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AI Technology for Underwater Robots pp 125–135Cite as

Challenges in Underwater Visual Navigation and SLAM

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Part of the book series: Intelligent Systems, Control and Automation: Science and Engineering ((ISCA,volume 96))

Abstract

This paper addresses visual navigation of autonomous underwater vehicles (AUVs) with and without a given map, where the latter is called Simultaneous Localization and Mapping (SLAM). We summarize the challenges and opportunities in underwater environments that make visual navigation different from land navigation and also briefly survey the current state-of-the-art in this area. Then as a position paper we argue why many of these challenges could be met by a proper modeling of uncertainties in the SLAM representation. This would in particular allow the SLAM algorithm to thoroughly handle the ambiguity between “I see the same feature again.”, “I see a different but similar looking feature.” and “The environment has changed and the feature moved.”.

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Notes

  1. 1.

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Author information

Authors and Affiliations

  1. GEOMAR Helmholtz Centre for Ocean Research Kiel, Wischhofstr. 1-3, 24148, Kiel, Germany

    Kevin Köser

  2. University of Bremen, Enrique-Schmidt-Str. 5, 28359, Bremen, Germany

    Udo Frese

Authors
  1. Kevin Köser
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  2. Udo Frese
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Corresponding authors

Correspondence to Kevin Köser or Udo Frese .

Editor information

Editors and Affiliations

  1. Robotics Innovation Center, DFKI GmbH and Robotic Group, University of Bremen, Bremen, Germany

    Frank Kirchner

  2. Robotics Innovation Center, DFKI GmbH, Bremen, Germany

    Sirko Straube

  3. Robotics Innovation Center, DFKI GmbH, Bremen, Germany

    Daniel Kühn

  4. Robotics Innovation Center, DFKI GmbH and Robotic Group, University of Bremen, Bremen, Germany

    Nina Hoyer

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Köser, K., Frese, U. (2020). Challenges in Underwater Visual Navigation and SLAM. In: Kirchner, F., Straube, S., Kühn, D., Hoyer, N. (eds) AI Technology for Underwater Robots. Intelligent Systems, Control and Automation: Science and Engineering, vol 96. Springer, Cham. https://doi.org/10.1007/978-3-030-30683-0_11

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