RI: Small: Providing Quality of Information in Robot Sensor Networks

RI：小型：在机器人传感器网络中提供高质量的信息

• 批准号: 1116010
• 负责人: Eric Frew
• 金额: $ 50万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-15 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1116010&HistoricalAwards=false
• 关键词: RI; Small; Providing; Quality; Information

This project develops distributed control algorithms for robot sensor networks using information dynamics to unify network mobility and communication. The new framework moves beyond location-based mobility control algorithms and packet-based communication protocols to a single information-theoretic approach. The framework is developed through: (1) formulation of a new quality of service of information metric and characterization of feasible quality of service demands, (2) adaptive receding horizon control that adjusts planning horizon and sample time based on information dynamics, (3) distributed calculation and optimization of team quality of service, and (4) experimental validation using a heterogeneous indoor robot sensor network and outdoor unmanned aircraft systems.This research enables the collection of in situ data over large spatiotemporal scales. When deployed in remote or hazardous locations the data collected with these networks leads to a direct improvement to model or understand complex environments, which can help save lives. Students will benefit from the multi-disciplinary activities involved, including embedded computing, miniature sensor devices, wireless networking, and automatic control.

本计画利用资讯动力学来统一网路的移动性与通讯性，发展机器人感测网路的分散式控制演算法。 新的框架超越了基于位置的移动性控制算法和基于分组的通信协议，以一个单一的信息理论的方法。 该框架是通过以下方式制定的：（1）制定新的信息度量服务质量和表征可行的服务质量需求，（2）基于信息动力学调整规划范围和采样时间的自适应滚动范围控制，（3）团队服务质量的分布式计算和优化，（4）实验验证使用异构室内机器人传感器网络和室外无人机系统。这项研究能够在大时空尺度上收集现场数据。 当部署在偏远或危险地区时，这些网络收集的数据可以直接改善建模或理解复杂环境的能力，这有助于挽救生命。 学生将受益于所涉及的多学科活动，包括嵌入式计算，微型传感器设备，无线网络和自动控制。