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Modular Neural Network and Classical Reinforcement Learning for Autonomous Robot Navigation: Inhibiting Undesirable Behaviors
Electronics and Information Systems (ELIS) department, Ghent university, Belgium.
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0001-5163-2997
State University of Maringá, Brazil.
2006 (English)In: International Joint Conference on Neural Networks, 2006. IJCNN '06, Piscataway, N.J.: IEEE Press, 2006, p. 498-505Conference paper, Published paper (Refereed)
Abstract [en]

Classical reinforcement learning mechanisms and a modular neural network are unified for conceiving an intelligent autonomous system for mobile robot navigation. The conception aims at inhibiting two common navigation deficiencies: generation of unsuitable cyclic trajectories and ineffectiveness in risky configurations. Distinct design apparatuses are considered for tackling these navigation difficulties, for instance: 1) neuron parameter for memorizing neuron activities (also functioning as a learning factor), 2) reinforcement learning mechanisms for adjusting neuron parameters (not only synapse weights), and 3) a inner-triggered reinforcement. Simulation results show that the proposed system circumvents difficulties caused by specific environment configurations, improving the relation between collisions and captures.

Place, publisher, year, edition, pages
Piscataway, N.J.: IEEE Press, 2006. p. 498-505
Series
IEEE International Joint Conference on Neural Networks (IJCNN), ISSN 1098-7576
Keywords [en]
mobile robots, neurocontrollers, path planning
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-2112DOI: 10.1109/IJCNN.2006.246723ISI: 000245125900073Scopus ID: 2-s2.0-40649114292Local ID: 2082/2507ISBN: 0-7803-9490-9 OAI: oai:DiVA.org:hh-2112DiVA, id: diva2:239330
Conference
International Joint Conference on Neural Networks, 2006. IJCNN '06, Vancouver
Note

©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Available from: 2008-11-07 Created: 2008-11-07 Last updated: 2018-03-23Bibliographically approved

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Baerveldt, Albert-JanRögnvaldsson, Thorsteinn

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
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Output format
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