| Project/Area Number |
17K14694
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Measurement engineering
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| Research Institution | Kyushu Institute of Technology |
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Principal Investigator |
LU HUIMIN 九州工業大学, 大学院工学研究院, 助教 (40742466)
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| Project Period (FY) |
2017-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2017: ¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
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| Keywords | 人工知能 / 海洋工学 / スペクトルカメラ / 画像分割 / 海中工学 / 画像処理 / ロボティックス / 深海採鉱機 / 画像計測 / ロボット |
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| Outline of Final Research Achievements |
There is a large amount of cobalt rich crust on the deep sea floor, and many cobalt rich crusts are distributed on the slope of the seamount. When using submarine mineral coring, complex topography such as steep cliffs and chimney groups are often present, and sediments are likely to fly up. The existing measurement system can not be used in the ultra-high turbidity environment of deep-sea hydrothermal deposits, and the resolution of the imaging systems is not good. Therefore, this project has developed an imaging system for deep sea mining machine using advanced artificial intelligence. During the research period, we developed a mineral identification method using ultra-high turbidity underwater video visualization technology and spectrum measurement platform.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究では、人工知能が適用できる多様な水中光学応用課題への取り組みと、それらを通じた横断的に抽出した情報学課題への取り組みとを往復することで、水中画質改善とスペクトルによる目標認識へのアプローチを展開しました。実施期間内に学術論文20編以上を発表し、市民講座4回を行いました。以上のことから、海洋立国を支える機械電子情報分野の人材の育成と基盤的な技術力の強化に貢献しています。
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