Smart drone audition: A search and rescue drone system that listens and communicates

智能无人机试听：能够聆听和通信的搜救无人机系统

• 批准号: 22KF0141
• 负责人: 中臺 一博
• 金额: $ 1.41万
• 依托单位: Tokyo Institute of Technology
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for JSPS Fellows
• 财政年份: 2023
• 资助国家: 日本
• 起止时间: 2023-03-08 至 2025-03-31
• 项目状态: 未结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-22KF0141/
• 关键词: ドローン聴覚; 音響信号処理; 深層学習

Dr. Benjamin Yen has integrated some of his research at the University of Auckland into related drone audition projects at the Tokyo Institute of Technology. Specifically, he incorporated techniques from his work in sound source enhancement to improve sound source tracking using multiple drones. This has yielded a conference paper submission to the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems. The paper is currently under review.We have submitted a journal article for drone audition to the IEEE/ACM Transactions on Audio Speech and Language Processing. Specifically, we proposed a noise covariance matrix estimation method that can be applied to sound source enhancement algorithms for drone audition. While this research is developed during Dr. Benjamin Yen's time at the University of Auckland, it is entirely within the research scope of the JSPS postdoctoral fellowship proposal and is a topic that will be further developed during this fellowship. The paper is currently under major revision.We have carried out a major outdoor experiment to collect the necessary data to perform performance evaluation for various drone audition algorithms. This includes accurate audio recordings of drone noise and a moving target sound source. In addition, accurate GPS data of the target sound source's movement is also recorded. These measurements will be helpful in evaluating sound source tracking performance from the algorithms proposed.We have planned a range of research topics related to the research theme to be researched by ourselves and new B4/masters students.

Benjamin Yen博士已经将他在奥克兰大学的一些研究整合到东京工业大学的相关无人机试听项目中。具体来说，他将自己在声源增强方面的工作技术结合起来，使用多架无人机来改进声源跟踪。这产生了一个会议论文提交给2023年IEEE/RSJ智能机器人和系统国际会议。该论文目前正在审查中。我们已经向IEEE/ACM Transactions on Audio Speech and Language Processing提交了一篇关于无人机试听的期刊文章。具体而言，我们提出了一种噪声协方差矩阵估计方法，可应用于声源增强算法的无人机试听。虽然这项研究是在Benjamin Yen博士在奥克兰大学期间开发的，但它完全在JSPS博士后奖学金提案的研究范围内，并且是在此奖学金期间将进一步发展的主题。本文目前正在进行重大修改。我们已经进行了一次重大的户外实验，以收集必要的数据，对各种无人机试听算法进行性能评估。这包括对无人机噪音和移动目标声源的准确录音。此外，还记录了目标声源运动的精确GPS数据。这些测量将有助于评估声源跟踪性能的算法提出。我们已经计划了一系列的研究课题相关的研究主题将由我们自己和新的B4/硕士生进行研究。

项目成果

Rotor noise power spectral density informed sound source enhancement and localisation for unmanned aerial vehicles

无人机转子噪声功率谱密度通知声源增强和定位

• 发表时间: 2022
• 作者: Sebastian Bahamonde;Sebastian Bahamonde;Sebastian Bahamonde;Benjamin Yen and Yusuke Hioka
• 通讯作者: Benjamin Yen and Yusuke Hioka