Recognition of Contact State of Four Layers Arrayed Type Tactile Sensor by using Neural Network

Abstract

Imitating human finger tip, an arrayed type tactile sensor comprising four layers is under development. In this report, a recognizing method of force and its direction is proposed by using two stage neural networks, and its validity is investigated by simulation. The procedure of simulation is as follows: first, the stress distribution of this sensor sheet applied force is simulated by FEM (finite element method). The obtained stress data are assigned to each assumed stress sensing element of the array. Second, all data of these elements are processed by the first stage neural network, and force direction is calculated. Third, using this direction data and maximal stress data of 4 layers are processed by the second stage neural network.