NeTS: Medium: Collaborative Research: Optimal Communication for Faster Sensor Network Coordination

NeTS：媒介：协作研究：更快传感器网络协调的最佳通信

• 批准号: 1302222
• 负责人: VICTOR PRECIADO
• 金额: $ 51.5万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1302222&HistoricalAwards=false
• 关键词: NeTS; Medium; Collaborative; Research; Optimal

The goal of this project is to develop a new framework where teams of mobile robots self-engineer the structure of their communication network in order to improve on the performance of distributed algorithms used for team coordination. The key idea that enables this work is the representation of the network structure in terms of metrics that depend on the full eigenvalue spectrum of the network's adjacency and Laplacian matrices, but can be approximated in a very efficient and decentralized way. These metrics can then be related to the performance of popular, distributed, coordination algorithms, such as consensus, gossiping, and viral information dissemination. The intellectual merit of this research lies in the development of a hybrid network of mobile robots that is controlled jointly in the space of network configurations and robot positions. The study of the integrated system requires the synthesis of new theoretical results drawing from control theory, spectral graph theory, wireless networking, and optimization. This hybrid network combines the following interrelated objectives: Spectral analysis and distributed control of robot networks; Integrated network and mobility control; Richer models of the communication space; Platform deployment and validation.Successful completion of this research will provide these necessary components in facilitating the design of mobile autonomous systems and fostering their adoption. Wide availability of such systems can have a significant societal impact on, e.g., search, rescue and recovery operations, environmental monitoring for homeland security, or surveillance and reconnaissance missions. The broader impact of this project lies on disseminating the research output in the industry and academia.

这个项目的目标是开发一个新的框架，团队的移动的机器人自我设计的结构，他们的通信网络，以提高性能的分布式算法用于团队协调。实现这项工作的关键思想是网络结构的度量表示，这些度量取决于网络邻接矩阵和拉普拉斯矩阵的完整特征值谱，但可以以非常有效和分散的方式近似。然后，这些指标可以与流行的分布式协调算法的性能相关，例如共识，八卦和病毒式信息传播。这项研究的智力价值在于开发一个混合网络的移动的机器人，共同控制在网络配置和机器人位置的空间。集成系统的研究需要从控制理论、谱图理论、无线网络和优化等方面综合新的理论成果。这种混合网络结合了以下相互关联的目标：频谱分析和分布式控制的机器人网络;集成的网络和移动控制;更丰富的通信空间模型;平台部署和validation. Successfully完成这项研究将提供这些必要的组件，促进移动的自主系统的设计，并促进其采用。这种系统的广泛可用性可以对以下方面产生重大的社会影响，例如，搜索、救援和恢复行动、国土安全环境监测或监视和侦察任务。该项目的更广泛影响在于在工业界和学术界传播研究成果。