论文标题
在选举中的指尖摩擦的两尺度FEM-BAM方法
A two-scale FEM-BAM approach for fingerpad friction under electroadhesion
论文作者
论文摘要
基于选举的触觉背后的复杂物理学表现出了巨大的建模挑战，因为不仅具有多个非线性层的指尖结构，而且微观量表的粗糙度也起着决定性的作用。为了研究触觉感知，潜在的模型还应提供在相关机械感受器部位提取机械刺激的可能性。在本文中，我们提出了一种两尺度的方法，该方法涉及宏观尺度上的有限元模型（FEM）和一个简单的轴承区域模型（BAM），该模型（BAM）解释了乳头脊上的粗糙度。这两个单独的尺度夫妇都使用等效气隙的概念以迭代方式。我们表明，拟议模型预测的选举诱导的摩擦和接触区域的变化与最近的实验研究符合定性一致。在一个简单的示例中，我们证明了该模型可以通过神经动力学模型轻松扩展，以研究选举嵌入的触觉感知。
The complex physics behind electroadhesion-based tactile displays poses an enormous modeling challenge since not only the fingerpad structure with multiple nonlinear layers, but also the roughness at the microscopic scale play a decisive role. To investigate tactile perception, a potential model should also offer the possibility to extract mechanical stimuli at the sites of the relevant mechanoreceptors. In this paper, we present a two-scale approach that involves a finite element model (FEM) at the macroscopic scale and a simple bearing area model (BAM) that accounts for the measured roughness on the papillary ridges. Both separate scales couple in an iterative way using the concept of an equivalent air gap. We show that the electroadhesion-induced changes in friction and contact area predicted by the proposed model are in qualitative agreement with recent experimental studies. In a simple example, we demonstrate that the model can readily be extended by a neural dynamics model to investigate the tactile perception of electroadhesion.
