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Immune evolutionary algorithms with domain knowledge for simultaneous localization and mapping

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Abstract

Immune evolutionary algorithms with domain knowledge were presented to solve the problem of simultaneous localization and mapping for a mobile robot in unknown environments. Two operators with domain knowledge were designed in algorithms, where the feature of parallel line segments without the problem of data association was used to construct a vaccination operator, and the characters of convex vertices in polygonal obstacle were extended to develop a pulling operator of key point grid. The experimental results of a real mobile robot show that the computational expensiveness of algorithms designed is less than other evolutionary algorithms for simultaneous localization and mapping and the maps obtained are very accurate. Because immune evolutionary algorithms with domain knowledge have some advantages, the convergence rate of designed algorithms is about 44% higher than those of other algorithms.

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Authors and Affiliations

  1. School of Information Science and Engineering, Central South University, 410083, Changsha, China

    Li Mei-yi PhD & Cai Zi-xing

  2. College of Information Engineering, Xiangtan University, 411105, Xiangtan, China

    Li Mei-yi PhD

Authors
  1. Li Mei-yi PhD
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  2. Cai Zi-xing
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Corresponding author

Correspondence to Li Mei-yi PhD.

Additional information

Foundation item: Projects(60234030; 60404021) supported by the National Natural Science Foundation of China

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Li, My., Cai, Zx. Immune evolutionary algorithms with domain knowledge for simultaneous localization and mapping. J Cent. South Univ. Technol. 13, 529–535 (2006). https://doi.org/10.1007/s11771-006-0082-9

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  • DOI: https://doi.org/10.1007/s11771-006-0082-9

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