The Gilbert-Johnson-Keerthi distance algorithm, or GJK, is a method for determining the minimum distance between two convex sets, first published by Elmer Gilbert, Daniel Johnson and S. Sathiya Keerthi in 1988. Rather than requiring geometry data in any specific format, it relies solely on a support function to iteratively generate closer simplices toward the correct answer using the Minkowski difference of the two convex shapes. Enhanced variants use edge information to speed convergence for polytopes with many vertices, and GJK is widely used for real-time collision detection in physics engines and video games because it converges quickly when reused incrementally from frame to frame.
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Gilbert-Johnson-Keerthi distance algorithm (Wikipedia)
In Field: Algorithms and Complexity Theory, Lead sentence
Gilbert-Johnson-Keerthi distance algorithm is a method of determining the minimum distance between two convex sets, first published by Elmer G. Gilbert, Daniel W. Johnson, and S. Sathiya Keerthi in 1988. Unlike many other distance algorithms, it does not requi
In Group: Geometric Intersection, Proximity and Measurement Algorithms, Lead
The Gilbert-Johnson-Keerthi distance algorithm is a method of determining the minimum distance between two convex sets, first published by Elmer G. Gilbert, Daniel W. Johnson, and S. Sathiya Keerthi in 1988.
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