NRI: INT: COLLAB: Interactive and collaborative robot-assisted emergency evacuations

NRI：INT：COLLAB：交互式协作机器人辅助紧急疏散

• 批准号: 1830335
• 负责人: Hai Lin
• 金额: $ 50.95万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1830335&HistoricalAwards=false
• 关键词: NRI; INT; COLLAB; Interactive; collaborative

Many emergencies require people to evacuate a building quickly. During an emergency, evacuees must make quick decisions, so they tend to rely on default decision making that may put them at risk, such as exiting the way they entered, following a crowd, or sheltering in place. When a crowd attempts to exit through a single exit, choke points and crowd congestion may impede the safe flow of evacuees, potentially resulting in a stampede of people and the loss of human lives. Mobile robots are increasingly being deployed as assistants on city streets and in hotels, shopping centers and hospitals. The future ubiquity of these systems offers an opportunity to change how people are evacuated from dangerous situations. In particular, when compared with traditional emergency infrastructure, such as fire alarms and smoke detectors, mobile robots can achieve better situation awareness and use this information to expedite evacuation and enhance safety. Additionally, mobile robots can be used in risky and life-threatening situations, such as chemical spills or active shooter scenarios, which present dangers to human first responders. This project aims to derive a scalable design framework and develop an embodied multi-robot evacuation system where multiple mobile robots, originally tasked for different purposes, serve as emergency evacuation first responders leading people to safety. In particular, multiple mobile robots efficiently coordinate with each other and actively interact with evacuees to maximize their egress. The project significantly contributes to the understanding of how people respond to a robots' directions and authoritative commands. Furthermore, the project implements these findings and demonstrates their effectiveness using real-world experiments with human subjects. Beyond emergency evacuation, the research findings can be extended to many other related areas, especially those involving cooperative robot teams that are embodied in an uncertain and dynamic physical world with the need to actively interact with humans; e.g., battlefield, law enforcement, urban transportation systems, manufacturing systems, rehabilitation and health management.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

许多紧急情况要求人们迅速撤离建筑物。在紧急情况下，撤离人员必须做出快速的决定，因此他们倾向于依靠默认决策，这可能会使他们处于危险之中，例如退出他们进入的方式，跟随人群或庇护所。当人群试图通过一次出口退出时，扼流圈和人群拥塞可能会阻碍撤离者的安全流动，可能导致人们的踩踏和丧失人类的生命。移动机器人越来越多地在城市街道以及酒店，购物中心和医院中部署为助手。这些系统的未来普遍性为改变人们从危险情况中撤离的方式提供了机会。特别是，与传统的紧急基础设施（例如火灾警报器和烟雾探测器）相比，移动机器人可以提高情况意识，并使用此信息来加快疏散并提高安全性。此外，移动机器人可用于危险和威胁生命的情况，例如化学溢出或主动射击者场景，这些情况对人类的急救人员构成危险。该项目旨在得出一个可扩展的设计框架，并开发一个具体的多机器人疏散系统，该系统最初是用于不同目的的多个移动机器人，作为紧急撤离的第一响应者，使人们掌握了安全。特别是，多个移动机器人有效地相互协调，并与疏散物积极相互作用以最大化其出口。该项目极大地有助于理解人们如何应对机器人的指示和权威命令。此外，该项目实现了这些发现，并通过对人类受试者进行的现实世界实验证明了它们的有效性。除了紧急撤离之外，研究结果还可以扩展到许多其他相关领域，尤其是那些涉及合作机器人团队的领域，这些领域体现在一个不确定且充满活力的身体世界中，需要与人类积极互动；例如，战场，执法，城市运输系统，制造系统，康复和健康管理。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响评估的评估来支持的。