Sophisticated collective foraging with minimalist agents: a swarm robotics test

摘要

How groups of cooperative foragers can achieve efficient and robust collective foraging is ofinterest both to biologists studying social insects and engineers designing swarm robotics systems.Of particular interest are distance-quality trade-offs and swarm-size-dependent foragingstrategies. Here, we present a collective foraging system based on virtual pheromones, testedin simulation and in swarms of up to 200 physical robots. Our individual agent controllers arehighly simplified, as they are based on binary pheromone sensors. Despite being simple, ourindividual controllers are able to reproduce classical foraging experiments conducted withmore capable real ants that sense pheromone concentration and follow its gradient. One keyfeature of our controllers is a control parameter which balances the trade-off between distanceselectivity and quality selectivity of individual foragers. We construct an optimal foragingtheory 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 controllersagainst our optimality model and find that, for moderate swarm sizes, they can be parameterisedto approximate the optimal foraging strategy. This study demonstrates the sufficiencyof simple individual agent rules to generate sophisticated collective foraging behaviour.