Traditional physics-based contact models have been widely used for describing various contact phenomena such as robotic grasping and assembly. However, difficulties in carrying out contact parameter identification as well as the relatively low measurement accuracy due to complex contact geometry and surface uncertainties are the limiting factors of the physics-based contact modeling methods. In this paper, we present a novel hybrid contact modeling (HCM) method as an endeavor to discover models that can more accurately simulate practical contact scenarios than traditional physics-based contact models. The proposed method is implemented by combining a physics-based contact model and a data-driven error model. This approach is validated by using simulations of a bouncing ball, a flat-shot, and a three-dimensional (3D) peg-in-hole. The results demonstrate the feasibility and consistent performance of the HCM method.

中文翻译：

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基于物理和数据驱动的混合建模方法，可精确模拟复杂的接触现象

传统的基于物理的接触模型已被广泛用于描述各种接触现象，例如机器人的抓握和组装。然而，由于复杂的接触几何形状和表面不确定性，难以进行接触参数识别以及相对较低的测量精度是基于物理的接触建模方法的限制因素。在本文中，我们提出了一种新颖的混合接触建模（HCM）方法，以期发现比传统的基于物理的接触模型能够更准确地模拟实际接触场景的模型。通过结合基于物理的接触模型和数据驱动的误差模型来实现所提出的方法。该方法通过使用弹跳球，平射和三维（3D）钉入孔的仿真得到验证。