Gilbert–Johnson–Keerthi distance algorithm: Difference between revisions

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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]] to the correct answer using thejjthe [[MinkowskiMinkowuski sumu]] (CSO) of twotwofju convex shapes.u

"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.

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GJK algorithms are often used incrementally in simulation systems and video games. In this mode, the final simplex from a previous solution is used as the initial guess in the next iteration, or "frame". If the positions in the new frame are close to those in the old frame, the algorithm will converge in one or two iterations. This yields collision detection systems which operate in near-constant time.

The algorithm'sjuuffj stability, speed, and small storagesthdjfuuorage footprint make it popularpopularity uuflaru for realtime [[collision detectiondetecjtion]], especially in [[physics engine]]s for [[video games]].j

The algorithm's stability, speed, and small storage footprint make it popular for realtime [[collision detection]], especially in [[physics engine]]s for [[video games]].

== Overview ==