会议专题

Detection of Collision and self-Collision Using QPSO for Deformable models

-In order to improve the speed of deformable objects collision and self-collision detection, proposing a new kind of stochastic collision method which is based on Quantum-behaved Particle Swarm Optimization. In this new algorithm the collision detection problem is treated as a kind of problem which is similar with Dynamic and Multi-objective Optimization Problem(MOP) where as many of the collision pairs satisfying the collision conditions are detected in certain time interval, notice that the detected collision pairs are not necessarily the globally optimal solution. For this problem that is similar with MOP, the iteration searching process for quantum-behaved particle has been optimized, in this algorithm, once a new collision pair satisfying the condition is detected, then the next searching will be converge towards the latest detected collision pair who satisfying the condition. This strategy significantly improved the searching ability for the satisfied collision pairs detection in the limited time interval, and there is no need for clustering, merger, division and any other operations, experiment results show that the efficiency of this algorithm is much better than the similar algorithms.

Collision detection QPSO MOP

Chen Baisong Ye Xuemei AnLi Wang Yuan

The Second Artillery Engineering College, Xi’an, 710025,China The Second Artillery Engineering College, Xi’an, 710025,China College of Science Air Force Engineeri

国际会议

2012 International Conference on Intelligent System Design and Engineering Applications(2012年智能系统设计与工程应用国际会议 ISDEA 2012)

三亚

英文

1028-1031

2012-01-06(万方平台首次上网日期,不代表论文的发表时间)