cbf_quadrotor
Control Barrier Functions (CBFs) for Quadrotors. Based on hocherie/2d_grid_playground for dynamics simulator, nominal controllers, range sensing.
Accompanying Lecture for Air Lab Summer School 2020: PDF Slides
Getting Started
Installation
Please install pyenv, if not already. Instructions. Specifically, follow (1) build dependecies and (2) Using the pyenv-installer.
git clone https://github.com/hocherie/cbf_quadrotor.git # Clone Repo
cd cbf_quadrotor # Navigate to folder
$ pyenv install -v 3.7.2 # Install Python
$ pyenv virtualenv 3.7.2 safety-cbf # Make Virtual Environment
$ pyenv local safety-cbf # Activate virtual env
$ pip install -r requirements.txt # Install dependencies
Accompanying Paper
"Provably Safe" in the Wild: Testing Control Barrier Functions on a Vision-Based Quadrotor in an Outdoor Environment.
Presented in 2020 RSS Workshop in Robust Autonomy. [PDF] [Flight Tests]
@inproceedings{hoshih2020provablyinwild,
title = {"Provably Safe" in the Wild: Testing Control Barrier Functions on a Vision-Based Quadrotor in an Outdoor Environment},
author = {Ho, Cherie* and Shih, Katherine* and Grover, Jaskaran and Liu, Changliu and Scherer, Sebastian},
booktitle = {RSS 2020 Workshop in Robust Autonomy},
year = {2020},
url = {https://openreview.net/pdf?id=CrBJIgBr2BK}
}
Author
Cherie Ho (cherieh@cs.cmu.edu)
Mohammadreza Mousaei (mmousaei@andrew.cmu.edu)
Kate Shih (kshih@andrew.cmu.edu)