A Finger-Shaped Tactile Sensor for Fabric Surfaces Evaluation by 2-Dimensional Active Sliding Touch

Abstract

Sliding tactile perception is a basic function for human beings to determine the mechanical properties of object surfaces and recognize materials. Imitating this process, this paper proposes a novel finger-shaped tactile sensor based on a thin piezoelectric polyvinylidene fluoride (PVDF) film for surface texture measurement. A parallelogram mechanism is designed to ensure that the sensor applies a constant contact force perpendicular to the object surface, and a 2-dimensional movable mechanical structure is utilized to generate the relative motion at a certain speed between the sensor and the object surface. By controlling the 2-dimensional motion of the finger-shaped sensor along the object surface, small height/depth variation of surface texture changes the output charge of PVDF film then surface texture can be measured. In this paper, the finger-shaped tactile sensor is used to evaluate and classify five different kinds of linen. Fast Fourier Transformation (FFT) is utilized to get original attribute data of surface in the frequency domain, and principal component analysis (PCA) is used to compress the attribute data and extract feature information. Finally, low dimensional features are classified by Support Vector Machine (SVM). The experimental results show that this finger-shaped tactile sensor is effective and high accurate for discriminating the five textures.

A Review of Piezoelectric PVDF Film by Electrospinning and Its Applications

“…We also have the piezoelectric shearing strain coefficient in directions 1 and 2 of the film, d 24 , and d 15 . However, their magnitudes are small and can be neglected [ 36 ]. In Figure 2 , the schematic diagram of the PVDF film showing directions is illustrated.…”

Active Tactile Transfer Learning for Object Discrimination in an Unstructured Environment Using Multimodal Robotic Skin

“…23 Previous researchers have used various robotic systems and tactile sensors to passively explore objects and discriminate among them. [24][25][26][27][28][29][30] They used a predefined number of exploratory actions to sense the physical properties of objects with fixed positions and orientation in a known workspace.…”

Re-using prior tactile experience by robotic hands to discriminate in-hand objects via texture properties

“…Hu et al used Support Vector Machine (SVM) to classify five different fabrics by sliding a finger-shaped sensor over the surfaces [4]. A robot actively knocks on the surface of the experimental objects with an accelerometer-equipped device to discriminate stone, mulch, moss, and grass from each other with a lookup table and k-nearest neighbors (K-NN) techniques [5].…”