计算机工程与应用 ›› 2019, Vol. 55 ›› Issue (1): 154-160.DOI: 10.3778/j.issn.1002-8331.1806-0411

• 模式识别与人工智能 • 上一篇    下一篇

融合QPSO算法的多精度布料仿真建模方法

靳雁霞,王  贺,程思岳,张晋瑞,程琦甫   

  1. 中北大学,太原 030051
  • 出版日期:2019-01-01 发布日期:2019-01-07

Adaptive Cloth Simulation Based on QPSO Algorithm

JIN Yanxia, WANG He, CHENG Siyue, ZHANG Jinrui, CHENG Qifu   

  1. North University of China, Taiyuan 030051, China
  • Online:2019-01-01 Published:2019-01-07

摘要: 在布料建模领域,如何快速模拟布料形变之后的褶皱细节是研究的热点。通过使用多精度布料建模方法,在布料的不同形变区域使用不同精度的网格,可以有效平衡建模的精度和速度,已有的工作主要是在布料形变过程中,动态计算出布料质点邻域的曲率,依据人为设定的阈值,划分出布料的多精度区域,而在大部分场景中,布料的变形模式没有规律,固定不变的阈值可能会影响布料的仿真效果。针对该问题,首先将基于量子行为的粒子群算法引入建模过程,通过粒子群算法对布料表面的搜索,提高了布料弯曲部位的搜索效率,优化了多精度布料的建模速度和精度,其次针对布料仿真运动过程进行研究,参考布料受空气阻力的数学模型,以及粒子动力学中的数值积分方法,优化布料运动的仿真计算方法。实验证明,与现有布料多精度方法相比,该方法能较快检测到布料褶皱区域并判断是否需要细化,且能较好地表现出布料仿真过程中空气阻力对布料造成的形变。

关键词: 布料仿真, QPSO算法, 多精度布料, 虚拟现实技术

Abstract: In the field of cloth modeling, how to quickly simulate the fold details after deformation is a hot topic of research. By using the method of multi-level fabric modeling, the accuracy and speed of modeling can be effectively balanced with different precision in different deformation areas. The existing work is mainly to dynamically calculate the curvature of the particle areas in the process of deformation and divide the multi-level areas according to the artificially set threshold. However, in most scenes, the deformation mode of the cloth is irregular, and the fixed threshold may affect the simulation effect of the cloth. By using the particle swarm algorithm to search the fabric surface, the searching efficiency of the curving part is improved, the modeling speed and precision are also optimized. Consider the mathematical model of air resistance, the numerical integration method of particle dynamics is used to optimize the calculation method of fabric simulation. Results show that compared with the existing cloth simulation method, this method can quickly detect the fabric curving area and determine whether need to be refined, and can show the air resistance on cloth simulation process.

Key words: cloth simulation, QPSO algorithm, multi-level cloth, virtual reality