Collision Detection Based on Surface Simplification and Particle Swam Optimization

Abstract

We present an efficient stochastic collision detection based on surface simplification and particle swam optimization (PSO). In this framework, first, the search space is reduced by surface simplification during the pre-process and then the interference triangles are gained by PSO. This framework takes the surface simplification’s advantage of decreasing the triangles dramatically with little geometry error. In order to handle every collision detection step, we use surface simplification and PSO, by which user not only can balance performance and detection quality, but also increase the speed of collision detection.