Dynamics of cooperative excavation in ant and robot collectives

Abstract

The solution of complex problems by the collective action of simple agents in both biologically evolved and synthetically engineered systems involves cooperative action. Understanding the resulting emergent solutions requires integrating across the organismal behaviors of many individuals. Here we investigate an ecologically relevant collective task in black carpenter ants Camponotus pennsylvanicus: excavation of a soft, erodible confining corral. Individual ants show a transition from individual exploratory excavation at random locations to spatially localized collective exploitative excavation and eventual excavate out from the corral. An agent minimal continuum theory that coarse-grains over individual actions and considers their integrated influence on the environment leads to the emergence of an effective phase space of behaviors in terms of excavation strength and cooperation intensity. To test the theory over the range of both observed and predicted behaviors, we used custom-built robots (RAnts) that respond to stimuli to characterize the phase space of emergence (and failure) of cooperative excavation. By tuning the amount of cooperation between RAnts, we found that we could vary the efficiency of excavation and synthetically generate the other macroscopic phases predicted by our theory. Overall, our approach shows how the cooperative completion of tasks can arise from simple rules that involve the interaction of agents with a dynamically changing environment that serves as both an enabler and a modulator of behavior.

Perception of motion salience shapes the emergence of collective motions

“…The majority of swarm models integrated into robots commonly employ the position-based and averaging-type interactions to engender the observable phenomena of alignment, attraction, and repulsion 17 , 28 – 30 . Nevertheless, practical applications necessitate a higher degree of complexity and a broader range of group adaptability across diverse contexts, such as collective anti-predators 15 , collective turn 31 , cooperative transportation 32 or excavation 33 , collective chase or escape 34 – 36 , and more. Clearly, the progression of swarm robotics with the capacity to tackle various collective tasks is intricately linked to the elucidation of the fundamental mechanisms governing the different collective patterns, dynamics, and functionalities observed in natural animal flocks.…”

Perception of Motion Salience Shapes the Emergence of Collective Motions

“…Third , existing phenomenological or visual projection models haven’t facilitated the adoption of bio-inspired mechanisms for the applications of swarm robotics 21,22 . Indeed, most of the theoretical models prescribe the position-based and average interactions to yield simple alignment, attraction, and repulsion 23,24,25,26 , while real applications require more sophisticated and highly maneuverable behaviors, e.g., collective anti-predators 15 , collective turn 27 , cooperative transportation 28 or excavation 29 , collective chase or escape 30,31,32 , etc. Obviously, for accommodating different kinds of collective tasks, designing bio-inspired swarm robotics is inextricably linked to revealing the fundamental mechanisms underlying different motion patterns of collective behaviors from real flocks.…”