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スマートドローン聴覚:聴覚コミュニケーション機能を有する災害救助ドローンシステム

研究課題

研究課題/領域番号 22KF0141
補助金の研究課題番号 22F22769 (2022)
研究種目

特別研究員奨励費

配分区分基金 (2023)
補助金 (2022)
応募区分外国
審査区分 小区分20020:ロボティクスおよび知能機械システム関連
研究機関東京工業大学

研究代表者

中臺 一博  東京工業大学, 工学院, 教授 (70436715)

研究分担者 YEN BENJAMIN  東京工業大学, 工学院, 外国人特別研究員
研究期間 (年度) 2023-03-08 – 2025-03-31
研究課題ステータス 交付 (2023年度)
配分額 *注記
2,200千円 (直接経費: 2,200千円)
2024年度: 600千円 (直接経費: 600千円)
2023年度: 1,100千円 (直接経費: 1,100千円)
2022年度: 500千円 (直接経費: 500千円)
キーワードドローン聴覚 / 音響信号処理 / 深層学習
研究開始時の研究の概要

This research aims to develop a drone intended for search and rescue. Equipped with "ears", the drone "listens" to an audible target and, in turn, promotes effective communication with them. "Listening" includes recognising, locating and recording the target sound "clearly" (i.e. free of noise from the drone's rotors and surroundings) under harsh, noisy environments, typical in search and rescue.

研究実績の概要

This research year, we developed and implemented a real-life sound source tracking system using drones equipped with microphone arrays. Previously, such systems were only demonstrated in simulations. Due to strict drone flight regulations in Japan, we designed an indoor system with miniature drones and custom microphones to navigate these restrictions. We also enhanced the system with a drone navigation setup that continuously adjusts drone positions to maximize sound tracking accuracy. Further modifications to the sound tracking algorithms were necessary to address real-life constraints and challenges.
Additionally, we have advanced drone noise reduction techniques for improved sound source tracking, showing promising results in simulations. Real-life testing, however, unveiled unforeseen challenges not anticipated in the simulation phase, necessitating further simulations and experimental tests to refine our approach and meet these new requirements.
These developments contribute to our smart drone audition research theme, utilizing multiple drones with autonomous navigation to enhance sound source tracking performance. This system not only aims to improve the accuracy of locating sound sources but also enhances the quality of recorded audio by minimizing drone noise interference. These advancements are expected to significantly benefit applications where audio clarity and quality are critical.

現在までの達成度 (区分)
現在までの達成度 (区分)

2: おおむね順調に進展している

理由

Given that it is our understanding that until now, no one has developed a multi-drone system that is used to perform sound source tracking, it is under the expectation that developing such a system will be challenging and will take a considerable amount of time. Several components in the system required custom hardware, and many trial-and-errors were needed to overcome the practical challenges and issues that arose, of which many have very limited information or solutions available.
Due to the time spent on developing this system, there has been limited development in the algorithm aspect of the research, which has impacted the research output in terms of publications.
However, most of the challenges have finally been overcome, and we now have a working real-life system to perform the designated task. We now have a development platform to prototype and test any new algorithmic developments of sound source tracking, and even other drone audition-related algorithms. We expect the number of research outputs to increase from this point onwards.

今後の研究の推進方策

We intend to continue the smart drone audition research in the following ways:
1) We intend to make use of the newly developed indoor system to prototype new sound source tracking algorithms, and more importantly drone noise reduction techniques to improve the performance of multi-drone sound source tracking. Such algorithms include namely i) drone noise reduction techniques, ii) sound source recognition (for multiple sound source scenarios, where identifying and ensuring the correct sound source is tracked is important) and if possible, iii) implemented obstacle avoidance and environmental mapping functionalities to improve the drone’s self-reliant capabilities.
2) Using the experience and software developed from the indoor system, we intend to expand and develop a full-sized outdoor multi-drone system for practical sound source tracking. This not only includes development of relevant algorithms, but also design choices in the hardware of the full-sized system. We also intent to integrate the multi-drone sound source tracking system with other forms of robots to allow cooperative sound source tracking to be carried out.

