Awesome
<!-- _____ _ _ __ > < / ____| | | |/ / > < ___ _ __ ___ _ __ | | __ | | ' / > < / _ \| '_ \ / _ \ '_ \| | |_ |_ | | < > < | (_) | |_) | __/ | | | |__| | |__| | . \ > < \___/| .__/ \___|_| |_|\_____|\____/|_|\_\ > < | | > < |_| > < > < Copyright 2022 Mattia Montanari, University of Oxford > < > < This program is free software: you can redistribute it and/or modify it under > < the terms of the GNU General Public License as published by the Free Software > < Foundation, either version 3 of the License. You should have received a copy > < of the GNU General Public License along with this program. If not, visit > < > < https://www.gnu.org/licenses/ > < > < This program is distributed in the hope that it will be useful, but WITHOUT > < ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS > < FOR A PARTICULAR PURPOSE. See GNU General Public License for details. -->OpenGJK
A fast and robust C implementation of the Gilbert-Johnson-Keerthi (GJK) algorithm with interfaces for C#, Go, Matlab and Python. A Unity Plug-in is also available in another repository.
Useful links: API references, documentation and automated benchmarks.
Getting started
On Linux, Mac or Windows, install a basic C/C++ toolchain - for example: git, compiler and cmake.
Next, clone this repo:
git clone https://github.com/MattiaMontanari/openGJK
Then use these commands to build and run an example:
cmake -E make_directory build
cmake -E chdir build cmake -DCMAKE_BUILD_TYPE=Release ..
cmake --build build
cmake -E chdir build/examples/c ./example_lib_opengjk_ce
The successful output should be:
Distance between bodies 3.653650
However, if you do get an error - any error - please file a bug. Support requests are welcome.
Use OpenGJK in your project
The best source to learn how to use OpenGJK are the examples. They are listed here for C, C#, Go, Matlab, ZIg and Python. I aim to publish few more for Julia.
Take a look at the examples folder in this repo and have fun. File a request if you wish to see more!
Contribute
You are very welcome to:
- Create pull requests of any kind
- Let me know if you are using this library and find it useful
- Open issues with request for support because they will help you and many others
- Cite this repository (a sweet GitHub feature) or my paper: Montanari, M. et at, Improving the GJK Algorithm for Faster and More Reliable Distance Queries Between Convex Objects (2017). ACM Trans. Graph.