Autonomous motion of mobile robot using fuzzy-neural networks

Antonio Moran Cardenas; Javier G. Rázuri; David Sundgren; Rahim Rahmani

Autonomous motion of mobile robot using fuzzy-neural networks

Antonio Moran Cardenas
, Javier G. Rázuri
, David Sundgren
, Rahim Rahmani

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

Abstract

This paper analyzes the performance and practical implementation of fuzzy-neural networks for the autonomous motion of mobile robots. The designed fuzzy-neural controller is a refined version of a conventional fuzzy controller, and was trained to optimize a given cost function minimizing positioning error. It was found that the mobile robot with fuzzy-neural controller presents good positioning and tracking performance for different types of desired trajectories. It was verified by computer simulation as well as experimentally using a laboratory-scale car-like robot model. © 2013 IEEE.

Original language	Spanish
Title of host publication	Proceedings - 2013 12th Mexican International Conference on Artificial Intelligence, MICAI 2013
Pages	80-84
Number of pages	5
State	Published - 1 Dec 2013
Externally published	Yes

Cite this

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title = "Autonomous motion of mobile robot using fuzzy-neural networks",

abstract = "This paper analyzes the performance and practical implementation of fuzzy-neural networks for the autonomous motion of mobile robots. The designed fuzzy-neural controller is a refined version of a conventional fuzzy controller, and was trained to optimize a given cost function minimizing positioning error. It was found that the mobile robot with fuzzy-neural controller presents good positioning and tracking performance for different types of desired trajectories. It was verified by computer simulation as well as experimentally using a laboratory-scale car-like robot model. {\textcopyright} 2013 IEEE.",

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AB - This paper analyzes the performance and practical implementation of fuzzy-neural networks for the autonomous motion of mobile robots. The designed fuzzy-neural controller is a refined version of a conventional fuzzy controller, and was trained to optimize a given cost function minimizing positioning error. It was found that the mobile robot with fuzzy-neural controller presents good positioning and tracking performance for different types of desired trajectories. It was verified by computer simulation as well as experimentally using a laboratory-scale car-like robot model. © 2013 IEEE.

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BT - Proceedings - 2013 12th Mexican International Conference on Artificial Intelligence, MICAI 2013

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