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

该项目开发和测试新的压缩传感和传感器定位技术，适用于各种不同的移动的机器人设计，同时可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相关者提供了切实的成果，可以利用这些成果将这些系统推进到未来现实世界的灾害管理场景中。研究小组开发了新的技术方法，从而调动了更多智能，自动化的“眼睛和耳朵”。“外联工作包括：（一）将活动与从业人员结合起来;（二）为环境工程师和第一反应者等受众举办研讨会/网播;（三）每年举办技术日营，吸引代表性不足群体的中学生学习工程;（四）向当地K-12机构进行演示;（五）将项目主题纳入正规课程;国际合作：该项目介绍了机器人2.0;这是一个针对自主机器人的框架，这些机器人是合作者和共同保护者，适应人类并与人类一起工作。该研究小组开发了一个网络控制网络（CCN），通过动态连接驱动，传感和控制子网络，允许多个固定和移动的机器人环境传感和测量，以快速适应不断变化的环境。这种CCN ControlWare和压缩传感架构的设计可以适用于灾难响应，缓解和管理之外的其他大规模问题，例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故。机器人传感平台不需要先验知识的危险和动态变化的环境，他们正在监测。机器人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.