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Improved Biogeography-Based Optimization Algorithm for Mobile Robot Path Planning

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Proceedings of 2017 Chinese Intelligent Systems Conference (CISC 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 460))

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Abstract

In view of biogeography-based optimization algorithm has the disadvantages of application limitations and slow convergence speed when in solving the problem of mobile robot path planning. This paper proposes an improved biogeography-based optimization algorithm, which is used to solve the global path planning of mobile robot in static environment. In the proposed algorithm, the navigation point model is selected as the working area model of mobile robot, and the nonlinear migration model and mutation mechanism with the elite retention mechanism are introduced to the biogeography-based optimization algorithm to improve its performance. Simulation proves the feasibility and the effectiveness of the proposed path planning algorithm.

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Author information

Authors and Affiliations

  1. Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China

    Jianfei Yang & Lin Li

Authors
  1. Jianfei Yang
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  2. Lin Li
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Corresponding author

Correspondence to Lin Li .

Editor information

Editors and Affiliations

  1. Beihang University , Beijing, China

    Yingmin Jia

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Junping Du

  3. University of Science and Technology Beijing, Beijing, China

    Weicun Zhang

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© 2018 Springer Nature Singapore Pte Ltd.

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Yang, J., Li, L. (2018). Improved Biogeography-Based Optimization Algorithm for Mobile Robot Path Planning. In: Jia, Y., Du, J., Zhang, W. (eds) Proceedings of 2017 Chinese Intelligent Systems Conference. CISC 2017. Lecture Notes in Electrical Engineering, vol 460. Springer, Singapore. https://doi.org/10.1007/978-981-10-6499-9_22

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  • DOI: https://doi.org/10.1007/978-981-10-6499-9_22

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6498-2

  • Online ISBN: 978-981-10-6499-9

  • eBook Packages: EngineeringEngineering (R0)

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