NRI: Collaborative Research: Dynamic Robot Guides for Emergency Evacuations

人群踩踏是人类最具危害性的集体行为之一。在整个历史事件中，例如，由于爆发火灾或意外开枪造成的恐慌，比最初的触发事件具有更大的危险。该项目支持对人-机器人交互对人群动力学的影响的基础研究，用于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能够响应各种需求的可重构机器人导轨。这些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，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，将研究与教育活动相结合。为了让年轻一代接触科学技术，该项目将与一个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与机器人相互作用，开发最优反馈控制以调节人流分布，并设计机器人辅助紧急疏散算法。这项研究将推进人-机器人交互的最先进水平，并通过实验验证和测量人群动力学中支配人-机器人交互的作用力，填补机器人学研究的空白。所提出的机器人运动基元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中真实的人-机器人交互实验中的使用。还将在商场和校园建筑等基准环境中进行模拟验证，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，但预计研究成果将具有交叉性，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.