| Project/Area Number |
16H02428
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Naval and maritime engineering
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| Research Institution | The University of Tokyo |
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Principal Investigator |
Maki Toshihiro 東京大学, 生産技術研究所, 准教授 (50505451)
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| Research Collaborator |
Sato Yoshiki
Matsuda Takumi
Sakamaki Takashi
Ito Takaaki
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥45,110,000 (Direct Cost: ¥34,700,000、Indirect Cost: ¥10,410,000)
Fiscal Year 2018: ¥9,490,000 (Direct Cost: ¥7,300,000、Indirect Cost: ¥2,190,000)
Fiscal Year 2017: ¥13,390,000 (Direct Cost: ¥10,300,000、Indirect Cost: ¥3,090,000)
Fiscal Year 2016: ¥22,230,000 (Direct Cost: ¥17,100,000、Indirect Cost: ¥5,130,000)
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| Keywords | AUV / 自律型海中ロボット / 海底ステーション / 海底地震津波観測網 / 海底地震津波観測 / ナビゲーション / 海中探査 |
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| Outline of Final Research Achievements |
This research developed a technical base to realize long term, wide area, and dense observation of seafloor, by developing a method to deploy an autonomous underwater vehicle (AUV) based on seafloor sensor network. The newly developed wide area navigation method enabled an AUV to transit to another seafloor station beyond the range of acoustic positioning devices. Docking method was also developed, which enables an AUV to dock to a seafloor station to charge battery and send data. Furthermore, it is also verified that the method can be applied to multi vehicle navigation, through sea experiments using the three AUVs, Tri-Dog 1, Tri-TON, and Tri-TON 2.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究により、AUVを船舶や人間の介在無しで長期間かつ広範囲に展開する手法が確立された。海底ステーション単体へのドッキングや音響ナビゲーションに関する研究事例は存在するが、複数の海底ステーションからなる海底センサネットワーク全域をターゲットとし、かつドッキングまで含んだシステム提案はこれまでほとんど存在しない。本手法は現在常識となっている船舶ベースの海洋調査を根本から変える可能性を秘めており、サイエンス分野のほか、資源開発、漁業、施設管理、環境モニタリング、捜索救助など幅広い応用が期待される。
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