半扫描Kaudd逐次过松弛(HSKSOR)方法中基于谐波电位的Agent导航

F. A. Musli, A. Saudi
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引用次数: 0

摘要

智能体在虚拟环境中的导航问题已被许多研究者广泛研究。提出了一种基于半扫描(HS)迭代和Kaudd逐次过松弛(KSOR)的组合方法来解决模拟虚拟环境中的智能体导航问题。所提出的半扫描Kaudd逐次过松弛(HSKSOR)方法用于获得称为调和函数的拉普拉斯方程的解,然后将其应用于搜索算法中,为智能体从指定的起始点导航到目标点生成无碰撞路径。结果表明,与现有的迭代方法相比,HSKSOR的计算速度更快,计算时间更短。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Agent Navigation via Harmonic Potentials with Half-Sweep Kaudd Successive Over Relaxation (HSKSOR) Method
Navigation problems of an agent in a virtual environment had been widely studied by many researchers. This paper presents a combination method based on Half-Sweep (HS) iteration and Kaudd Successive Over Relaxation (KSOR) to solve agent navigation problem in a simulated virtual environment. The proposed method, namely Half-Sweep Kaudd Successive Over Relaxation (HSKSOR), is used to obtain the solutions of Laplace’s equation known as harmonic functions which then be applied in the search algorithm to generate collision-free path for an agent to navigate from a specified start point to a target point. The results found that the HSKSOR offers faster computational approach with less computational time compared to the existing iterative methods.
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