Gilbert–Johnson–Keerthi distance algorithm: Difference between revisions

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Revision as of 01:15, 23 January 2009

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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 algorithm|simplexessimplex]]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.