| Project/Area Number |
22K20519
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| Research Category |
Grant-in-Aid for Research Activity Start-up
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| Allocation Type | Multi-year Fund |
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| Review Section |
0403:Biomedical engineering and related fields
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| Research Institution | National Institute of Advanced Industrial Science and Technology |
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Principal Investigator |
Shen Keli 国立研究開発法人産業技術総合研究所, 情報・人間工学領域, 産総研特別研究員 (80965179)
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| Project Period (FY) |
2022-08-31 – 2024-03-31
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| Project Status |
Completed (Fiscal Year 2023)
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| Budget Amount *help |
¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2023: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2022: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | Dance adpative skills / Motor coordination / Sports biomechanics / Beat detection / Complexity analysis / Deep RL / Computational modeling / Beat-aligned synergies / TD-PCA / Motion complexity / Motor synergy / Motor injury prevention / Latent behavior / Adaptive motor skills / Dance motion Imitation / DRL / Motor Synergy |
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| Outline of Research at the Start |
In this project, advanced model-free DRL methods will be applied to reproduce natural street dance motions in AIST Dance DB, combining some efficient tricks for robustness improvement, and the adaptive dance motor skills will be analyzed.
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| Outline of Final Research Achievements |
We developed a TD-PCA approach to extract beat-aligned motor synergies from street dance datasets, leveraging the first synergy to improve kinematic beat detection and enable accurate beat alignment with music. The enhancement was verified through cross-validation. We simulated deep reinforcement learning models reproducing dance skills, analyzing them kinematically/kinetically, demonstrating our methods' effectiveness for studying AI- generated dance movements.
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| Academic Significance and Societal Importance of the Research Achievements |
我々の計算フレームワークは、複雑なダンスモーションを分析し、ダンスジャンルの運動メカニズムを理解し、動きのダイナミクスと音楽の関係についての洞察を提供し、ダンス研究、パフォーマンス分析、トレーニング、怪我の予防に応用できる。
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