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Python implementation of MPPI (Model Predictive Path-Integral) controller to understand the basic idea. Mandatory dependencies are numpy and matplotlib only.

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License: MIT Poetry

Simple MPPI Implementation with Python

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.

pathtracking and obstacle avoidance demonstraion

pathtracking demonstraion

swinging up pendulum demonstraion

swinging up pendulum demonstraion

Dependency

  • python

    • version 3.10 or higher is recommended.
  • poetry

    • setting up python environment easily and safely.
    • only numpy, matplotlib, notebook are needed to run all scripts in this repository.
  • ffmpeg

    • mp4 movie writer

    • installation details
      • For Ubuntu Users
        • sudo apt-get update
        • sudo apt-get -y install ffmpeg
      • For Windows Users
        • Install scoop
        • scoop install ffmpeg
      • For macOS Users
      • Check the official website if necessary

Setup

git clone https://github.com/MizuhoAOKI/python_simple_mppi.git
cd python_simple_mppi
poetry install

Usage

Path Tracking

pendulum

Simple Path Tracking

  • 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

Path Tracking with Obstacle Avoidance

  • 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

Pendulum

pendulum

  • 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

CartPole

cartpole

  • 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

References

  1. G. Williams et al. "Information-Theoretic Model Predictive Control: Theory and Applications to Autonomous Driving"