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图学学报 ›› 2021, Vol. 42 ›› Issue (4): 615-622.DOI: 10.11996/JG.j.2095-302X.2021040615

• 计算机图形学与虚拟现实 • 上一篇    下一篇

基于改进多粒子群的牙齿正畸路径规划

  

  1. 西安科技大学计算机科学与技术学院,陕西 西安 710054
  • 出版日期:2021-08-31 发布日期:2021-08-05
  • 基金资助:
    国家自然科学基金项目(61834005);陕西省自然科学基础研究计划企业联合基金项目(2019JLM-11)

Orthodontic path planning based on improved multi-PSO

  1. College of Computer Science and Technology, Xi’an University of Science and Technology, Xi’an Shaanxi 710054, China
  • Online:2021-08-31 Published:2021-08-05
  • Supported by:
    National Natural Science Foundation of China (61834005); Enterprise Joint Fund Project of Shaanxi Natural Science Basic Research Plan
    (2019JLM-11)

摘要: 牙齿矫治路径规划是虚拟牙齿正畸系统的重要组成部分。针对多目标高维度的路径规划问题,
提出一种改进多粒子群的路径规划方法。首先,采用多粒子群对牙齿路径规划问题进行建模和设计,解决牙齿
正畸维度过高的问题;其次,考虑不同类别牙齿的生理重建难度,基于 Beta 曲线和牙弓深度优化不同粒子群
的惯性参数 w,精细化传统正畸系统的矫治过程;最后,通过修改位置更新上下限缩小路径搜索范围,减少正
畸过程中的碰撞同时优化正畸效果。实验结果表明,该方法效率比单粒子群模型整体提升了约 38%,更符合临
床正畸过程,矫治后更接近理想的正畸效果。

关键词: 牙齿正畸, 路径规划, 多粒子群算法, 变步长

Abstract: Orthodontic path planning is an integral part of a virtual orthodontic system. Aiming at the multi-objective
and high-dimensional path planning problem, an improved multi-particle swarm optimization (PSO) path planning
method was proposed. Firstly, the multi-PSO was utilized to model and design the tooth path planning to solve the
problem of the overly high orthodontic dimension. Secondly, the difficulties in physiological reconstruction of
different types of teeth were considered based on Beta curve and dental arch depth, and the inertia parameter w of
different particle swarms was optimized to refine the orthodontic treatment process of the traditional orthodontic
system. Finally, the upper and lower limits of position updating were modified to narrow the path search range, reduce
the collision during orthodontic process, and optimize the orthodontic effect. The experimental results show that this
method is 38% more efficient than the single particle swarm optimization model, which is more consistent with
clinical orthodontic treatment, and is more likely to achieve the ideal orthodontic effect after treatment.

Key words: orthodontics, path planning, multi-particle swarm optimization, variable step size

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