We present a method for differentiable simulation of soft articulated bodies. Our work enables the integration of differentiable physical dynamics into gradient-based pipelines. We develop a top-down matrix assembly algorithm within Projective Dynamics and derive a generalized dry friction model for soft continuum using a new matrix splitting strategy. We derive a differentiable control framework for soft articulated bodies driven by muscles, joint torques, or pneumatic tubes. The experiments demonstrate that our designs make soft body simulation more stable and realistic compared to other frameworks. Our method accelerates the solution of system identification problems by more than an order of magnitude, and enables efficient gradient-based learning of motion control with soft robots.
翻译:我们提出了一个对软体分解体进行不同模拟的方法。我们的工作使得不同的物理动态能够融入基于梯度的管道。我们在投影动力中开发了自上而下矩阵组合算法,并利用新的矩阵分解战略为软体连续体生成了普遍的干摩擦模型。我们为肌肉、联合火把或气管驱动的软体分解提供了一个不同的控制框架。实验表明,我们的设计使得软体模拟与其他框架相比更加稳定和现实。我们的方法加快了系统识别问题的解决速度,超过了一个数量级,并使得以梯度为基础的软机器人有效学习动作控制。