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Interaction between Humans and Puppets: Humanoid Robot Design using Empirical mode decomposition and Deep learning

Research Project

Project/Area Number 20K23352
Research Category

Grant-in-Aid for Research Activity Start-up

Allocation TypeMulti-year Fund
Review Section 1002:Human informatics, applied informatics and related fields
Research InstitutionTokyo University of Technology

Principal Investigator

DONG Ran  東京工科大学, コンピュータサイエンス学部, 助教 (80879891)

Project Period (FY) 2020-09-11 – 2022-03-31
Project Status Completed (Fiscal Year 2021)
Budget Amount *help
¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Fiscal Year 2021: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2020: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Keywords経験的モード分解 / ロボット / インタラクションデザイン / 序破急 / 伝統芸能 / 人形浄瑠璃 / モーションデザイン / ヒューマンロボットインタラクション / 深層学習 / モーション解析 / ロボット工学 / 人形浄瑠璃文楽
Outline of Research at the Start

ユネスコ無形文化遺産「人形浄瑠璃文楽」は,3人の人形遣いが一体の人形を操作し,義太夫と三味線使いが義太夫節と呼ばれる音楽により物語を語り,三業一身で舞台を構成する.本研究では,「文楽カラクリ×文楽人形感情表現の匠×序破急メカニズム」の視点から,文楽の動きを周波数領域空間において分解し,抽出された特徴量をAIに学習させる.序破急という非決定論的日本伝統芸能メカニズムを,人工情動知能アシスタントと連動できるコミュニケーションロボットのインタラクションに応用する.

Outline of Final Research Achievements

In Ningyo Joruri (puppet theater), the puppeteers use an unparalleled method to manipulate one puppet, and their movements have been praised as the most beautiful emotional expressions in the world. This is made possible by the use of a traditional performing technique in which the puppeteers perform the story to synchronize a Japanese musical form called Gidayu-bushi (Gidayu and Shamisen). In this study, we proposed a method for analyzing emotional expressions in the frequency domain from the viewpoint of Jo-Ha-Kyu that are considered important in this technique using the Hilbert-Huang transform. We also developed a robot motion generation framework that adopts the extracted features as training data for deep learning. Furthermore, we were able to apply the method developed in this study for interdisciplinary fusion and contribute to nonlinear problems in different fields.

Academic Significance and Societal Importance of the Research Achievements

本研究では,初めて「音×動き×序破急メカニズム」の視点から,伝統芸能の動きを周波数領域空間で解析を行った.序破急という非決定論的日本伝統芸能メカニズムを用いることにより,人工情動知能アシスタントと連動できるコミュニケーションAIのインタラクション手法の確立に寄与できる.本研究が実施した伝統芸能からのロボット創造は,現在世界に注目されている日本文化や日本的感性のテクノロジーを世界へ発信できる学術研究として期待できると同時に,これまでのAIアシスタントの普及を妨げてきた,対人感覚の欠如を改善し,利用の広がりを飛躍的に進める可能性がある.

Report

(3 results)
  • 2021 Annual Research Report   Final Research Report ( PDF )
  • 2020 Research-status Report
  • Research Products

    (14 results)

All 2022 2021 2020

All Journal Article (6 results) (of which Peer Reviewed: 6 results,  Open Access: 3 results) Presentation (8 results) (of which Int'l Joint Research: 1 results)

  • [Journal Article] Photonic Crystal Frequency Demultiplexer Design for Electromagnetic Wave using FDTD and MEMD2022

    • Author(s)
      Dong Ran, Shigeta Daisuke, Fujita Yoshihisa, Ikuno Soichiro
    • Journal Title

      Journal of Advanced Simulation in Science and Engineering

      Volume: 9 Issue: 1 Pages: 65-77

    • DOI

      10.15748/jasse.9.65

    • NAID

      130008158426

    • ISSN
      2188-5303
    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Nonlinear frequency analysis of COVID-19 spread in Tokyo using empirical mode decomposition2022

    • Author(s)
      Dong Ran, Ni Shaowen, Ikuno Soichiro
    • Journal Title

      Scientific Reports

      Volume: 12 Issue: 1 Pages: 1-12

    • DOI

      10.1038/s41598-022-06095-w

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Electromagnetic Penetration and Reflection Analysis in Fractal Structures using Three-dimensional Empirical Mode Decomposition2022

