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Selective image registration for efficient visual SLAM on planar surface structures in underwater environment

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Abstract

This paper presents a computationally efficient approach that can be applied to visual simultaneous localization and mapping (SLAM) for the autonomous inspection of underwater structures using monocular vision. A selective image registration scheme consisting of key-frame selection and key-pair selection is proposed to effectively use visual features that may not be evenly distributed on the surface of underwater structures. The computational cost of the visual SLAM algorithm can be substantially reduced using only potentially effective images and image pairs by applying the proposed image registration scheme. The performance of the proposed approach is demonstrated on two different experimental datasets obtained using autonomous underwater vehicles.

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Acknowledgements

This research was a part of the project titled ‘Development of an autonomous ship-hull inspection system’, funded by the Ministry of Oceans and Fisheries, Korea.

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Authors and Affiliations

  1. Robotics Program, KAIST, Daejeon, Korea

    Seonghun Hong & Jinwhan Kim

  2. Department of Mechanical Engineering, KAIST, Daejeon, Korea

    Jinwhan Kim

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  1. Seonghun Hong
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  2. Jinwhan Kim
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Correspondence to Jinwhan Kim.

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Hong, S., Kim, J. Selective image registration for efficient visual SLAM on planar surface structures in underwater environment. Auton Robot 43, 1665–1679 (2019). https://doi.org/10.1007/s10514-018-09824-1

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  • DOI: https://doi.org/10.1007/s10514-018-09824-1

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