Diverse Motions and Character Shapes for Simulated Skills

Diverse Motions and Character Shapes for Simulated Skills
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多种动作和角色形状,模拟技能

DOI:
10.1109/tvcg.2014.2314658
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发表时间:
2014
影响因子:
5.2
通讯作者:
M. V. D. Panne
M. V. D. Panne
中科院分区:
计算机科学1区
文献类型:
--
作者:
Shailen Agrawal;Shuo Shen;M. V. D. Panne

文献摘要

被引文献

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我们提出了一个优化框架,为诸如跳跃、翻转和行走等任务的基于物理的角色产生各种各样的运动。这与产生单个最优运动的更常见的优化用法形成对比。解决方案可以优化,以实现运动多样性或多样性的比例模拟人物。作为输入,该方法采用一个字符模型、一个用于成功运动实例的参数化控制器、一组应保留的约束和一个成对距离度量。离线优化然后产生一组高度多样化的运动风格,或者,适合不同角色形状的运动。我们展示了各种基于2D和3D物理的运动的结果,表明该方法可以产生令人信服的模拟技能的新变化。
We present an optimization framework that produces a diverse range of motions for physics-based characters for tasks such as jumps, flips, and walks. This stands in contrast to the more common use of optimization to produce a single optimal motion. The solutions can be optimized to achieve motion diversity or diversity in the proportions of the simulated characters. As input, the method takes a character model, a parameterized controller for a successful motion instance, a set of constraints that should be preserved, and a pairwise distance metric. An offline optimization then produces a highly diverse set of motion styles or, alternatively, motions that are adapted to a diverse range of character shapes. We demonstrate results for a variety of 2D and 3D physics-based motions, showing that the approach can generate compelling new variations of simulated skills.