Elsevier

Fuzzy Sets and Systems

Volume 201, 16 August 2012, Pages 105-121
Fuzzy Sets and Systems

An expert fuzzy cognitive map for reactive navigation of mobile robots

https://doi.org/10.1016/j.fss.2011.12.013Get rights and content

Abstract

A control technique is described for reactive navigation of mobile robots. The problems of large number of rules, and inefficient definition of contributing factors, e.g., robot wheel slippage, are resolved. Causal inference mechanism of the fuzzy cognitive map (FCM) is hired for deriving the required control values from the FCM's motion concepts and their causal interactions. The FCM-based control is proven to be advantageous over rule-based techniques. The developed system is utilized to control a Pioneer platform. The results and comparisons with the related works are given using ActivMedia simulation and a developed FCM simulation tool. An error estimation technique is used to measure the error between the actual and the simulation results.

References (36)

  • C.D. Stylios et al.

    Fuzzy cognitive map architectures for medical decision support systems

    Appl. Soft Comput.

    (2008)
  • W. Stach et al.

    Genetic learning off fuzzy cognitive maps

    Fuzzy Sets Syst.

    (2005)
  • E.I. Papageorgiou et al.

    A new hybrid method using evolutionary algorithms to train fuzzy cognitive maps

    Appl. Soft Comput.

    (2005)
  • J.P. Carvalho et al.

    Qualitative optimization of fuzzy causal rule bases using fuzzy boolean nets

    Fuzzy Sets Syst.

    (2007)
  • E.I. Papageorgiou et al.

    Unsupervised learning techniques for fine-tuning fuzzy cognitive map causal links

    Int. J. Human–Computer Studies

    (2006)
  • E. Kolman et al.

    Extracting symbolic knowledge from recurrent neural networks: a fuzzy logic approach

    Fuzzy Sets Syst.

    (2009)
  • E.I. Papageorgiou et al.

    Unsupervised learning techniques for fine-tuning fuzzy cognitive map causal links

    Int. J. Human–Computer Studies

    (2006)
  • K.M. Krishna et al.

    Perception and remembrance of the environment during real-time navigation of a mobile robot

    Robotics Autonomous Syst.

    (2001)
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