CCRI: Medium: Collaborative Research: mu-Net: Infrastructure to Advance Mobile Underwater Wireless Networking Research

CCRI：媒介：合作研究：mu-Net：推进移动水下无线网络研究的基础设施

• 批准号: 2016582
• 负责人: Klementyna Kasraie
• 金额: $ 62万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2016582&HistoricalAwards=false
• 关键词: CCRI; Medium; Collaborative; Research; mu

The aquatic environments, including the oceans, lakes, and rivers, are the basis for life. An exciting direction is to use a group of robots to support science and discovery in aquatic environments. Currently, there are no shared infrastructures available to the nation’s institutions to investigate how a group of robots can coordinate with each other in the underwater environment. This project develops a low-cost and flexible infrastructure, referred to as mu-Net, to support both laboratory tests and field experiments for users from institutions around the nation. The mu-Net infrastructure, a collaborative project between the University of Alabama and Georgia Institute of Technology, advances underwater technologies by lowering the research participation threshold. It also supports the training of the next generation workforce to manage and preserve marine resources.The mu-Net infrastructure uses a service-oriented, non-hierarchical software architecture to facilitate integrated sensing, communications, and navigation. It consists of 1) re-configurable, open-source software suites for simulations and emulations, 2) miniaturized aquatic robots for laboratory tests, 3) commercial-off-the-shelf autonomous surface vehicles and autonomous underwater vehicles for lake tests, and 4) user services to support shared usage. The mu-Net framework merges the functionality of network-centric and autonomy-centric structures to enhance flexible networking capability for collaborative robots. The intellectual merit resides in that the infrastructure enables research in multiple directions. Examples of the enabled research include cooperative and coordinated marine robotics, underwater mobile communication networks, joint networking and navigation of marine robots, and underwater Internet of Things.The mu-Net infrastructure aims to break down the underwater networking-robotics disciplinary barrier and promote close interactions between the two fields. It significantly lowers the participation barrier for researchers in a wide range of areas like marine biology, food sources, and economic development. It has the potential to inspire more exploration of the earth’s vast water bodies for scientific and commercial activities. The project uses a spectrum of community engagement activities, such as annual workshops, conference special sessions, summer training school, and deployment camps, to expand user communities. In addition, enabled by the cost-effective assets and fueled by the participation of users via social media, mu-Net attracts widespread adoption for different education and research purposes, ranging from ocean-literacy education, workforce training, academic research, to industrial technology development.The project website is gtsr.gatech.edu/munet.html, where users can access experimental management portal, open-source simulators, design repositories, test data, and so on. The project website is regularly updated during the project period and is planned to be maintained through at least three years after the expiration of the project.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

水生环境，包括海洋、湖泊和河流，是生命的基础。一个令人兴奋的方向是使用一组机器人来支持水生环境中的科学和发现。目前，国家机构还没有共享的基础设施来研究一组机器人如何在水下环境中相互协调。该项目开发了一个低成本和灵活的基础设施，称为mu-Net，以支持全国各地机构用户的实验室测试和现场实验。mu-Net基础设施是亚拉巴马大学和格鲁吉亚理工学院之间的一个合作项目，通过降低研究参与门槛来推进水下技术。它还支持培训下一代劳动力来管理和保护海洋资源。mu-Net基础设施使用面向服务的非分层软件架构，以促进集成传感、通信和导航。它包括：1）用于模拟和仿真的可重新配置的开源软件套件，2）用于实验室测试的小型水生机器人，3）用于湖上测试的商用现成自主水面车辆和自主水下车辆，以及4）支持共享使用的用户服务。mu-Net框架融合了以网络为中心和以机器人为中心的结构的功能，以增强协作机器人的灵活联网能力。其智力优势在于，基础设施使研究能够在多个方向上进行。该项目的研究领域包括海洋机器人的协作与协调、水下移动的通信网络、海洋机器人的联合组网与导航、水下物联网等。mu-Net基础设施旨在打破水下网络与机器人的学科壁垒，促进两个领域的密切互动。它大大降低了研究人员在海洋生物学、食物来源和经济发展等广泛领域的参与门槛。它有可能激发更多的探索地球的巨大水体的科学和商业活动。该项目采用一系列社区参与活动，如年度研讨会、会议特别会议、暑期培训学校和部署营地，以扩大用户社区。此外，通过成本效益的资产和用户通过社交媒体的参与，mu-Net吸引了广泛采用不同的教育和研究目的，从海洋扫盲教育，劳动力培训，学术研究，到工业技术开发。该项目的网站是gtsr.gatech.edu/munet.html，用户可以访问实验管理门户网站，开源模拟器，设计库，测试数据等。项目网站在项目期间定期更新，并计划在项目结束后至少三年内进行维护。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

First Step Towards μNet: Open-Access Aquatic Testbeds and Robotic Ecosystem

迈向μNet的第一步：开放式水生试验台和机器人生态系统

• DOI: 10.1145/3491315.3491322
• 发表时间: 2021
• 期刊: 15th Internationa Conference on Underwater Networks & Systems (WUWNet’21
• 作者: Mayberry, Scott;Wang, Junkai;Tao, Qiuyang;Zhang, Fumin;Song, Aijun;Hong, Xiaoyan;Dong, Shuai;Webb, Connor;Dugaev, Dmitrii;Peng, Zheng
• 通讯作者: Peng, Zheng

Distributed Cooperative Kalman Filter Constrained by Discretized Poisson Equation for Mobile Sensor Networks

移动传感器网络离散泊松方程约束的分布式协同卡尔曼滤波器

• DOI: 10.23919/acc55779.2023.10156161
• 发表时间: 2023
• 期刊: 2023 American Control Conference
• 作者: Zhang, Ziqiao;Mayberry, Scott T.;Wu, Wencen;Zhang, Fumin
• 通讯作者: Zhang, Fumin

A Laplacian Regularized Least Square Algorithm for Motion Tomography

运动层析成像拉普拉斯正则化最小二乘算法

• DOI: 10.23919/acc50511.2021.9482730
• 发表时间: 2021
• 期刊: Proc. American Control Conference (ACC 2021
• 作者: Ouerghi, Meriam;Zhang, Fumin
• 通讯作者: Zhang, Fumin

BlueBuzz, an Open-Source Acoustic Modem

• DOI: 10.1109/oceans47191.2022.9977326
• 发表时间: 2022-10
• 期刊: OCEANS 2022, Hampton Roads
• 作者: Scott Mayberry;Jinzhi Cai;Fumin Zhang

First Step Towards Low-Cost, Open-Source Optical Modem for Underwater Communication with Experimental Results

• DOI: 10.1145/3567600.3568157
• 发表时间: 2022-11
• 期刊: Proceedings of the 16th International Conference on Underwater Networks & Systems
• 作者: Jinzhi Cai;Scott Mayberry;Fumin Zhang