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.

许多紧急情况需要人们迅速撤离建筑物。在紧急情况下，疏散人员必须迅速做出决定，因此他们往往依赖于可能使他们处于危险之中的默认决策，例如从他们进入的方式中退出，跟随人群或在原地避难。当人群试图通过单一出口离开时，阻塞点和人群拥挤可能会阻碍疏散人员的安全流动，可能导致人群踩踏和人员生命损失。移动的机器人越来越多地被部署在城市街道、酒店、购物中心和医院中作为助手。这些系统的未来普及为改变人们从危险情况中疏散的方式提供了机会。特别是，与传统的紧急基础设施（如火警和烟雾探测器）相比，移动的机器人可以实现更好的态势感知，并利用这些信息加快疏散和提高安全性。此外，移动的机器人可用于危险和危及生命的情况，例如化学品泄漏或主动射击场景，这对人类第一响应者构成危险。该项目旨在导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，其中多个移动的机器人，最初负责不同的目的，作为紧急疏散第一响应者领导人们的安全。特别是，多个移动的机器人有效地相互协调，并积极与疏散人员互动，以最大限度地提高他们的出口。该项目有助于理解人们如何对机器人的指示和权威命令做出反应。此外，该项目实施这些发现，并使用人类受试者的真实世界实验证明其有效性。除了紧急疏散之外，研究结果还可以扩展到许多其他相关领域，特别是那些涉及合作机器人团队的领域，这些团队体现在不确定和动态的物理世界中，需要与人类积极互动;例如，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。