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Learning to avoid moving obstacles optimally for mobile robots using a genetic-fuzzy approach

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Parallel Problem Solving from Nature — PPSN V (PPSN 1998)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1498))

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Abstract

The task in a motion planning problem for a mobile robot is to find an obstacle-free path between a starting and a destination point, which will require the minimum possible time of travel. Although there exists many studies involving classical methods and using fuzzy logic controllers (FLCs), they are either computationally extensive or they do not attempt to find optimal controllers. The proposed genetic-fuzzy approach optimizes the travel time of a robot off-line by simultanously finding an optimal fuzzy rule base and optimal membership function distributions describing various values of condition and action variables of fuzzy rules. A mobile robot can then use this optimal FLC on-line to navigate in the presence of moving obstacles. The results of this study on a number of problems show that the proposed genetic-fuzzy approach can produce efficient rules and membership functions of an FLC for controlling the motion of a robot among moving obstacles.

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Authors and Affiliations

  1. Kanpur Genetic Algorithms Laboratory (KanGAL) Department of Mechanical Engineering, Indian Institute of Technology, Kanpur, Pin 208 016, Kanpur, India

    Kalyanmoy Deb, Dilip Kumar Pratihar & Amitabha Ghosh

Authors
  1. Kalyanmoy Deb
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  2. Dilip Kumar Pratihar
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  3. Amitabha Ghosh
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Editor information

Agoston E. Eiben Thomas Bäck Marc Schoenauer Hans-Paul Schwefel

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© 1998 Springer-Verlag Berlin Heidelberg

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Deb, K., Pratihar, D.K., Ghosh, A. (1998). Learning to avoid moving obstacles optimally for mobile robots using a genetic-fuzzy approach. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, HP. (eds) Parallel Problem Solving from Nature — PPSN V. PPSN 1998. Lecture Notes in Computer Science, vol 1498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0056900

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  • DOI: https://doi.org/10.1007/BFb0056900

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65078-2

  • Online ISBN: 978-3-540-49672-4

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