Intelligent Service Robotics

, Volume 9, Issue 3, pp 217–229 | Cite as

Online underwater optical mapping for trajectories with gaps

  • Armagan ElibolEmail author
  • Hyunjung Shim
  • Seonghun Hong
  • Jinwhan Kim
  • Nuno Gracias
  • Rafael Garcia
Original Research Paper


This paper proposes a vision-only online mosaicing method for underwater surveys. Our method tackles a common problem in low-cost imaging platforms, where complementary navigation sensors produce imprecise or even missing measurements. Under these circumstances, the success of the optical mapping depends on the continuity of the acquired video stream. However, this continuity cannot be always guaranteed due to the motion blurs or lack of texture, common in underwater scenarios. Such temporal gaps hinder the extraction of reliable motion estimates from visual odometry, and compromise the ability to infer the presence of loops for producing an adequate optical map. Unlike traditional underwater mosaicing methods, our proposal can handle camera trajectories with gaps between time-consecutive images. This is achieved by constructing minimum spanning tree which verifies whether the current topology is connected or not. To do so, we embed a trajectory estimate correction step based on graph theory algorithms. The proposed method was tested with several different underwater image sequences and results were presented to illustrate the performance.


Underwater robotics Optical mapping Image mosaicing Environmental monitoring 



Authors would like to thank anonymous reviewers for their detailed and constructive comments. This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the IT Consilience Creative Program (IITP-2015-R0346-15-1008) supervised by the NIPA (National IT Industry Promotion Agency), the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (2013062644) and was a part of the project titled ‘Development of an autonomous ship-hull inspection system’ funded by the Ministry of Oceans and Fisheries, Korea. It was also partially funded through MINECO (grant number CTM2013-46718-R), the European Commission’s Seventh Framework Programme as part of the project Eurofleets2 (grant number FP7-INF-2012-312762), and Generalitat de Catalunya through the ACCIO/TecnioSpring program (TECSPR14-1-0050)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Armagan Elibol
    • 1
    Email author
  • Hyunjung Shim
    • 1
  • Seonghun Hong
    • 2
  • Jinwhan Kim
    • 2
    • 3
  • Nuno Gracias
    • 4
  • Rafael Garcia
    • 4
  1. 1.School of Integrated Technology, Yonsei Institute of Convergence TechnologyYonsei UniversityIncheonRepublic of Korea
  2. 2.Robotics Program, Korea Advanced Institute of Science and Technology (KAIST)DaejeonRepublic of Korea
  3. 3.Department of Mechanical EngineeringKorea Advanced Institute of Science and Technology (KAIST)DaejeonRepublic of Korea
  4. 4.Computer Vision and Robotics Research InstituteUniversity of GironaGironaSpain

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