MRI: Development of an Underwater Mobile Testbed Using a Software-Defined Networking Architecture

MRI：使用软件定义的网络架构开发水下移动测试台

• 批准号: 1828678
• 负责人: Aijun Song
• 金额: $ 30万
• 依托单位: University of Alabama Tuscaloosa
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1828678&HistoricalAwards=false
• 关键词: MRI; Development; Underwater; Mobile; Testbed

This project, developing one of the first Software Defined Network (SDN)-based underwater mobile testbeds to support the operation of marine robot fleets, aims to address a technological bottleneck, that of achieving integrated communications and navigation underwater. A fleet of Autonomous Surface Vehicles (ASV)s are directed to follow sampling Autonomous Underwater Vehicles (AUVs) to provide acoustic and Magnetic Induction (MI) communication over relatively short ranges. Launching the following effort thrusts: Acoustic & MI Communication; Control of ASVs & UAVs; SDN architecture; and Integration and evaluation.The testbed will be designed to achieve cost-effectiveness, transferability, flexibility, and scalability and is expected to become a stable instrument that is accessible by multiple research communities that include ocean acoustics, communication and networking, robotics, oceanography and environmental sciences. The hybrid acoustic/MI communication will be used to achieve reliability and high data rates across the mobile network for ASVs and AUVs, while smooth autonomy of the fleet would be ensured by cooperative localization and real-time data transfer among the ASV-AUV pairs. The testbed is expected to enable various research directions, including underwater swarming, deep-learning-based underwater joint networking and navigation, and integrated oil spill responses.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.

该项目开发了第一个基于软件定义网络（SDN）的水下移动的测试平台，以支持海洋机器人舰队的运作，旨在解决技术瓶颈，即实现水下集成通信和导航。自主水面航行器（ASV）的舰队被指示跟随采样自主水下航行器（AUV），以在相对短的距离内提供声和磁感应（MI）通信。开展以下工作重点：声学&MI通信; ASV无人机的控制&; SDN架构;该试验台的设计将实现成本效益、可转移性、灵活性和可扩展性，预计将成为一个稳定的仪器，可供海洋声学、通信和网络、机器人、海洋学和环境科学等多个研究团体使用。混合声学/MI通信将用于实现ASV和AUV的移动的网络的可靠性和高数据速率，而ASV-AUV对之间的合作定位和实时数据传输将确保船队的平稳自主性。该测试平台预计将支持各种研究方向，包括水下集群、基于深度学习的水下联合网络和导航以及综合漏油响应。该奖项反映了NSF的法定使命，并通过使用该基金会的评估被认为值得支持智力优点和更广泛的影响审查标准。

项目成果

Optimal Real-time Scheduling of Human Attention for a Human and Multi-robot Collaboration System

人类和多机器人协作系统的人类注意力的最佳实时调度

• DOI: 10.23919/acc45564.2020.9147782
• 发表时间: 2020
• 期刊: Proceedings of the 2020 American Control Conference
• 作者: Yao, Ningshi;Zhang, Fumin
• 通讯作者: Zhang, Fumin

Learning and detecting abnormal speed of marine robots

• DOI: 10.1177/1729881421999268
• 发表时间: 2021-03-01
• 期刊: INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS
• 影响因子: 2.3
• 作者: Cho, Sungjin;Zhang, Fumin;Edwards, Catherine R.
• 通讯作者: Edwards, Catherine R.

A Derivative-Free Optimization Method With Application to Functions With Exploding and Vanishing Gradients

• DOI: 10.1109/lcsys.2020.3004747
• 发表时间: 2021-04-01
• 期刊: IEEE CONTROL SYSTEMS LETTERS
• 影响因子: 3
• 作者: Al-Abri, Said;Lin, Tony X.;Zhang, Fumin
• 通讯作者: Zhang, Fumin

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

Method of evolving junction on optimal path planning in flows fields

• DOI: 10.1007/s10514-022-10058-5
• 发表时间: 2019-04
• 期刊: Autonomous Robots
• 影响因子: 3.5
• 作者: Haoyan Zhai;Mengxue Hou;Fumin Zhang;Haomin Zhou