U.S. Naval Research Laboratory, Washington, DC, 20375, USA.
University of Pennsylvania, Philadelphia, PA, 19104, USA.
Sci Rep. 2021 Jun 29;11(1):13544. doi: 10.1038/s41598-021-92748-1.
Understanding swarm pattern formation is of great interest because it occurs naturally in many physical and biological systems, and has artificial applications in robotics. In both natural and engineered swarms, agent communication is typically local and sparse. This is because, over a limited sensing or communication range, the number of interactions an agent has is much smaller than the total possible number. A central question for self-organizing swarms interacting through sparse networks is whether or not collective motion states can emerge where all agents have coherent and stable dynamics. In this work we introduce the phenomenon of swarm shedding in which weakly-connected agents are ejected from stable milling patterns in self-propelled swarming networks with finite-range interactions. We show that swarm shedding can be localized around a few agents, or delocalized, and entail a simultaneous ejection of all agents in a network. Despite the complexity of milling motion in complex networks, we successfully build mean-field theory that accurately predicts both milling state dynamics and shedding transitions. The latter are described in terms of saddle-node bifurcations that depend on the range of communication, the inter-agent interaction strength, and the network topology.
理解群体模式形成具有重要意义,因为它在许多物理和生物系统中自然发生,并在机器人技术中有人工应用。在自然和工程群体中,代理通信通常是局部和稀疏的。这是因为,在有限的传感或通信范围内,代理的交互数量远远小于总可能数量。通过稀疏网络相互作用的自组织群体的一个核心问题是,是否可以出现所有代理都具有相干和稳定动力学的集体运动状态。在这项工作中,我们引入了群体脱落现象,其中弱连接的代理从具有有限范围相互作用的自推进群体网络中的稳定铣削模式中被抛出。我们表明,群体脱落可以局部化在少数几个代理周围,也可以非局部化,并导致网络中所有代理的同时抛出。尽管复杂网络中的铣削运动很复杂,但我们成功地构建了均值场理论,该理论准确地预测了铣削状态动力学和脱落转变。后者用依赖于通信范围、代理间相互作用强度和网络拓扑的鞍点分岔来描述。