We present DiffXPBD, a novel and efficient analytical formulation for the differentiable position-based simulation of compliant constrained dynamics (XPBD). Our proposed method allows computation of gradients of numerous parameters with respect to a goal function simultaneously leveraging a performant simulation model. The method is efficient, thus enabling differentiable simulations of high resolution geometries and degrees of freedom (DoFs). Collisions are naturally included in the framework. Our differentiable model allows a user to easily add additional optimization variables. Every control variable gradient requires the computation of only a few partial derivatives which can be computed using automatic differentiation code. We demonstrate the efficacy of the method with examples such as elastic material parameter estimation, initial value optimization, optimizing for underlying body shape and pose by only observing the clothing, and optimizing a time-varying external force sequence to match sparse keyframe shapes at specific times. Our approach demonstrates excellent efficiency and we demonstrate this on high resolution meshes with optimizations involving over 26 million degrees of freedom. Making an existing solver differentiable requires only a few modifications and the model is compatible with both modern CPU and GPU multi-core hardware.
翻译:我们提出DiffXPBD, 这是一种新型的高效分析配方, 用于兼容受限动态(XPBD)的不同位置模拟。 我们提议的方法允许在同时利用性能模拟模型同时计算目标功能方面多种参数的梯度。 这种方法效率高, 从而能够对高分辨率的几度和自由度进行不同的模拟( DoFs) 。 框架自然包含碰撞。 我们不同的模型允许用户轻松添加额外的优化变量。 每个控制变量都要求只计算少数部分衍生物, 而这些衍生物可以使用自动区分码计算。 我们用弹性物质参数估计、 初始价值优化、 优化基本体形和形状等示例来展示该方法的功效, 仅通过观察外形和优化一个时间变化的外部力序列来匹配特定时间的稀疏关键框架形状( DFs)。 我们的方法展示了极好的效率, 我们在高分辨率中间展示了这一点, 优化了超过2 600万度的自由度的优化度。 使现有的求解器差异只需要很少的修改, 而模型与现代的CPU和GPU多核硬件是兼容的。