Underwater 3D structures as semantic landmarks in SONAR mapping

Thomas Guerneve, Kartic Subr, Yvan Petillot

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)
46 Downloads (Pure)

Abstract

SONAR mapping of underwater environments leads to dense point-clouds. These maps have large memory footprints, are inherently noisy and consist of raw data with no semantic information. This paper presents an approach to underwater semantic mapping where known man-made structures that appear in multibeam SONAR data are automatically recognised. From a set of SONAR images acquired by an Autonomous Underwater Vehicle (AUV) and a catalogue of 'a-priori' 3D CAD models of structures that may potentially be found in the data, our algorithm proceeds in two phases. First we recognise objects using an efficient, rotation-invariant 2D descriptor combined with a histogram matching method. Then, we determine pose using a 6 degree-of-freedom registration of the 3D object to the local scene using a fast 2D correlation, refined with an iterative closest point (ICP)-based method. Once the structures located and identified, we build a semantic representation of the world based on the initial CAD models, resulting in a lightweight yet accurate world model. We demonstrate the applicability of our method on field data acquired by an AUV in Loch Linnhe, Scotland. Our method proves to be suitable for online semantic mapping of a partially man-made underwater environment such as a typical oil field.

Original languageEnglish
Title of host publication2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
PublisherIEEE
Pages614-619
Number of pages6
ISBN (Electronic)9781538626825
DOIs
Publication statusPublished - 14 Dec 2017
Event30th IEEE/RSJ International Conference on Intelligent Robots and Systems 2017 - Vancouver, Canada
Duration: 24 Sep 201728 Sep 2017

Publication series

NameIEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherIEEE
ISSN (Electronic)2153-0866

Conference

Conference30th IEEE/RSJ International Conference on Intelligent Robots and Systems 2017
Abbreviated titleIROS 2017
CountryCanada
CityVancouver
Period24/09/1728/09/17

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Guerneve, T., Subr, K., & Petillot, Y. (2017). Underwater 3D structures as semantic landmarks in SONAR mapping. In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 614-619). (IEEE/RSJ International Conference on Intelligent Robots and Systems). IEEE. https://doi.org/10.1109/IROS.2017.8202215