论文标题
运动服装的计算设计
Computational Design of Kinesthetic Garments
论文作者
论文摘要
动力学服装通过量身定制的增强材料分布提供了身体姿势和运动的物理反馈。他们有选择地加强服装对特定动作的反应的能力使它们吸引了康复，运动，机器人技术和许多其他应用领域的吸引力。但是，找到分发给定数量的加固材料以最大程度地加强对指定动议的响应的设计是一个具有挑战性的问题。在这项工作中，我们提出了一种优化驱动的方法，用于用于动力学服装的增强模式的自动设计。我们的主要贡献是将这项设计任务作为体内拓扑优化问题。我们的方法使设计人员可以探索与各种增强覆盖范围相对应的连续设计范围。我们的模型捕获了布与身体之间的紧密接触和升空分离。我们展示了有关不同身体部位和运动的各种增强设计问题的方法。最佳设计在能量密度方面的性能提高了两到三倍。在比较用户研究中，一组制造的设计始终被评为比基线更具阻力
Kinesthetic garments provide physical feedback on body posture and motion through tailored distributions of reinforced material. Their ability to selectively stiffen a garment's response to specific motions makes them appealing for rehabilitation, sports, robotics, and many other application fields. However, finding designs that distribute a given amount of reinforcement material to maximally stiffen the response to specified motions is a challenging problem. In this work, we propose an optimization-driven approach for automated design of reinforcement patterns for kinesthetic garments. Our main contribution is to cast this design task as an on-body topology optimization problem. Our method allows designers to explore a continuous range of designs corresponding to various amounts of reinforcement coverage. Our model captures both tight contact and lift-off separation between cloth and body. We demonstrate our method on a variety of reinforcement design problems for different body sites and motions. Optimal designs lead to a two- to threefold improvement in performance in terms of energy density. A set of manufactured designs were consistently rated as providing more resistance than baselines in a comparative user study
