Intelligent automated guided vehicle with reverse strategy: a comparison study

Authors:
Shigeru Kato;Kok Wai Wong
Affiliations:
Murdoch University, Murdoch, Western Australia and Yuge National College of Maritime Technology, Ochigun, Japan;Murdoch University, Murdoch, Western Australia
Venue:
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Year:
2008

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Abstract

This paper describes the intelligent automated guided vehicle (AGV) control system. The AGV used in this paper is a virtual vehicle simulated using computer. The purpose of the control system is to control the simulated AGV for moving along the given path towards the goal. Some obstacles can be placed on or near the path to increase the difficulties of the control system. The intelligent AGV should trace the path by avoiding these obstacles. In some situations, it is inevitable to avoid the obstacles without reversing. In this paper, we look into the use of fuzzy automaton for controlling the AGV. In order to better avoid the obstacles, reverse strategy has been implemented to the fuzzy automaton controller. Another alternative to incorporate the human expertise and observations is to use a hybrid intelligent controller using fuzzy and case base reasoning to implement the reverse strategy. This paper presents the comparison results for the three intelligent AGV systems used to avoid obstacles.