Neural-network steering control of an automated guided vehicle

Shigeyuki Funabiki, Michio Mino

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

A new steering control for an AGV based on the neural network using the backpropagation method was proposed. The good steering control results by the fuzzy control were adopted for the teaching signal of the neural network. First, the effect of the number of learning and the learning errors on the steering control results were discussed by computer simulation using the AGV model. Furthermore, the ability of generalization in the turning radius and the traveling speed also were investigated. It became clear that the AGV can travel along a designated route provided the neural network learns both the right and the left turning at the maximum turning radius. Then it was proved by an experiment using the AGV constructed for the test that the proposed steering control method is very effective.

Original languageEnglish
Pages (from-to)135-143
Number of pages9
JournalElectrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi)
Volume114
Issue number7
Publication statusPublished - Dec 1 1994

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Neural networks
Fuzzy control
Backpropagation
Teaching
Computer simulation
Experiments

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Neural-network steering control of an automated guided vehicle. / Funabiki, Shigeyuki; Mino, Michio.

In: Electrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi), Vol. 114, No. 7, 01.12.1994, p. 135-143.

Research output: Contribution to journalArticle

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