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An automatic parking system using an optimized image-based fuzzy controller by genetic algorithms

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Abstract

An automatic parking system of a car-like mobile robot is an important issue in commercial applications. An image-based fuzzy controller for an automatic parking system of a car-like mobile robot was developed in previous work, where the membership functions were tuned by experimentally. The aim of this paper is to optimize the parameters of the membership functions, which were performed in previous work, using a genetic algorithm against the complicated tuning of the controller. The details of GA implementation, such as the design parameters and choice of fitness function, are described. Simulation results illustrate the effectiveness of the developed schemes.

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Authors and Affiliations

  1. Department of Intelligent Mechanical Systems, Division of Industrial Innovation Sciences, Graduate School of Natural Science and Technology, Okayama University, 3-1-1 Tsushima-naka, Kita-ku, Okayama, 700-8530, Japan

    Yin Yin Aye, Keigo Watanabe, Shoichi Maeyama & Isaku Nagai

Authors
  1. Yin Yin Aye
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  2. Keigo Watanabe
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  3. Shoichi Maeyama
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  4. Isaku Nagai
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Corresponding author

Correspondence to Yin Yin Aye.

Additional information

This work was presented in part at the 21st International Symposium on Artificial Life and Robotics, Beppu, Oita, January 20–22, 2016.

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Aye, Y.Y., Watanabe, K., Maeyama, S. et al. An automatic parking system using an optimized image-based fuzzy controller by genetic algorithms. Artif Life Robotics 22, 139–144 (2017). https://doi.org/10.1007/s10015-016-0326-1

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  • DOI: https://doi.org/10.1007/s10015-016-0326-1

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