DocumentCode :
2692398
Title :
Application of adaptive neural network to localization of objects using pressure array transducer
Author :
Leung, Anderson ; Payandeh, Shahram
Author_Institution :
Sch. of Eng. Sci., Simon Fraser Univ., Burnaby, BC, Canada
Volume :
3
fYear :
1994
fDate :
2-5 Oct 1994
Firstpage :
2114
Abstract :
Pattern recognition and object localization, using various sensors such as vision and tactile sensors, are two important areas in the application of robotic systems. This paper demonstrates the feasibility of using some relatively inexpensive pressure sensors and a neural network to achieve object localization and pattern recognition. The sensors used are force sensing resistors (FSRs), more specifically, a 16×16 array of FSRs. Because of the nonlinearities associated with a FSR, three approaches for gathering output from the sensor array are used. The neural network used consists of two 2-layer counterpropagation networks (CPNs). In addition to recognizing pre-trained patterns, this paper also demonstrates that the conventional CPN configuration can be modified to learn new patterns even when its training period is completed. Both simulated and experimental results of this paper suggest that the neural network can provide an alternative approach for object localization using tactile arrays
Keywords :
adaptive systems; feedforward neural nets; image processing; object recognition; robot vision; tactile sensors; adaptive neural network; force sensing resistors; image processing; object localisation; pattern recognition; pressure array transducer; tactile arrays; tactile sensors; two-layer counterpropagation networks; Adaptive systems; Force sensors; Neural networks; Pattern recognition; Resistors; Robot sensing systems; Robot vision systems; Sensor arrays; Sensor systems and applications; Tactile sensors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-2129-4
Type :
conf
DOI :
10.1109/ICSMC.1994.400176
Filename :
400176
Link To Document :
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