Bi-stability in cooperative transport by ants in the presence of obstacles

Abstract

To cooperatively carry large food items to the nest, individual ants conform their efforts and coordinate their motion. Throughout this expedition, collective motion is driven both by internal interactions between the carrying ants and a response to newly arrived informed ants that orient the cargo towards the nest. During the transport process, the carrying group must overcome obstacles that block their path to the nest. Here, we investigate the dynamics of cooperative transport, when the motion of the ants is frustrated by a linear obstacle that obstructs the motion of the cargo. The obstacle contains a narrow opening that serves as the only available passage to the nest, and through which single ants can pass but not with the cargo. We provide an analytical model for the ant-cargo system in the constrained environment that predicts a bi-stable dynamic behavior between an oscillatory mode of motion along the obstacle and a convergent mode of motion near the opening. Using both experiments and simulations, we show how for small cargo sizes, the system exhibits spontaneous transitions between these two modes of motion due to fluctuations in the applied force on the cargo. The bi-stability provides two possible problem solving strategies for overcoming the obstacle, either by attempting to pass through the opening, or take large excursions to circumvent the obstacle.

Micro/Nano Motor Navigation and Localization via Deep Reinforcement Learning

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Ant collective cognition allows for efficient navigation through disordered environments

“…It was previously shown for ants ( Ron et al, 2018 ; Gelblum et al, 2016 ) (and other animal groups Tunstrøm et al, 2013 ; Buhl et al, 2006 ) that physical interaction with a trap can induce change in the collective characteristics of motion. This responsiveness does not require any individual to be explicitly aware of the trap and can therefore be perceived as implicit, emergent trap detection.…”

Scale-Free Dynamics in Animal Groups and Brain Networks

“…Here, we discussed coordination or synchronization in animal groups in the context of emerging of directional order (or onset of collective motion) (Vicsek and Zafeiris, 2012 ) and condensation or clustering transitions (Chen et al, 2012 ; Calvao and Brigatti, 2019 ). Modeling work reflects this wide variety in collective behavior, which have been linked to different types of phase transitions, mainly of the discontinuous type [first order transitions, including hysteresis and metastability; e.g., Couzin et al ( 2002 ), Chate et al ( 2008 ), Hein et al ( 2015 ), and Calvao and Brigatti ( 2019 )] or the continuous type [second order, in line with criticality; e.g., Barberis and Albano ( 2014 ), Calovi et al ( 2015 ), Feinerman et al ( 2018 )], or both (Huepe et al, 2011 ). Even within one model, the type of phase transition encountered can be sensitive to the specific model parameters and simulations conducted.…”

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