A New Parallel Collision Detection Algorithm Based on Particle Swarm Optimization

摘要

A new parallel collision detection algorithm based on Particle Swarm Optimization (PSO) is proposed in the paper. The collision detection problem is transformed to the optimization problems of the space formed by the number of characteristics of the two models. Using the intelligent search features of the PSO algorithm, the search process of the local minimum characteristics is completed during collision detection. The optimization model is fully parallel by dividing polyhedron algorithm. The parallel method improves the detection speed for further step. The test results show the collision detection algorithm based on PSO can improve time efficiency. With the application of parallel technology, the detection speed can be further improved by adjusting the number of computer nodes.