報告書

(2件)
  • 2023 実施状況報告書
  • 2022 実績報告書
  • 研究成果

    (13件)

すべて 2024 2023 2022 その他

すべて 国際共同研究 (1件) 雑誌論文 (1件) (うち国際共著 1件、 査読あり 1件、 オープンアクセス 1件) 学会発表 (10件) (うち国際学会 5件、 招待講演 2件) 備考 (1件)

  • [国際共同研究] The University of Auckland/Victoria University of Wellington(ニュージーランド)

    • 関連する報告書
      2023 実施状況報告書
  • [雑誌論文] Rotor Noise-Aware Noise Covariance Matrix Estimation for Unmanned Aerial Vehicle Audition2023

    • 著者名/発表者名
      Yen Benjamin、Li Yameizhen、Hioka Yusuke
    • 雑誌名

      IEEE/ACM Transactions on Audio, Speech, and Language Processing

      巻: 31 ページ: 2491-2506

    • DOI

      10.1109/taslp.2023.3288410

    • 関連する報告書
      2023 実施状況報告書
    • 査読あり / オープンアクセス / 国際共著
  • [学会発表] Real Time Sound Source Localization Using Von-Mises ResNet2024

    • 著者名/発表者名
      Mert Bozkurtlar, Benjamin Yen, Katsutoshi Itoyama, Kazuhiro Nakadai
    • 学会等名
      IEEE/SICE International Symposium on System Integration (SII)
    • 関連する報告書
      2023 実施状況報告書
    • 国際学会
  • [学会発表] Robot Audition 5.0 and Beyond, Southern University of Science and Technology2023

    • 著者名/発表者名
      Kazuhiro Nakadai
    • 学会等名
      Southern University of Science and Technology (SUSTech)
    • 関連する報告書
      2023 実施状況報告書
    • 招待講演
  • [学会発表] Performance evaluation of sound source localisation and tracking methods using multiple drones2023

    • 著者名/発表者名
      Benjamin Yen, Taiki Yamada, Katsutoshi Itoyama, Kazuhiro Nakadai
    • 学会等名
      Internoise 2023
    • 関連する報告書
      2023 実施状況報告書
    • 国際学会
  • [学会発表] Development of a continuous classroom signal-to-noise ratio measurement system2023

    • 著者名/発表者名
      Benjamin Yen, C. T. Justine Hui, Esther Bergin, Eleesa Jensen, Suzanne C. Purdy, William Keith, Yusuke Hioka, James Whitlock, George Dodd
    • 学会等名
      Internoise 2023
    • 関連する報告書
      2023 実施状況報告書
    • 国際学会
  • [学会発表] Rotor Noise-Informed Sound Source Tracking with Multiple Drones Using Microphone Arrays2023

    • 著者名/発表者名
      Benjamin Yen, Taiki Yamada, Katsutoshi Itoyama, Kazuhiro Nakadai
    • 学会等名
      IEEE/RSJ International Conference on Intellignet Robots and Systems (IROS 2023) LBR
    • 関連する報告書
      2023 実施状況報告書
    • 国際学会
  • [学会発表] PyHARK: A Python Package for Robot Audition Based on HARK2023

    • 著者名/発表者名
      Kazuhiro Nakadai, Masayuki Takigahira, Katsutoshi Itoyama
    • 学会等名
      IEEE/RSJ International Conference on Intellignet Robots and Systems (IROS 2023) LBR
    • 関連する報告書
      2023 実施状況報告書
    • 国際学会
  • [学会発表] Robot Audition 5.0 and Beyond2023

    • 著者名/発表者名
      Kazuhiro Nakadai
    • 学会等名
      POSTECH
    • 関連する報告書
      2023 実施状況報告書
    • 招待講演
  • [学会発表] ドローンのローターノイズによる地表材質推定手法の検討2023

    • 著者名/発表者名
      矢野 翼, 糸山 克寿, 西田 健次, 中臺 一博
    • 学会等名
      SICE SI 2023
    • 関連する報告書
      2023 実施状況報告書
  • [学会発表] Few-shot detection on Drone Captured Scenarios2023

    • 著者名/発表者名
      Md Ragib Amin Nihal, Benjamin Yen, Katsutoshi Itoyama, Kazuhiro Nakadai
    • 学会等名
      日本ロボット学会学術講演会
    • 関連する報告書
      2023 実施状況報告書
  • [学会発表] Rotor noise power spectral density informed sound source enhancement and localisation for unmanned aerial vehicles2022

    • 著者名/発表者名
      Benjamin Yen and Yusuke Hioka
    • 学会等名
      第61回人工知能学会 AI チャレンジ研究会
    • 関連する報告書
      2022 実績報告書
  • [備考] 東京工業大学中臺研究室~災害救助~

    • URL

      https://www.ra.sc.e.titech.ac.jp/research/rescue/

    • 関連する報告書
      2023 実施状況報告書

URL: 

公開日: 2022-11-17   更新日: 2024-12-25  

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