Abstract
The development of techniques for a navigation of multiple mobile robots is abroad topic, covering a large spectrum of different technologies and applications. Neural networks and fuzzy logic control techniques can improve real-time control performance for a mobile robot due to their high robustness and error-tolerance ability. This paper proposes a neuro-fuzzy (NF) controller, which integrates the transparency of the fuzzy logic with the learning capability of neural networks is developed for multiple mobile robots navigation in an unknown environment. The neuro-fuzzy controller developed in this research consists of a neural network pre-processor followed by a fuzzy logic controller. The former is structured using multi-layer perceptron (MLP) or local model network (LMN). Practical results reflect the soundness of the proposed scheme.
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Awad, H.A., Koutb, M.A., Al-zorkany, M.A. (2005). Multiple Mobile Robots Navigation in a Cluttered Environment using Neuro-Fuzzy Controller. In: Abraham, A., Dote, Y., Furuhashi, T., Köppen, M., Ohuchi, A., Ohsawa, Y. (eds) Soft Computing as Transdisciplinary Science and Technology. Advances in Soft Computing, vol 29. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32391-0_93
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DOI: https://doi.org/10.1007/3-540-32391-0_93
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