Hindes Jason, Edwards Victoria, Kamimoto Sayomi, Triandaf Ioana, Schwartz Ira B
U.S. Naval Research Laboratory, Code 6792, Plasma Physics Division, Washington, DC 20375, USA.
U.S. Naval Research Laboratory, Code 5514, Navy Center for Applied Research in Artificial Intelligence, Washington, DC 20375, USA.
Phys Rev E. 2020 Apr;101(4-1):042202. doi: 10.1103/PhysRevE.101.042202.
It is known that introducing time delays into the communication network of mobile-agent swarms produces coherent rotational patterns, from both theory and experiments. Often such spatiotemporal rotations can be bistable with other swarming patterns, such as milling and flocking. Yet, most known bifurcation results related to delay-coupled swarms rely on inaccurate mean-field techniques. As a consequence, the utility of applying macroscopic theory as a guide for predicting and controlling swarms of mobile robots has been limited. To overcome this limitation, we perform an exact stability analysis of two primary swarming patterns in a general model with time-delayed interactions. By correctly identifying the relevant spatiotemporal modes, we are able to accurately predict unstable oscillations beyond the mean-field dynamics and bistability in large swarms-laying the groundwork for comparisons to robotics experiments.
从理论和实验两方面都可知,在移动智能体群体的通信网络中引入时间延迟会产生连贯的旋转模式。通常,这种时空旋转可能与其他群体模式(如 milling 和 flocking)呈现双稳态。然而,大多数已知的与延迟耦合群体相关的分岔结果依赖于不准确的平均场技术。因此,将宏观理论用作预测和控制移动机器人群体的指南的效用受到了限制。为克服这一限制,我们在具有时间延迟相互作用的一般模型中对两种主要的群体模式进行了精确的稳定性分析。通过正确识别相关的时空模式,我们能够准确预测超出平均场动力学的不稳定振荡以及大群体中的双稳态,从而为与机器人实验进行比较奠定基础。