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Design and Control of Intelligent Robotic Systems pp 209–226Cite as

Evolutionary Terrain-Based Navigation of Autonomous Mobile Robots

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 177))

Abstract

Optimal motion planning is critical for the successful operation of an autonomous mobile robot. Evolutionary approaches are able to provide optimal paths to problems normally intractable for traditional search methods. However, most proposed methods lack the ability to operate in a dynamic environment in real-time, and few address the impact of varying terrain conditions on the optimal path. This evolutionary navigation approach employs a novel chromosome encoding scheme that provides both path and trajectory planning. The terrain conditions are modeled using fuzzy linguistic variables to allow for the imprecision and uncertainty of the terrain data. The method is extensible and robust, allowing the robot navigate in real-time and to adapt to dynamic conditions in the environment.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Coastal Carolina University, Conway, South Carolina, 29528, USA

    Terrence P. Fries

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  1. Terrence P. Fries
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Editor information

Editors and Affiliations

  1. University of Technology, Sydney, Australia

    Dikai Liu

  2. Texas A&M University, College Station, TX, USA

    Lingfeng Wang

  3. National University of Singapore, Singapore

    Kay Chen Tan

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© 2009 Springer-Verlag Berlin Heidelberg

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Fries, T.P. (2009). Evolutionary Terrain-Based Navigation of Autonomous Mobile Robots. In: Liu, D., Wang, L., Tan, K.C. (eds) Design and Control of Intelligent Robotic Systems. Studies in Computational Intelligence, vol 177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89933-4_11

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  • DOI: https://doi.org/10.1007/978-3-540-89933-4_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89932-7

  • Online ISBN: 978-3-540-89933-4

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