Crowd formation via hierarchical planning

Xingce Wang, Na Liu, Shaolong Liu, Zhongke Wu, Mingquan Zhou, Jiale He, Peng Cheng, C. Miao, N. Magnenat-Thalmann
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引用次数: 6

Abstract

Team formation with realistic crowd simulation behaviour is a challenge in computer graphics, multi-agent control and social simulation. In this paper, we propose a framework of crowd formation via hierarchical planning, which includes cooperative-task, coordinated-behaviour and action-control planning. In cooperative-task planning, we improve the grid potential field to achieve global path planning for a team. In coordinated-behaviour planning, we propose a time-space table to arrange behaviour scheduling for a movement. In action-control planning, we combine the gaze-movement angle model and fuzzy logic control to achieve agent action. Our method has several advantages: (1) The hierarchical architecture is guaranteed to match the human decision process from high to low intelligence. (2) The agent plans his behaviour only with the local information of his neighbour; the global intelligence of the group emerges from these local interactions. (3) The time-space table fully utilizes the three-dimensional information. Our method is verified using crowds of various densities, from sparse to dense crowds, using quantitative performance measures. The approach is independent of the simulation model and can be extended to other crowd simulation tasks.
通过分层规划形成人群
具有真实人群模拟行为的团队形成是计算机图形学、多智能体控制和社会仿真领域的一个挑战。本文提出了一种基于分层规划的群体形成框架,该框架包括合作任务、协调行为和行动控制规划。在协同任务规划中,改进网格势场,实现团队全局路径规划。在协调行为规划中,我们提出了一个时空表来安排运动的行为调度。在动作控制规划中,我们将注视-运动角度模型与模糊逻辑控制相结合来实现智能体的动作。该方法具有以下优点:(1)层次结构保证了从高智能到低智能的人类决策过程的匹配。(2) agent仅根据邻居的局部信息来规划自己的行为;这个群体的全球智慧来自于这些地方性的互动。(3)时空表充分利用了三维信息。我们的方法使用不同密度的人群进行验证,从稀疏人群到密集人群,使用定量性能度量。该方法独立于仿真模型,可以推广到其他人群仿真任务中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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