Cloth simulation has wide applications including computer animation, garment design, and robot-assisted dressing. In this work, we present a differentiable cloth simulator whose additional gradient information facilitates cloth-related applications. Our differentiable simulator extends the state-of-the-art cloth simulator based on Projective Dynamics and with dry frictional contact governed by the Signorini-Coulomb law. We derive gradients with contact in this forward simulation framework and speed up the computation with Jacobi iteration inspired by previous differentiable simulation work. To our best knowledge, we present the first differentiable cloth simulator with the Coulomb law of friction. We demonstrate the efficacy of our simulator in various applications, including system identification, manipulation, inverse design, and a real-to-sim task. Many of our applications have not been demonstrated in previous differentiable cloth simulators. The gradient information from our simulator enables efficient gradient-based task solvers from which we observe a substantial speedup over standard gradient-free methods.

中文翻译：

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DiffCloth：干摩擦接触的可微布料模拟

布料模拟具有广泛的应用，包括计算机动画、服装设计和机器人辅助穿衣。在这项工作中，我们提出了一个可微分的布料模拟器，它的附加梯度信息有助于与布料相关的应用程序。我们的可微分模拟器扩展了基于投影动力学和受 Signorini-Coulomb 定律支配的干摩擦接触的最先进的布料模拟器。我们在这个前向模拟框架中通过接触导出梯度，并通过受先前可微模拟工作启发的 Jacobi 迭代加速计算。据我们所知，我们展示了第一个具有库仑摩擦定律的可微布料模拟器。我们展示了我们的模拟器在各种应用中的功效，包括系统识别、操作、逆向设计、和一个真实到模拟的任务。我们的许多应用程序都没有在以前的可微布料模拟器中得到演示。来自我们模拟器的梯度信息支持高效的基于梯度的任务求解器，我们从中观察到比标准的无梯度方法有显着的加速。