NRI: Collaborative Research: Robotics 2.0 for Disaster Response and Relief Operations

该项目开发和测试了新颖的压缩传感和传感器定位技术，这些技术适用于各种不同的移动机器人设计，同时可以在当今的无线通信基础设施上运行。独特的现场实验室和现场实验为科学家和其他利益攸关方提供了切实的成果，可以利用这些成果将这些系统推进到未来现实世界的危险管理情景中。研究小组开发了新的技术方法，结果是动员更智能、自动化的“地面上的眼睛和耳朵”。外展工作包括：(I)将活动与从业者结合起来；(Ii)面向环境工程师和第一反应人员等受众的研讨会/网络广播；(Iii)年度技术日营，以吸引来自代表性不足群体的中学生进入工程学；(Iv)向当地K-12机构演示；(V)将项目主题纳入常规课程；以及(Vi)国际合作。研究小组开发了一个网络控制网络(CCN)，通过将驱动、感知和控制的子网络动态链接在一起，允许多个固定和移动的机器人环境感知和测量快速适应不断变化的环境。这种CCN控件和压缩传感架构的设计可以适用于除灾难应对、减灾和管理之外的其他大规模问题，如电网监控和重新配置，或区域城市交通运营，以应对交通拥堵和事件。机器人传感平台不需要对它们正在监测的危险和动态变化的环境的先验知识。Robotics 2.0框架允许快速响应、准备和管理各种类型的灾难。

The project develops and tests novel compressive sensing and sensor locating techniques that are adaptable to a myriad of different mobile robot designs while operable on today's wireless communication infrastructures. Unique in-situ laboratory and field experiments provide tangible results to scientists and other stakeholders that can be leveraged to advance these systems into future real-world hazard management scenarios. The research team develops new technological approaches that results in mobilizing more intelligent, automated "eyes and ears on the ground." Outreach efforts include: (i) integration of the activities with practitioners; (ii) Seminars/webcasts to audiences like environmental engineers and first responders; (iii) Annual technology day camps to attract middle-schoolers from under-represented groups to engineering; (iv) Demonstrations to local K-12 institutions; (v) Inclusion of the project themes to the regular curricula; and (vi) International collaborations.This project introduces Robotics 2.0; a framework that targets autonomous robots that are co-workers and co-protectors, adapting to and working with humans. The research team develops a Cyber-Control Network (CCN) to allow multiple fixed and mobile robotic environmental sensing and measurements to adapt quickly to the changing environment by dynamically linking sub-networks of actuation, sensing, and control together. The design of such CCN ControlWare, and compressive sensing architectures, could be adapted to other large-scale problems beyond disaster response, mitigation, and management, such as power grid monitoring and reconfiguration, or regional urban traffic operations to respond to traffic congestion and incidents. The robotic sensing platforms do not require a-priori knowledge of the hazardous and dynamically changing environments they are monitoring. The Robotics 2.0 framework allows to swiftly respond, to prepare, and to manage various types of disasters.