Delay induced swarm pattern bifurcations in mixed reality experiments

Abstract

Swarms of coupled mobile agents subject to inter-agent wireless communication delays are known to exhibit multiple dynamic patterns in space that depend on the strength of the interactions and the magnitude of the communication delays. We experimentally demonstrate communication delay-induced bifurcations in the spatiotemporal patterns of robot swarms using two distinct hardware platforms in a mixed reality framework. Additionally, we make steps toward experimentally validating theoretically predicted parameter regions where transitions between swarm patterns occur. We show that multiple rotation patterns persist even when collision avoidance strategies are incorporated, and we show the existence of multi-stable, co-existing rotational patterns not predicted by usual mean field dynamics. Our experiments are the first significant steps toward validating existing theory and the existence and robustness of the delay-induced patterns in real robotic swarms.

Swarm shedding in networks of self-propelled agents

“…Such transitions were accurately described in terms of saddle-node bifurcations of circular-orbit limit cycles within a mean-field approximation, and agreed well with numerical simulations. This network-based swarming theory will guide new physics-inspired swarm robotics experiments, where earlier instantiations effectively assumed all-to-all communication, and hence, may not be easily scalable to larger robotic swarms, especially in complex environments 42 , 46 .…”

“…On the other hand, physically inspired models, where collective motion emerges from the more basic interplay of position-dependent forces and self-propulsion energy, have typically assumed global, homogeneous, or lattice communication topology 39 – 45 . For instance, early robotics experiments based on such nonlinear-physics models, also assumed all-to-all coupling 42 , 46 —making them difficult to scale to larger systems and less controlled environments. 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 .…”

“…A successful theory in this regard should predict how strong the coupling must be, and how far the communication range, in order to stabilize collective motion states in given a network. Such a theory could also provide insights for guiding robotics experiments with autonomous ground, surface, and aerial vehicles 42 , 53 , 46 , which have used Eqs. ( 2 ), and similar variants, as an underlying control law.…”

Swarm Shedding in Networks of Self-propelled Agents

“…A successful theory in this regard should predict how strong the coupling must be, and how far the communication range, in order to stabilize collective motion states in given a network. Such a theory could also provide insights for guiding robotics experiments with autonomous ground, surface, and aerial vehicles 42,52,54 , which have used Eqs. (2), and similar variants, as an underlying control law.…”

Interacting Swarm Sensing and Stabilization

“…In pushing the theory to robotic platforms, engineers have focused on designing and building swarms of mobile robots with a large and ever expanding number of platforms, as well as virtual and physical interaction mechanisms [11,21,22,23,24]. Robotic applications range from exploration [22], mapping [25], resource allocation [26,27,28], and swarms for defense [29,30,31] Since robotic swarms must operate in real environments, theoretical and experimental swarming systems have been analyzed in many contexts, including swarms of mobile robots with homogeneous and heterogeneous agents and delayed communication [32,33]. Moreover, the dynamics of robotic swarms have been tested in complex environments, from drones flying in the air, to boats tracking coherent structures in complex flows, and collaborating robots locating sources in turbulent media [34,35].…”