Gilbert–Johnson–Keerthi distance algorithm: Difference between revisions

Revision as of 03:49, 14 February 2011

Revision as of 00:27, 8 December 2011

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The '''Gilbert–Johnson–Keerthi distance [[algorithm]]''' is a method of determining the minimum distance between two [[convex set]]s. Unlike many other distance algorithms, it does not require that the geometry data be stored in any specific format, but instead relies solely on a [[support (mathematics)|support function]] to iteratively generate closer [[simplex|simplices]]es to the correct answer using the [[Minkowski sum]] (CSO) of two convex shapes.

"Enhanced GJK" algorithms use edge information to speed up the algorithm by following edges when looking for the next simplex. This improves performance substantially for polytopes with large numbers of vertices.