An application of a backpropagation network for the control of a tracking behavior

Author

Berns, Karsten ; Dillmann, Rüdiger ; Hofstetter, Roland

Author_Institution

Forschungszentrum Inf., Karlsruhe Univ., Germany

fYear

1991

fDate

9-11 Apr 1991

Firstpage

2426

Abstract

The problem of correctly evaluating noisy and incorrect data for the interpretation of ultrasonic sensor signals is addressed. Neural networks, with their inherent characteristics of adaptivity and high fault and noise tolerance, are well suited for such tasks. A backpropagation algorithm is described for the control of the tracking behavior of an autonomous mobile robot. Input data are provided by three ultrasonic sensors mounted on the front of the vehicle. For more flexibility the behavior and learning capability of the tracking algorithm have been improved using different networks

Keywords

acoustic signal processing; learning systems; mobile robots; neural nets; position control; US sensor signal interpretation; autonomous mobile robot; backpropagation network; fault tolerance; learning systems; neural nets; noise tolerance; position control; tracking control; Axles; Backpropagation algorithms; Floors; Mobile robots; Neural networks; Production facilities; Sensor phenomena and characterization; Ultrasonic variables measurement; Vehicles; Wheels;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Automation, 1991. Proceedings., 1991 IEEE International Conference on

Conference_Location

Sacramento, CA

Print_ISBN

0-8186-2163-X

Type

conf

DOI

10.1109/ROBOT.1991.131986

Filename

131986