An Algorithm for Rapidly Computing the Minimum Distance between Two Objects Collision Detection
A novel efficient algorithm for computing the minimum distance between two objects in collision detection is proposed, which is based on extracting the objects’ feature points set to represent the shape figure, and computing the point sets to get the minimum distance between the two objects. Theoretical analyses and experimental results show that the method reduces the computing complexity, improves the efficiency and meets the requirement of real time of collision detection.
In this article, we study nonsmooth convex minimax programming problems with cone constraint and abstract constraint. Our aim is to develop sequential Lagrange multiplier rules for this class of problems in the absence of any constraint qualification. These rules are obtained in terms of ∊-subdifferentials of the functions. As an application of these rules, a sequential dual is proposed and sequential duality results are presented.