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International Conference on Neural Information Processing

ICONIP 2016: Neural Information Processing pp 158–167Cite as

Entropy Maximization of Occupancy Grid Map for Selecting Good Registration of SLAM Algorithms

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9947))

Abstract

This paper analyzes entropy of occupancy grid map (OGM) for evaluating registration performance of SLAM (simultaneous localization and mapping) algorithms. So far, there are a number of SLAM algorithms having been proposed, but we do not have general measure to evaluate the registration performance of point clouds obtained by LRF (laser range finder) for SLAM algorithms. This paper analyzes to show that good registration seems corresponding to large overlap of point clouds in OGM as well as large entropy, large uncertainty and low information of OGM. This analysis indicates a method of entropy maximization of OGM for selecting good registration of SLAM algorithms. By means of executing numerical experiments, we show the validity and the effectiveness of the entropy of OGM to evaluate the registration performance.

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Author information

Authors and Affiliations

  1. Kyushu Institute of Technology, Tobata, Kitakyushu, Fukuoka, 804-8550, Japan

    Daishiro Akiyama, Kazuya Matsuo & Shuichi Kurogi

Authors
  1. Daishiro Akiyama
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  2. Kazuya Matsuo
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  3. Shuichi Kurogi
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Corresponding author

Correspondence to Shuichi Kurogi .

Editor information

Editors and Affiliations

  1. The University of Tokyo, Tokyo, Japan

    Akira Hirose

  2. Kobe University, Kobe, Japan

    Seiichi Ozawa

  3. Okinawa Institute of Science and Technology Graduate University, Onna, Japan

    Kenji Doya

  4. Nara Institute of Science and Technology, Ikoma, Japan

    Kazushi Ikeda

  5. Kyungpook National University, Daegu, Korea (Republic of)

    Minho Lee

  6. Chinese Academy of Sciences, Beijing, China

    Derong Liu

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© 2016 Springer International Publishing AG

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Akiyama, D., Matsuo, K., Kurogi, S. (2016). Entropy Maximization of Occupancy Grid Map for Selecting Good Registration of SLAM Algorithms. In: Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., Liu, D. (eds) Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science(), vol 9947. Springer, Cham. https://doi.org/10.1007/978-3-319-46687-3_17

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  • DOI: https://doi.org/10.1007/978-3-319-46687-3_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46686-6

  • Online ISBN: 978-3-319-46687-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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