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[ICRA2024] Stein Variational Guided Model Predictive Path Integral Control: Proposal and Experiments with Fast Maneuvering Vehicles

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Stein Variational Guided Model Predictive Path Integral Control (SVG-MPPI)

This package includes ROS implementation of Stein Variational Guided Model Predictive Path Integral Control: Proposal and Experiments with Fast Maneuvering Vehicles presented in ICRA 2024.

Overview

Tested Environment

  • Ubuntu Focal 20.04 (LTS)
  • ROS Noetic
Basic Instllation

Install ROS noetic

Installation guide

# Set up your computer to accept software from packages.ros.org
sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'

# Set up your keys
sudo apt install -y curl # if you haven't already installed curl
curl -s https://raw.githubusercontent.com/ros/rosdistro/master/ros.asc | sudo apt-key add -
sudo apt update

# install ROS
sudo apt install -y ros-noetic-desktop-full

# Install other tools 
sudo apt install python3-osrf-pycommon python3-catkin-tools

Install Docker

Installation guide

# Install from get.docker.com
curl -fsSL https://get.docker.com -o get-docker.sh
sudo sh get-docker.sh
sudo groupadd docker
sudo usermod -aG docker $USER

Install Dependencies

cd proj-svg_mppi
make setup

Build Controllers

cd proj-svg_mppi
make build

Run Simulation with Visualization

Launch simulator in the Docker container

cd proj-svg_mppi
./script/launch_simulator.sh

Launch controllers in another terminal

cd proj-svg_mppi
./script/launch_controllers.sh 

You can change the all MPPI parameters and settings in the yaml file

Evaluation

You can reproduce all simulation results in the paper by one command:

cd proj-svg_mppi/script
./eval_all.sh

Or, You can evaluate a fixed parameters by this command:

cd proj-svg_mppi/script
./eval.sh

Note: The evaluation is used asynchronous simulation using ROS. So, the results can be slightly changed even if all seeds are fixed.

Citation

@inproceedings{honda2024stein,
  title={Stein Variational Guided Model Predictive Path Integral Control: Proposal and Experiments with Fast Maneuvering Vehicles},
  author={Honda, Kohei and Akai, Naoki and Suzuki, Kosuke and Aoki, Mizuho and Hosogaya, Hirotaka and Okuda, Hiroyuki and Suzuki, Tatsuya},
  booktitle={2024 IEEE International Conference on Robotics and Automation (ICRA)},
  pages={7020--7026},
  year={2024},
  organization={IEEE}
}

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[ICRA2024] Stein Variational Guided Model Predictive Path Integral Control: Proposal and Experiments with Fast Maneuvering Vehicles

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