    • Author(s)
      Dong Ran, Fujita Yoshihisa, Nakamura Hiroaki, Ikuno Soichiro
    • Journal Title

      IEEE Transactions on Magnetics

      Volume: in press Issue: 9 Pages: 1-4

    • DOI

      10.1109/tmag.2022.3161997

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed
  • [Journal Article] A deep learning framework for realistic robot motion generation2021

    • Author(s)
      Dong Ran, Chang Qiong, Ikuno Soichiro
    • Journal Title

      Neural Computing and Applications

      Volume: in press Issue: 32 Pages: 1-14

    • DOI

      10.1007/s00521-021-06192-3

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Photonic Rendering for Hair Cuticles using High Accuracy NS-FDTD method2021

    • Author(s)
      Hou Zhuo, Cai Dongsheng, Dong Ran
    • Journal Title

      ACM SIGGRAPH 2021 Talks

      Volume: SIGGRAPH '21 Pages: 1-2

    • DOI

      10.1145/3450623.3464678

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Motion Capture Data Analysis in the Instantaneous Frequency-Domain Using Hilbert-Huang Transform2020

    • Author(s)
      Dong Ran、Cai Dongsheng、Ikuno Soichiro
    • Journal Title

      Sensors

      Volume: 20 Issue: 22 Pages: 6534-6534

    • DOI

      10.3390/s20226534

    • Related Report
      2020 Research-status Report
    • Peer Reviewed / Open Access
  • [Presentation] Parallelization Efficiency of k-skip Mister R for Large Scale Linear System obtained from Electromagnetic Analysis2022

    • Author(s)
      Takayasu Morishita, Ran Dong, Kuniyoshi Abe, Yoshihisa Fujita, Soichiro Ikuno
    • Organizer
      Compumag 2021
    • Related Report
      2021 Annual Research Report
    • Int'l Joint Research
  • [Presentation] MEMDを用いたフォトニック結晶内の電磁波周波数解析2022

    • Author(s)
      重田 大祐、董 然、生野 壮一郎
    • Organizer
      情報処理学会第84回全国大会
    • Related Report
      2021 Annual Research Report
  • [Presentation] k段飛ばしMrR法の数値特性と並列化効率の数値的検証2022

    • Author(s)
      森下 貴康、董 然、阿部 邦美、生野 壮一郎
    • Organizer
      情報処理学会第84回全国大会
    • Related Report
      2021 Annual Research Report
  • [Presentation] 経験的モード分解を用いた東京都 COVID-19 新規感染者のトレンド解析2021

    • Author(s)
      董 然、生野 壮一郎
    • Organizer
      日本応用数理学会2021年度年会
    • Related Report
      2021 Annual Research Report
  • [Presentation] フラクタル構造内電磁波伝播現象に対する三次元経験的モード分解を用いた空間周波数解析2021

    • Author(s)
      董 然、藤田 宜久、中村 浩章、生野 壮一郎
    • Organizer
      第30回MAGDAコンファレンス (MAGDA2021)
    • Related Report
      2021 Annual Research Report
  • [Presentation] 多変量経験的モード分解を用いた電磁波瞬時周波数解析と可視化2021

    • Author(s)
      董然,生野壮一郎
    • Organizer
      2020年度非線形問題の解法と可視化に関する研究会
    • Related Report
      2020 Research-status Report
  • [Presentation] 残差履歴に応じて適応的に収束改善をするk段飛ばしMrR法の検討と評価2020

    • Author(s)
      森下貴康,董然,生野壮一郎
    • Organizer
      第29回MAGDAコンファレンス (MAGDA2020)
    • Related Report
      2020 Research-status Report
  • [Presentation] 時間発展電磁界解析に対する経験的モード分解の適用可能性の検討2020

    • Author(s)
      董然,重田大祐,生野壮一郎
    • Organizer
      第29回MAGDAコンファレンス (MAGDA2020)
    • Related Report
      2020 Research-status Report

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Published: 2020-09-29   Modified: 2023-01-30  

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