关键词: 碰撞检测, 层次包围盒, 混合算法, 量子粒子群算法, 差分进化算法

Abstract: Aiming at the accuracy and instantaneity of collision detection algorithm, a collision detection algorithm which is fused with intelligent algorithm is proposed. On the basis of random collision detection, a hybrid algorithm which is mixed quantum behavior particle swarm optimization algorithm and differential evolution algorithm is used to search with the hybrid bounding technique using to reduce the particle search space. The local attractor is used as the basis of differential variation, and the convergence rate of the algorithm is accelerated while expanding the diversity of the population, which effectively solves the problems of the traditional intelligent algorithm not suitable for the discrete space computation and the premature convergence. Aiming at the characteristics of random collision particle search space, the introduction of hybrid algorithm greatly improves the detection efficiency of collision detection algorithm, and solves the phenomenon of puncture and omission in the detection process. The experimental results show that this method improves the real-time and accuracy of deformable object collision detection.

Key words: collision detection, hybrid bounding box, hybrid algorithm, quantum behaved particle swarm optimization, differential evolution