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RatSLAM: Using Models of Rodent Hippocampus for Robot Navigation and Beyond

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Robotics Research

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 114))

Abstract

We describe recent biologically-inspired mapping research incorporating brain-based multi-sensor fusion and calibration processes and a new multi-scale, homogeneous mapping framework. We also review the interdisciplinary approach to the development of the RatSLAM robot mapping and navigation system over the past decade and discuss the insights gained from combining pragmatic modelling of biological processes with attempts to close the loop back to biology. Our aim is to encourage the pursuit of truly interdisciplinary approaches to robotics research by providing successful case studies.

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Acknowledgments

This work was supported by an Australian Research Council Discovery Project DP120102775 and Microsoft Research Faculty Fellowship to MM, and an ARC & NHMRC Thinking Systems grant TS0669699 to GW.

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Authors and Affiliations

  1. School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane, Australia

    Michael Milford, Adam Jacobson, Zetao Chen & Gordon Wyeth

Authors
  1. Michael Milford
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  2. Adam Jacobson
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  3. Zetao Chen
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  4. Gordon Wyeth
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Corresponding author

Correspondence to Michael Milford .

Editor information

Editors and Affiliations

  1. Creative Informatics, The University of Tokyo, Tokyo, Japan

    Masayuki Inaba

  2. School of Electrical Engineering and Com, Queensland Univ of Technology, Brisbane, Queensland, Australia

    Peter Corke

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Milford, M., Jacobson, A., Chen, Z., Wyeth, G. (2016). RatSLAM: Using Models of Rodent Hippocampus for Robot Navigation and Beyond. In: Inaba, M., Corke, P. (eds) Robotics Research. Springer Tracts in Advanced Robotics, vol 114. Springer, Cham. https://doi.org/10.1007/978-3-319-28872-7_27

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  • DOI: https://doi.org/10.1007/978-3-319-28872-7_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28870-3

  • Online ISBN: 978-3-319-28872-7

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