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Combining GPU-generated linear trajectory segments to create collision-free paths for real-time ambient crowds

机译:结合GPU生成的线性轨迹线段以创建实时环境人群的无碰撞路径

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摘要

Ambient crowds are used widely in today's computer games and movies. In this study, a real-time steering-free ambient crowd navigation technique is presented, which combines linear and constant-speed trajectory segments end-to-end to provide collision-free paths to simulated agents. This method seeks spatio-temporal space to find such trajectory segments by utilizing specialized features of the GPU. Each segment is required to come one after another, and at the transition points, the segments are restricted to have direction and/or speed changes within certain limits. Experiments revealed that the proposed multi-segment path technique can create denser crowds by simulating more agents (up to 53% on average and up to 44% as a maximum) than the single-segment path method existing in the literature. It is also shown in the experiments that the presented technique requires less time per navigated agent per time step (up to 98%) than a popular velocity-based microscopic method. (C) 2018 Elsevier Inc. All rights reserved.
机译:环境人群在当今的计算机游戏和电影中被广泛使用。在这项研究中,提出了一种实时无转向环境人群导航技术,该技术端到端结合了线性和恒速轨迹段,从而为模拟主体提供了无碰撞路径。该方法通过利用GPU的特殊功能来寻找时空空间以找到这样的轨迹段。要求每个段都相继到达,并且在过渡点处,这些段被限制为具有在特定限制内的方向和/或速度变化。实验表明,与文献中存在的单段路径方法相比,拟议的多段路径技术可以通过模拟更多的代理(平均最多53%,最多最多44%)来创建更密集的人群。在实验中还显示,与流行的基于速度的微观方法相比,所提出的技术每个时间步长每个导航代理所需的时间更少(最多98%)。 (C)2018 Elsevier Inc.保留所有权利。

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