融合智能算法的变形体碰撞检测算法研究  

Research on collision detection algorithm based on fusion intelligent algorithm

作　　者：靳雁霞[1] 任超 李照[1] 程思岳 王贺[1] 韩慧妍[1] JIN Yanxia;REN Chao;LI Zhao;CHEN Siyue;WANG He;HAN Huiyan(North University of China, School of Computer Science and Control Engineering, Taiyuan 030051, China)

机构地区：[1]中北大学计算机与控制工程学院,太原030051

出　　处：《计算机工程与应用》2017年第19期130-135,共6页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61379080);山西省自然科学基金(No.2015021093)

摘　　要：针对变形体碰撞检测算法的准确性与实时性问题,提出了一种融合智能算法的变形体碰撞检测算法。在随机碰撞检测的基础上,使用层次包围技术缩小粒子搜索空间,采用一种融合基于量子行为的粒子群算法与差分进化算法的混合智能算法进行搜索。该方法以局部吸引子作为差分变异基础,在扩大种群多样性的同时加快了算法收敛速度,有效地解决了传统智能算法不适应离散空间计算问题以及早熟收敛问题。针对随机碰撞粒子搜索空间特点,混合算法的引入大大提高了碰撞检测算法的检测效率,解决了检测过程中的穿刺与遗漏现象。经实验验证该方法在很大程度上提高了变形体碰撞检测的实时性与准确性。Aiming at the accuracy and instantaneity of collision detection algorithm,a collision detection algorithm whichis fused with intelligent algorithm is proposed.On the basis of random collision detection,a hybrid algorithm which ismixed quantum behavior particle swarm optimization algorithm and differential evolution algorithm is used to search withthe hybrid bounding technique using to reduce the particle search space.The local attractor is used as the basis of differentialvariation,and the convergence rate of the algorithm is accelerated while expanding the diversity of the population,whicheffectively solves the problems of the traditional intelligent algorithm not suitable for the discrete space computation andthe premature convergence.Aiming at the characteristics of random collision particle search space,the introduction ofhybrid algorithm greatly improves the detection efficiency of collision detection algorithm,and solves the phenomenon ofpuncture and omission in the detection process.The experimental results show that this method improves the real-timeand accuracy of deformable object collision detection.

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 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]