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http://yadda.icm.edu.pl:443/baztech/element/bwmeta1.element.baztech-article-BUJ7-0011-0006

Czasopismo

Journal of Automation Mobile Robotics and Intelligent Systems

Tytuł artykułu

A simple local navigation system inspired by hippocampal function and its autonomous mobile robot implementation

Autorzy Miki, T.  Hayashi, H.  Goto, Y.  Watanabe, M.  Inoue, T. 
Treść / Zawartość
Warianty tytułu
Języki publikacji EN
Abstrakty
EN We propose a practical simple local navigation system inspired by the sequence learning mechanism of the entorhino-hippocampal system. The proposed system memorizes a route as sequences of landmarks in the same way humans do. The proposed local navigation system includes a local route memory unit, landmark extraction unit, and learning-type matching unit. In the local route memory unit, the concept of the sequence learning mechanism of the entorhino-hippocampal system is implemented using a fully connected network, while a sequence of landmarks is embedded in the connection matrix as the local route memory. This system has two operation modes: learning and recall modes. In learning mode, a sequence of landmarks, i.e. a local route, is represented by enhanced loop connections in the connection matrix. In recall mode, the system traces the stored route comparing current landmarks with the stored landmarks using the landmark extraction and learning-type matching units. The system uses a prospective sequence to match the current landmark sequence with the recalled one. Using a prospective sequence in the route comparison allows confirmation of the correct route and deals with any slight change in the current sequence of landmarks. A certainty index is also introduced for judging the validity of the route selection. We describe a basic update mechanism for the stored landmark sequence in the case of a small change in the local route memory. The validity of the proposed system is confirmed using an autonomous mobile robot with the proposed navigation system.
Słowa kluczowe
EN human-like local navigation   sequence learning   entorhino-hippocampal system   autonomous mobile robot  
Wydawca Industrial Research Institute for Automation and Measurements PIAP
Czasopismo Journal of Automation Mobile Robotics and Intelligent Systems
Rocznik 2010
Tom Vol. 4, No. 2
Strony 31--38
Opis fizyczny Bibliogr. 11 poz., rys.
Twórcy
autor Miki, T.
autor Hayashi, H.
autor Goto, Y.
autor Watanabe, M.
autor Inoue, T.
  • Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, 2-4, Hibikino, Wakamatsu-ku, Kitakyushu 808-0196, Japan. Tel/Fax: +81-93-695-6125, miki@brain.kyutech.ac.jp
Bibliografia
[1] Makoto M., "Recent Topics of Car Electronics”, Technical report of IEICE. ICD (in Japanese) , vol. 94, no. 243, 1994, pp. 69-75.
[2] Yamaguchi Y., “A Theory of hippocampal memory based on theta phase precession”, Biological Cybernetics , no. 89, 2003, pp. 1-9.
[3] Hafting T., et al. , “Hippocampus-independent phase precession in entorhinal grid cells”, Nature, no. 453, 2008, pp.1248-1252.
[4] Wagatsuma H.,Yamaguchi Y., “Content-Dependent Adaptive Behavior Generated in the Theta Phase Coding Network”, ICONIP 2007 , Part II, LNCS 4985, 2008, pp. 177-184.
[5] Yoshida M., Hayashi H., "Emergence of sequence sensitivity in a hippocampal CA3-CA1 model”, Neural Networks, vol. 20, 2007, pp. 653-667.
[6] Igarashi J., Hayashi H., Tateno K., "Theta phase coding in a network model of the entorhinal cortex layer II with entorhinal-hippocampal loop connections”, Cognitive Neurodynamics, vol. 1, no. 2, 2007, pp. 169-184.
[7] Natsume K., et al. , “The Possibility of Brain-Inspired Time-Series Memory System using the Recurrent Neuronal Network between Entorhinal Cortex and Hippocampus”, Joint 4 th Int. Conf. on Soft Computing and Intelligent Systems and 9 th Int. Sympo. on advanced Intelligent Systems (SCIS&ISIS2008) , Nagoya, 2008, pp. 1778-1782.
[8] Gionannangeli C., Gaussier P., “Autonomous visionbased navigation: Goal-oriented action planning by transient states prediction, cognitive map building, and sensory-motor learning”, International Conference on Intelligent Robots and Systems (IROS 2008) , 2008, pp. 676-683.
[9] Barrera A., Weitzenfeld A., “Biologically-inspired robot spatial cognition based on rat neurophysiological studies ”, Autonomous Robots , vol. 25, no. 1-2, 2008, pp. 147-169.
[10] Miki T., et al. , “Practical Local Navigation System Based in Entorhino-hippocampal Functions”, Joint 4 th Int. Conf. on Soft Computing and Intelligent Systems and 9 th Int. Sympo. on advanced Intelligent Systems (SCIS& ISIS2008), 2008, Nagoya, pp. 1783-1787.
[11] Ishii K., Miki T., "Mobile robot platforms for artificial and swarm intelligence researches ", Brain-Inspired IT , vol. 3, 2007, pp. 39-42.
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