NRI: Collaborative Research: Dynamic Robot Guides for Emergency Evacuations

人群踩踏是最有害的人类集体行为之一。在历史上的各种事件中，由于诸如火灾的爆发或火器的意外发射而引起的恐慌比最初的触发事件造成的危害更大。本项目支持人机交互对人群动态影响的基础研究，旨在设计动态机器人控制算法，以在紧急情况下帮助人类并防止恐慌。这项研究的最终目标将是可重构的机器人向导，可以响应各种需求。这包括不同类型的紧急疏散，以及涉及人群大规模移动的非紧急情况，例如游行、音乐会或其他大型公共活动。该项目通过以机器人为中心的教育和短期课程开发，将研究与教育活动结合起来。为了让年轻一代接触科学技术，该项目将与一所大学教育中心和一所社区学院合作，开展各种外展活动。该项目的目标是研究人群动力学中的人机交互，开发最优反馈控制来调节人流分布，并设计机器人辅助的紧急疏散算法。该研究将通过实验验证和测量人群动力学中控制人机交互的相互作用力，从而推进人机交互的最新技术，填补机器人研究的空白。提出的机器人运动原语设计为基于学习的机器人运动规划提供了新的方法，以有效地吸引人类。该项目验证了动态机器人导轨在室内环境下真实人机交互实验中的使用。还将在购物中心和校园建筑等基准环境中进行仿真验证，并评估替代机器人辅助疏散策略的效率。虽然主要针对智能机器人，但预计研究结果将是跨领域的，并适用于其他领域，如交通、通信和控制。

Crowd stampede is one of the most harmful collective human behaviors. In incidents throughout history, panic due, for example, to the outbreak of fire or the unexpected discharge of firearms has been a greater hazard than the original triggering events. This project supports fundamental research on the influence of human-robot interaction on crowd dynamics, towards the design of dynamic robot control algorithms to assist humans and prevent panic in emergency situations. The ultimate goal of this research will be reconfigurable robot guides that can respond to a variety of needs. These include different types of emergency evacuation, as well as non-emergency situations involving mass movement of crowds, such as at parades, concerts, or other large public events. The project integrates research with educational activities through robot-centric education and short course development. To engage the younger generation with science and technology, the project will partner with a university educational center and a community college for various outreach activities.The objective of the project is to investigate human-robot interaction in crowd dynamics, develop optimal feedback control to regulate human flow distribution, and design robot-assisted emergency evacuation algorithms. The research will advance the state-of-the-art in human-robot interaction, and fill a gap in robotics research by experimentally validating and measuring the interaction forces governing human-robot interaction in crowd dynamics. The proposed robot motion primitive design leads to new approaches for learning-based robot motion planning to efficiently engage humans. The project validates the use of dynamic robot guides in real human-robot interaction experiments in indoor environments. Simulation validation in benchmark environments such as shopping-malls and campus buildings will also be performed, and the efficiency of alternative robot-assisted evacuation strategies will be evaluated. While primarily for intelligent robots, the research results are anticipated to be cross-cutting and applicable to other areas such as transportation, communication, and control.