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.

该项目开发了基于水下的水下移动测试床以支持海洋机器人机队的运行之一，旨在解决技术瓶颈，即实现集成通信和导航水下的技术瓶颈。指示一组自动表面车辆（ASV）遵循采样自动驾驶水下车辆（AUV），以在相对较短的范围内提供声学和磁感应（MI）通信。发起以下努力：声学和MI通信；控制ASV和无人机； SDN体系结构；测试平台将旨在实现成本效益，可转移性，灵活性和可伸缩性，并有望成为一种稳定的工具，该工具可以被包括海洋声学，通信和网络，机器人技术，海洋学和环境科学在内的多个研究社区获得。混合声/MI通信将用于在ASV和AUVS上实现移动网络上的可靠性和高数据速率，而舰队的平稳自主权通过合作定位和ASV-AUV对之间的实时数据传输来确保。预计测试床有望实现各种研究方向，包括水下蜂群，基于深度学习的水下联合网络和导航，以及集成的溢油响应。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的审查标准来通过评估来通过评估来支持的。

项目成果

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.

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

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

Contention-resolving model predictive control for an intelligent intersection traffic model

• DOI: 10.1007/s10626-020-00336-8
• 发表时间: 2021-03
• 期刊: Discrete Event Dynamic Systems
• 作者: Ningshi Yao;Fumin Zhang