Collective behavior in groups of self-propelled particles with active and passive sensing inspired by animal echolocation

Collective behavior is observed in many physical and biological systems and has been studied through agent-based models, including the Vicsek model, which enforces aligned motion among agents. The behaviors produced by these models are highly dependent on the type of sensing individuals use. In nature, bats successfully use a complex form of sensing, namely, active echolocation in a relatively narrow beam and passive eavesdropping on their conspecifics' sound over a wider volume. Inspired by this system, we investigate whether augmenting an active sensing mechanism with passive sensing can improve the collective behavior of the group. A three-dimensional Vicsek-type model is presented to study the effects of combining active and passive sensing on collective behavior of a group of particles in the presence of noise. Phase transition is observed in both the presence and absence of passive sensing, yet the range of parameters for which ordered and disordered group states exist dramatically changes when passive sensing is implemented. Notably, we find numerous cases of the model for which the implementation of passive sensing increases the robustness of the collective behavior to noise.