NetSE: Small: Game Theoretic Coverage and Connectivity Services

NetSE：小型：博弈论覆盖和连接服务

• 批准号: 0916209
• 负责人: Ibrahim Isler
• 金额: $ 38.2万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0916209&HistoricalAwards=false
• 关键词: NetSE; Small; Game; Theoretic; Coverage

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Robotic Sensor Networks (RSNs) are finding increasing use in criticalapplications such as surveillance, environmental monitoring, emergencyresponse and search-and-rescue. With recent advances in embeddedtechnologies, devices that can be used as RSN units are becoming availablefor everyday use. Intellectual Merit:This project focuses on pursuit-evasion games where one or morepursuers tries to "capture" an evader who, in turn, tries to avoidcapture. Robust, provably correct solutions to many RSN tasks (such as coverage and connectivity) can be obtained by modeling them as pursuit-evasion games.Existing solutions to pursuit-evasion games usually assume that(i) all players can observe each other at all times and (ii) there isa centralized authority that coordinates all pursuers. Hence, suchsolutions are not applicable for modeling RSN applications where thenetwork faces severe sensing and communication limitations. Theprimary goals of the proposed work are to understand the effect of theselimitations on the outcome of the game, and to design strategies toovercome them. Broader Impacts:Sensing and actuation are expected to play significant roles in theevolution of information technology and the Internet. Thisresearch will contribute to this evolution in two major ways. First,it will deliver algorithms, tools and techniques to addresscommunication, sensing and actuation issues simultaneously. Second,it will help scientists and engineers participating in this development acquire a broadrange of skills in areas such as algorithms, perception, robotics and communications. Thiswill be achieved through outreach programs and by incorporating this research in PI's courses.

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。机器人传感器网络（RSN）在监视，环境监测，应急响应和搜索和救援等关键应用中的使用越来越多。随着嵌入式技术的最新进展，可以用作RSN单元的设备正在变得可用于日常使用。智力优点：这个项目的重点是追求逃避游戏，一个或多个追求者试图“捕获”一个逃避者，反过来，试图避免捕获。许多RSN任务（如覆盖和连通性）的鲁棒、可证明正确的解决方案可以通过将其建模为追捕-逃避游戏来获得。现有的追捕-逃避游戏解决方案通常假设（i）所有参与者可以随时观察对方，（ii）伊萨个集中的权威机构协调所有追捕者。因此，这样的解决方案是不适用的建模RSN应用程序中的网络面临严重的传感和通信的限制。本研究的主要目标是了解这些限制对博弈结果的影响，并设计克服这些限制的策略。更广泛的影响：传感和驱动预计将在信息技术和互联网的发展中发挥重要作用。这项研究将在两个主要方面促进这一演变。首先，它将提供算法，工具和技术，以同时解决通信，传感和驱动问题。其次，它将帮助参与这一开发的科学家和工程师获得算法、感知、机器人和通信等领域的广泛技能。这将通过推广计划和将这项研究纳入PI的课程来实现。