Title :
Towards the realization of an artificial tactile system: fine-form discrimination by a tensorial tactile sensor array and neural inversion algorithms
Author :
Caiti, A. ; Canepa, G. ; De Rossi, D. ; Germagnoli, F. ; Magenes, G. ; Parisini, Thomas
Author_Institution :
Dept. of Commun., Comput. & Syst. Sci., Genoa Univ., Italy
fDate :
6/1/1995 12:00:00 AM
Abstract :
This paper describes techniques and methodologies so far developed to investigate object fine-form discrimination by means of artificial tactile sensors. Sensor arrays, selectively sensitive to stress-tensor components and based on piezoelectric polymer technology, have been realized. Sensor output data are used to solve inverse elastic contact problems, by means of neural networks suitably trained to learn regularized inverse maps. Two possible neural network designs are considered: one is based on the multilayer perceptron trained with the standard backpropagation algorithm, and the other is based on the use of radial basis functions. In both cases, reconstruction of object shapes is demonstrated to be effective and robust with both simulated and real data
Keywords :
backpropagation; feedforward neural nets; image reconstruction; inverse problems; multilayer perceptrons; object recognition; piezoelectric transducers; tactile sensors; backpropagation; fine-form discrimination; inverse elastic contact problems; multilayer perceptron; neural inversion; neural networks; object fine-form discrimination; object shape reconstruction; piezoelectric polymer; radial basis function network; tactile sensors; tensorial tactile sensor array; Algorithm design and analysis; Artificial neural networks; Backpropagation algorithms; Multi-layer neural network; Multilayer perceptrons; Neural networks; Polymers; Sensor arrays; Shape; Tactile sensors;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on