階層構造がロボット群のスケーラビリティを決める
Hierarchies define the scalability of robot swarms
平等型と階層型のロボット群を比較し、階層型が広大で複雑な環境での放射線除去タスクにおいて少ない資源で効率的に適応できることをシミュレーションと実機実験で示した。
著者: Vivek Shankar Varadharajan, Karthik Soma, Sepand Dyanatkar, Pierre-Yves Lajoie, Giovanni Beltrame
分類: cs.RO
原文アブストラクト
The emerging behaviors of swarms have fascinated scientists and gathered significant interest in the field of robotics. Traditionally, swarms are viewed as egalitarian, with robots sharing identical roles and capabilities. However, recent findings highlight the importance of hierarchy for deploying robot swarms more effectively in diverse scenarios. Despite nature's preference for hierarchies, the robotics field has clung to the egalitarian model, partly due to a lack of empirical evidence for the conditions favoring hierarchies. Our research demonstrates that while egalitarian swarms excel in environments proportionate to their collective sensing abilities, they struggle in larger or more complex settings. Hierarchical swarms, conversely, extend their sensing reach efficiently, proving successful in larger, more unstructured environments with fewer resources. We validated these concepts through simulations and physical robot experiments, using a complex radiation cleanup task. This study paves the way for developing adaptable, hierarchical swarm systems applicable in areas like planetary exploration and autonomous vehicles. Moreover, these insights could deepen our understanding of hierarchical structures in biological organisms.
