripts/mppi_pendulum.py
-
Run jupyter notebook if you would like to check mathematical explanations on the algorithm.
cd python_simple_mppi poetry run jupyter notebook notebooks/mppi_pendulum.ipynb
-
Run simulation of cartpole
cd python_simple_mppi poetry run python scripts/mppi_cartpole.py
-
Run jupyter notebook if you would like to check mathematical explanations on the algorithm.
cd python_simple_mppi poetry run jupyter notebook notebooks/mppi_cartpole.ipynb
- G. Williams et al. "Information-Theoretic Model Predictive Control: Theory and Applications to Autonomous Driving"