Similar texture recognition based on FBG finger-shaped tactile sensors

Abstract Current tactile perception of surfaces with identical materials and similar textures relies on additional equipment to maintain a constant velocity for sensors, which constrains the practical application of tactile sensing devices in daily life. A finger-shaped tactile sensor leveraging the high sensitivity of Fiber Bragg Grating (FBG) in tactile sensing is proposed in this paper. It is able to distinguish different textures based on the variation amplitude of the central wavelength in FBG. The deployment position of FBG was optimized using COMSOL Multiphysics finite element simulation software, analyzing the influence of texture depth on the output signal, and an experimental platform was constructed to collect 11 texture signals from three categories. The experimental results show that different texture features are reflected by the amplitude of FBG signal, using the SVM classification model to classify four kinds of regular ridge spacing textures and three kinds of fabric texture samples collected at random velocity, and the recognition accuracy is 99.17% and 98.89%, respectively. This method, compared to other similar texture tactile experiments, has better classification ability and advantages in adapting to different texture perception speeds, providing valuable reference for intelligent perception of robot fingertip touch.