Hybrid dynamics in delay-coupled swarms with mothership networks

Hindes, Jason; Szwaykowska, Klementyna; Schwartz, Ira B.

doi:10.1103/physreve.94.032306

Cited by 21 publications

(19 citation statements)

References 32 publications

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“…For example, an individual agent of a flock can be slow enough to respond to a signal coming from its neighbour. This causes communication-delay [38,39,40,41]. It has been shown that in presence of a noise induced transition from translatory to rotatory motion of agents [42], the time-delayed communication among them can introduce further instabilities where the harmonically interacting agents can form dynamic clusters or swarms, with a high degree of polarity [38].…”

Section: Introductionmentioning

confidence: 99%

Active particle condensation by non-reciprocal and time-delayed interactions

2018

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We consider the flocking of self-propelling agents in two dimensions, each of which communicates with its neighbors within a limited vision-cone. Also, the communication occurs with some time-delay. The communication among the agents are modeled by Vicsek rules. In this study we explore the combined effect of non-reciprocal interaction (induced by limited vision-cone) among the agents and the presence of delay in the interactions on the dynamical pattern formation within the flock. We find that under these two influences, without any position-based attractive interactions or confining boundaries, the agents can spontaneously condense into "drops". Though the agents are in motion within the drop, the drop as a whole is pinned in space. We find that this novel state of the flock has a well-defined order and it is stabilized by the noise present in the system.

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Section: Introductionmentioning

confidence: 99%

Active particle condensation by non-reciprocal and time-delayed interactions

2018

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“…Since the latter class of models derive from basic physical principles, they showcase a broader spectrum of emergent motion patterns, and they can more easily incorporate, e.g., active-matter dynamics 15,43 and collective motion on arbitrary surfaces 46 . Recent work has begun to address network structure in such physically-inspired swarming systems, including how topology affects robustness to noise 47 and how heterogenous topology drives the formation of hybrid motion states 48 . Yet, much remains unknown about how complex topology influences the dynamical stability of swarms with general nonlinear interactions and under what circumstances a sparse swarming network can maintain coherent motion of all its agents-especially in the much broader range of collective-motion patterns without rigid velocity consensus.…”

Section: Introductionmentioning

confidence: 99%

“…To make progress, we consider a generic system of mobile agents moving under the influence of self-propulsion, friction, and pairwise interaction forces 41,43,47,49 mediated through a network 42,48 . In the absence of interactions, each swarmer will tend to a fixed speed, which balances its self-propulsion and friction but has no preferred direction 46 .…”

Section: Introductionmentioning

confidence: 99%

Swarm Shedding in Networks of Self-propelled Agents

Hindes

Edwards

Kasraie

et al. 2021

Preprint

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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 stable and coherent 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.

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“…Since the latter class of models derive from basic physical principles, they showcase a broader spectrum of emergent motion patterns, and can more easily incorporate, e.g., active-matter dynamics 15 , 43 and collective motion on arbitrary surfaces 47 . Recent work has begun to address network structure in such physically-inspired swarming systems, including how topology affects robustness to noise 48 and how heterogenous topology drives the formation of hybrid motion states 49 . Yet, much remains unknown about how complex topology influences the dynamical stability of swarms with general nonlinear interactions and under what circumstances a sparse swarming network can maintain coherent motion of all its agents—especially in the much broader range of collective-motion patterns without rigid velocity consensus.…”

Section: Introductionmentioning

confidence: 99%

“…To make progress, we consider a well known physics-based model of mobile agents moving under the influence of self-propulsion, damping, and pairwise interaction forces 41 , 43 , 48 , 50 , to which we add explicit sparse networks that mediate and constrain the inter-agent interactions 42 , 49 . In the absence of interactions, each swarmer will tend to a fixed speed, which balances its self-propulsion and damping but has no preferred direction 47 .…”

Section: Introductionmentioning

confidence: 99%

Swarm shedding in networks of self-propelled agents

Hindes

Edwards

Kasraie

et al. 2021

Sci Rep

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Hybrid dynamics in delay-coupled swarms with mothership networks

Cited by 21 publications

References 32 publications

Active particle condensation by non-reciprocal and time-delayed interactions

Active particle condensation by non-reciprocal and time-delayed interactions

Swarm Shedding in Networks of Self-propelled Agents

Swarm shedding in networks of self-propelled agents

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