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 proceedingConference contributionpeer-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.

Original languageEnglish
Title of host publicationProceedings - 2013 12th Mexican International Conference on Artificial Intelligence, MICAI 2013
Pages80-84
Number of pages5
DOIs
StatePublished - 2013
EventProceedings - 2013 12th Mexican International Conference on Artificial Intelligence, MICAI 2013 - Mexico City, Mexico
Duration: 24 Nov 201330 Nov 2013

Publication series

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

Conference

ConferenceProceedings - 2013 12th Mexican International Conference on Artificial Intelligence, MICAI 2013
Country/TerritoryMexico
CityMexico City
Period24/11/1330/11/13

Keywords

  • Dynamic Back Propagation
  • Fuzzy-Neural Control
  • Mobile Robot
  • Neural Network Training

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