| Project/Area Number |
18K18129
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 61050:Intelligent robotics-related
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| Research Institution | Osaka University (2019-2021)
The University of Tokyo (2018) |
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Principal Investigator |
Koyama Keisuke 大阪大学, 基礎工学研究科, 助教 (20817415)
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| Project Period (FY) |
2018-04-01 – 2022-03-31
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| Project Status |
Completed (Fiscal Year 2021)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2021: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2020: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2019: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 近接覚センサ / インハンドマニピュレーション / 回転操作 / 高速ロボット / 機械学習 |
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| Outline of Final Research Achievements |
In order to efficiently carry out automatic product assembly operations, in-hand manipulation is needed to change the posture of picked-up part. In this study, (i) the development of a wiring-saving, compact and high-precision proximity sensor and (ii) a manipulation strategy using high-speed sensor feedback were proposed to realise high-speed rotational manipulation of an object grasped by a robot hand. In the experiments, a delicate insertion task of a lid of remote controller was achieved. And, a rotational manipulation of jelly drink was also achieved.
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| Academic Significance and Societal Importance of the Research Achievements |
今後，工業製品などの組み立てラインでは，作業者の確保が困難となり，一人当たりの作業負担が増加する恐れがある．負担軽減のためには，ロボットによる一部作業の自動化が効果的であるが，ピックアップした様々な形状の部品を目的の姿勢に持ち替えることは未だに難しい．本研究は高速なセンサフィードバックを用いることで，部品を掴んだ状態で確実な姿勢変更を実現する．将来的にヒトの手作業の一部の自動化に貢献する．
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