Sophisticated collective foraging with minimalist agents: a swarm robotics test

Abstract

How groups of cooperative foragers can achieve efficient and robust collective foraging is of interest both to biologists studying social insects and engineers designing swarm robotics systems. Of particular interest are distance-quality trade-offs and swarm-size-dependent foraging strategies. Here, we present a collective foraging system based on virtual pheromones, tested in simulation and in swarms of up to 200 physical robots. Our individual agent controllers are highly simplified, as they are based on binary pheromone sensors. Despite being simple, our individual controllers are able to reproduce classical foraging experiments conducted with more capable real ants that sense pheromone concentration and follow its gradient. One key feature of our controllers is a control parameter which balances the trade-off between distance selectivity and quality selectivity of individual foragers. We construct an optimal foraging theory model that accounts for distance and quality of resources, as well as overcrowding, and predicts a swarm-size-dependent strategy. We test swarms implementing our controllers against our optimality model and find that, for moderate swarm sizes, they can be parameterised to approximate the optimal foraging strategy. This study demonstrates the sufficiency of simple individual agent rules to generate sophisticated collective foraging behaviour.

Coherent collective behaviour emerging from decentralised balancing of social feedback and noise

“…To put this relationship into focus, we assume the agent not to be able to cancel noise but only to adapt its social feedback. The advantages of modulating the social feedback have been previously investigated in systems of collective motion (Torney et al 2009;Shklarsh et al 2011;Khaluf et al 2018), foraging (Pagliara et al 2018;Pitonakova et al 2018;Talamali et al 2019a;Rausch et al 2019), and collective decision-making (Talamali et al 2019b).…”

Augmented Reality for Robotics: A Review

“…During the study ARK platform also known as AR for Kilobots was used as the main simulation framework. The study on the collective foraging behavior continued [122], where behaviors of around 200 Kilobots having access to the sensing data from the virtual sensors and actuators were studied. ARGoS framework was used as the main experimental platform.…”

Swarm Foraging Review: Closing the Gap Between Proof and Practice

“…Three major approaches have been used to emulate ant pheromones: beacon robots [74][75][76], physical materials [77][78][79], and virtual pheromone [42,49,60,61,80]. Virtual pheromones may be implemented with augmented reality: Kilobots are capable of light stigmergy [12,49] as are epucks [61]. Arvin et al [60] implemented a series of low-cost robots capable of following light pheromones.…”

“…Isaacs et al performed experiments with a Gazebo [82] simulation developed for the Swarmathon [4]. Talimali et al [12] and in follow up work Llenas et al [44] used ARK [49] and ARGoS in a study informed by optimal foraging theory to show that congestion as a product of swarm size determines when swarms benefit from switching to alternate, lower quality, target clusters.…”

“…Foundational papers were selected by tracing references in recent work back to the first relevant ancestral publication (e.g., Baeza-Yates [8]) and frequently cited papers from that period (e.g., Brooks [9]), or papers that were representative of a highly cited author or research group (e.g., Deneubourg et al [10]). See Efremov and Kholod [11] and Talamali et al [12] for alternative points of view on recent foraging research.…”