Docking at pool and sea by using active marker in turbid and day/night environment

Khin Nwe Lwin, Naoki Mukada, Myo Myint, Daiki Yamada, Mamoru Minami, Takayuki Matsuno, Kazuhiro Saitou, Waichiro Godou

Research output: Contribution to journalArticle

Abstract

Nowadays, autonomous underwater vehicle (AUV) is playing an important role in human society in different applications such as inspection of underwater structures (dams, bridges). It has been desired to develop AUVs that can work in a sea with a long period of time for the purpose of retrieving methane hydrate, or rare metal, and so on. To achieve such AUVs, the automatic recharging capability of AUVs under the sea is indispensable and it requires AUVs to dock itself to recharging station autonomously. Therefore, we have developed a stereo-vision-based docking methodology for underwater battery recharging to enable the AUV to continue operations without returning surface vehicle for recharging. Since underwater battery recharging units are supposed to be installed in a deep sea, the deep-sea docking experiments cannot avoid turbidity and low-light environment. In this study, the proposed system with a newly designed active—meaning self-lighting—3D marker has been developed to improve the visibility of the marker from an underwater vehicle, especially in turbid water. Experiments to verify the robustness of the proposed docking approach have been conducted in a simulated pool where the lighting conditions change from day to night. Furthermore, sea docking experiment has also been executed to verify the practicality of the active marker. The experimental results have confirmed the effectiveness of the proposed docking system against turbidity and illumination variation.

Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalArtificial Life and Robotics
DOIs
Publication statusAccepted/In press - Jun 16 2018

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Keywords

  • Active marker
  • Illumination variation
  • Stereo-vision
  • Turbidity
  • Underwater docking
  • Visual servoing

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Artificial Intelligence

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