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

本项目开发机器人传感器网络的分布式控制算法，利用信息动力学来统一网络的移动性和通信。新框架超越了基于位置的移动控制算法和基于分组的通信协议，采用了单一的信息论方法。该框架通过(1)制定新的服务质量信息度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水平和样本时间的自适应退化水平控制；(3)团队服务质量的分布式计算和优化；(4)基于异构室内机器人传感器网络和室外无人机系统的实验验证。这项研究使得在大的时空尺度上收集原位数据成为可能。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进模型或了解复杂环境，从而有助于挽救生命。学生将受益于涉及的多学科活动，包括嵌入式计算，微型传感器设备，无线网络和自动控制。

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.