| Project/Area Number |
21H01287
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Review Section |
Basic Section 20020:Robotics and intelligent system-related
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| Research Institution | Japan Advanced Institute of Science and Technology |
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Principal Investigator |
Ho Anhvan 北陸先端科学技術大学院大学, 先端科学技術研究科, 准教授 (60757508)
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| Co-Investigator(Kenkyū-buntansha) |
渋谷 恒司 龍谷大学, 先端理工学部, 教授 (20287973)
高村 禅 北陸先端科学技術大学院大学, 先端科学技術研究科, 教授 (20290877)
都 英次郎 北陸先端科学技術大学院大学, 先端科学技術研究科, 准教授 (70443231)
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| Project Period (FY) |
2021-04-01 – 2024-03-31
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| Project Status |
Completed (Fiscal Year 2023)
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| Budget Amount *help |
¥17,290,000 (Direct Cost: ¥13,300,000、Indirect Cost: ¥3,990,000)
Fiscal Year 2023: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2022: ¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2021: ¥10,270,000 (Direct Cost: ¥7,900,000、Indirect Cost: ¥2,370,000)
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| Keywords | 形態変動 / 形態による補正 / ソフトセンシング / ソフトな形態の変形 / ダメージ / Morphology / Soft sensing / Compensation / MR fluids / Topological change / Whiskered sensor / Wrinkled sensor / Corona discharge / Micro pattern / ソフトロボット / Soft Robot / 形態補佐 / 有限要素法 |
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| Outline of Research at the Start |
This research is to clarify the underlying physics of the morphological compensation, which reveals the correlation between the embedded sensors’ output and critical changes in morphology of the soft body (such as damaged, trimmed). From this framework, we aim to propose a methodology of compensation strategy based on morphological change of the soft body for maintaining the soft robot’s performance (sensing, actuation, interaction) upon critical changes. We also plan to apply such strategy in actual robotic mechanisms.
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| Outline of Annual Research Achievements |
1) Building a SOFA program for online modeling of the critical change of the soft body, such as trimming, cutting. It has been applied to the whiskered sensor for evaluation of sensing response while there is topological change. 2) Constructing a preliminary Reinforcement learning plugin for the SOFA environment, from which the morphological optimization can be elaborated.
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| Research Progress Status |
令和5年度が最終年度であるため、記入しない。
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| Strategy for Future Research Activity |
令和5年度が最終年度であるため、記入しない。
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