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Intelligent Robotic Systems Based on Soft Computing—Adaptation, Learning and Evolution

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Book cover Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration with Applications

Part of the book series: NATO ASI Series ((NATO ASI F,volume 162))

Abstract

This paper deals with some intelligent control schemes for robotic systems, such as a hierarchical control based on fuzzy, neural network, genetic algorithm, reinforcement learning control, and group behavior control scheme. We also introduce the network robotic system, which is a new trend in robotic systems. The hierarchical control scheme has three levels: learning level, skill level and adaptation level. The learning level manipulates symbols to reason logically for control strategies. The skill level produces control references along with the control strategies and sensory information on environments. The adaptation level controls robots and machines while adapting to their environments which include uncertainties. For these levels and to connect them, artificial intelligence, neural networks, fuzzy logic, and genetic algorithms are applied to the hierarchical control system while integrating and synthesizing themselves. To be intelligent, the hierarchical control system learns various experiences both in a top-down manner and a bottom-up manner. The reinforcement learning is very important for acquisition of the control signal without any previous information of the system or environment. The group behavior control scheme which is one of the artificial life research areas, and the network robot control scheme are also very important for multiple robotic systems. Thus, these control schemes are effective for intelligent robotics.

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Author information

Authors and Affiliations

  1. Dept. of Micro System Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-01, Japan

    Toshio Fukuda

  2. National Industrial Research Institute of Nagoya, AIST, MITI, 1-1 Hirate-cho, Kita-ku, Nagoya, 462, Japan

    Koji Shimojima

Authors
  1. Toshio Fukuda
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  2. Koji Shimojima
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Editor information

Editors and Affiliations

  1. Faculty of Engineering, Bogaziçi University, Istanbul, TR-80815, Turkey

    Okyay Kaynak

  2. Computer Science Division, University of California at Berkeley, Berkeley, CA, 94720-1776, USA

    Lotfi A. Zadeh

  3. University of Toronto, Ontario, M5S 3G8, Canada

    Burhan Türkşen

  4. Bánki Donát Polytechnic, Népszinház u. 8, Budapest, H-1081, Hungary

    Imre J. Rudas

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© 1998 Springer-Verlag Berlin Heidelberg

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Fukuda, T., Shimojima, K. (1998). Intelligent Robotic Systems Based on Soft Computing—Adaptation, Learning and Evolution. In: Kaynak, O., Zadeh, L.A., Türkşen, B., Rudas, I.J. (eds) Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration with Applications. NATO ASI Series, vol 162. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-58930-0_22

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  • DOI: https://doi.org/10.1007/978-3-642-58930-0_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-63796-4

  • Online ISBN: 978-3-642-58930-0

  • eBook Packages: Springer Book Archive

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