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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)

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Control Barrier Functions for Quadrotors, standalone with dynamics simulator, nominal controllers.

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