Robust visual odometry in underwater environment

Jun Zhang, Viorela Ila, Laurent Kneip

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    17 Citations (Scopus)

    Abstract

    The accurate estimation of pose and velocity of an autonomous underwater vehicle (AUV) is critical to ensure the repeatability and validity of scientific data that is captured using sensors onboard the AUV. A low-cost and effective way is by using stereo camera sensors to perform visual odometry (VO). However, this is a difficult problem in underwater due to poor imaging condition and inconsistent motion caused by water flow. This paper proposes a robust and effective stereo underwater VO system that can overcome aforementioned difficulties and accurately localize the AUV. Experimental results demonstrate that the proposed pipeline outperforms existing VO systems in underwater environment, as well as obtains a comparative performance on the KITTI benchmark dataset.

    Original languageEnglish
    Title of host publication2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781538616543
    DOIs
    Publication statusPublished - 4 Dec 2018
    Event2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018 - Kobe, Japan
    Duration: 28 May 201831 May 2018

    Publication series

    Name2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018

    Conference

    Conference2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018
    Country/TerritoryJapan
    CityKobe
    Period28/05/1831/05/18

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