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openGJK: compute minimum distance between 3D polyhedra

Version 1.2 (41.1 KB) by Mattia

Fast and reliable implementation of the Gilbert-Johnson-Keerthi (GJK) algorithm. University of Oxford.

https://www.mattiamontanari.com/opengjk/

5.0

(2)

263 Downloads

Updated 25 Apr 2023

From GitHub

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This reposity implements a new verstion of the GJK algorithm to compute the minimum ditance between two convex bodies in 3D. All it needs are the coordinates of the bodies in [N x 3] matrices, where N is the number of points defining a body.

An example is provided in example2_mex/runme.m. By running this file, Matlab will compile a MEX funciton which is called thereaftert. To compile a MEX function you'll need a C/C++ compiler, please refer to Matlab documention or leave a comment below.

Thanks to Kwanyuan Chan for this tip to Windows users: Matlab users need to set up the MinGW-w64 C/C++ compiler before running the example2_mex/runme.m file. More about the compile and related setting procedures at:/matlabcentral/fileexchange/52848-matlab-support-for-mingw-w64-c-c-compiler

Cite As

Montanari, Mattia, et al. “Improving the GJK Algorithm for Faster and More Reliable Distance Queries Between Convex Objects.” ACM Transactions on Graphics, vol. 36, no. 4, Association for Computing Machinery (ACM), June 2017, p. 1, doi:10.1145/3072959.3083724.

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Montanari, Mattia, and Nik Petrinic. “OpenGJK for C, C# and Matlab: Reliable Solutions to Distance Queries between Convex Bodies in Three-Dimensional Space.” SoftwareX, vol. 7, Elsevier BV, Jan. 2018, pp. 352–55, doi:10.1016/j.softx.2018.10.002.

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MATLAB Release Compatibility

Created with R2018b

Compatible with R2016a and later releases

Platform Compatibility

Windows macOS Linux

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Versions that use the GitHub default branch cannot be downloaded

Version	Published	Release Notes
1.2	25 Apr 2023	link and docs
1.0.2	22 Mar 2021	Docs and links updates
1.0.1	22 Mar 2021	Update description.
1.0.0	16 Mar 2019

To view or report issues in this GitHub add-on, visit the GitHub Repository.

MLA	Montanari, Mattia, et al. “Improving the GJK Algorithm for Faster and More Reliable Distance Queries Between Convex Objects.” ACM Transactions on Graphics, vol. 36, no. 4, Association for Computing Machinery (ACM), June 2017, p. 1, doi:10.1145/3072959.3083724.
APA	Montanari, M., Petrinic, N., & Barbieri, E. (2017). Improving the GJK Algorithm for Faster and More Reliable Distance Queries Between Convex Objects. ACM Transactions on Graphics, 36(4), 1. Association for Computing Machinery (ACM). Retrieved from https://doi.org/10.1145%2F3072959.3083724
BibTeX	@article{Montanari_2017, doi = {10.1145/3072959.3083724}, url = {https://doi.org/10.1145%2F3072959.3083724}, year = 2017, month = {jun}, publisher = {Association for Computing Machinery ({ACM})}, volume = {36}, number = {4}, pages = {1}, author = {Mattia Montanari and Nik Petrinic and Ettore Barbieri}, title = {Improving the {GJK} Algorithm for Faster and More Reliable Distance Queries Between Convex Objects}, journal = {{ACM} Transactions on Graphics} }

MLA	Montanari, Mattia, and Nik Petrinic. “OpenGJK for C, C# and Matlab: Reliable Solutions to Distance Queries between Convex Bodies in Three-Dimensional Space.” SoftwareX, vol. 7, Elsevier BV, Jan. 2018, pp. 352–55, doi:10.1016/j.softx.2018.10.002.
APA	Montanari, M., & Petrinic, N. (2018). OpenGJK for C, C# and Matlab: Reliable solutions to distance queries between convex bodies in three-dimensional space. SoftwareX, 7, 352–355. Elsevier BV. Retrieved from https://doi.org/10.1016%2Fj.softx.2018.10.002
BibTeX	@article{Montanari_2018, doi = {10.1016/j.softx.2018.10.002}, url = {https://doi.org/10.1016%2Fj.softx.2018.10.002}, year = 2018, month = {jan}, publisher = {Elsevier {BV}}, volume = {7}, pages = {352--355}, author = {Mattia Montanari and Nik Petrinic}, title = {{OpenGJK} for C, C{\#}~and Matlab: Reliable solutions to distance queries between convex bodies in three-dimensional space}, journal = {{SoftwareX}} }