A Python package to make implementing control barrier functions (CBFs) and control Lyapunov functions (CLFs) simple.
First clone the environment into your desired location
git clone git@github.com:mit-ll-trusted-autonomy/cbfToolbox.git
cd cbfToolbox/
Create a conda environment to run the CBF Toolbox.
conda env create -f ./environment.yml
conda activate cbfToolbox
pip install -e .
Try running one of the examples.
python ./examples/simple_example.py
If there is an error with Gurobi when running the example, you may need to setup your Gurobi license. Follow instructions at this link to setup Gurobi.
Roberto Tron, Boston University - Advisor to CBF Toolbox development
Guang Yang
Max Cohen - cbfToolbox.jl
Ahmad Ahmad
Amy Fang
Helena Teixera-Dasilva
Cristian So
DISTRIBUTION STATEMENT A. Approved for public release. Distribution is unlimited.
© 2023 Massachusetts Institute of Technology.
Subject to FAR 52.227-11 – Patent Rights – Ownership by the Contractor (May 2014)
SPDX-License-Identifier: BSD-3-Clause
This material is based upon work supported by the Under Secretary of Defense for Research and Engineering under Air Force Contract No. FA8702-15-D-0001. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Under Secretary of Defense for Research and Engineering.
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The software/firmware is provided to you on an As-Is basis