Multi-Robot-Assisted Human Crowd Evacuation using Navigation Velocity Fields
Multi-Robot-Assisted Human Crowd Evacuation using Navigation Velocity Fields
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DOI：
10.1109/cdc51059.2022.9993368
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发表时间：
2022-09
期刊：
影响因子：
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通讯作者：
Tongjia Zheng;Zhenyuan Yuan;Mollik Nayyar;Alan R. Wagner;Minghui Zhu;Hai Lin
中科院分区：
文献类型：
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作者：
Tongjia Zheng;Zhenyuan Yuan;Mollik Nayyar;Alan R. Wagner;Minghui Zhu;Hai Lin
本文研究了一个机器人辅助人群疏散的问题，我们控制一小群机器人引导大量的人群到安全的地方。挑战在于如何对人机交互进行建模，并设计机器人控制，以间接控制数量远远超过机器人的人口。为了应对这一挑战，我们将人群视为一个连续体，并将疏散目标制定为将人群密度驱动到目标位置。我们提出了一种新的平均场模型，它包括一个家庭的微观方程，明确地模拟人类的运动是如何本地引导的机器人和相关的宏观方程，描述了人群密度是如何控制的导航速度场所产生的所有机器人。然后，我们设计了密度反馈控制器的机器人动态调整其状态，使产生的导航速度场驱动人群密度的目标密度。所提出的控制器的稳定性保证证明。基于代理的模拟评估所提出的疏散算法。
This work studies a robot-assisted crowd evacuation problem where we control a small group of robots to guide a large human crowd to safe locations. The challenge lies in how to model human-robot interactions and design robot controls to indirectly control a human population that significantly outnumbers the robots. To address the challenge, we treat the crowd as a continuum and formulate the evacuation objective as driving the crowd density to target locations. We propose a novel mean-field model which consists of a family of microscopic equations that explicitly model how human motions are locally guided by the robots and an associated macroscopic equation that describes how the crowd density is controlled by the navigation velocity fields generated by all robots. Then, we design density feedback controllers for the robots to dynamically adjust their states such that the generated navigation velocity fields drive the crowd density to a target density. Stability guarantees of the proposed controllers are proven. Agent-based simulations are included to evaluate the proposed evacuation algorithms.