Bio-inspired tactile sensors for contour detection using an fem based approach

Abstract

Various mammals, like mice, cats, and rats, have long hairs in the snout region, called mystacial vibrissae. These vibrissae allow the animal to determine a mechanical contact to obstacles and even to get information about the obstacles contour. Thereby, the vibrissa itself can be seen as conductor for mechanical forces and moments. From a mechanical perspective, the only information (the animal relies on) are governed at the support of the hair: the follicle sinus complex (FSC). Here, a lot of different mechanoreceptors detect several mechanical properties to recognize deformation. The vibrissa itself is a hair of conical shape, which is precurved and consists of multiple materials of different properties. In order to use the biological principle for technical sensory system, the reason for this design of the hair needs to be analyzed. Beam models incorporating all these facts (conical shape, hollow, multiple layers, precurvature, visco-elastic support) boundary-value problems, which are hard to handle using numerics. For this, we develop a mechanical model using an FEM-based approach to match all facts from biology and transfer them into a mechanical model for investigations. This work shall serve as a first attempt.