无需复杂通信，机器人仅靠视线即可自动聚成紧凑集群。
A Minimalist Controller for Autonomously Self-Aggregating Robotic Swarms: Enabling Compact Formations in Multitasking Scenarios
- 仅用视线传感器实现多任务自聚合，无需中心控制。
- 在不同集群规模下均形成紧凑结构，聚类率与已有研究相当。
- 适合资源受限的多机器人协同场景，如搜救、勘探。
群体机器人中简单涌现行为的部署已有广泛研究。近期研究展示了多任务环境下自聚合的可行性——多个自聚合任务在同一环境中并发进行。然而，多任务自聚合面临新挑战：各集群动态相互影响。目前的方法要么生成非紧凑的圆形结构，要么缺乏完全自主性。本文提出一种多任务自聚合方法，使同质机器人仅依赖视线传感器即能自发形成不同紧凑集群。该方法在多种集群数量和每组机器人数量的仿真配置下表现出良好可扩展性，显著提升集群紧凑度，同时保持与其他研究相当的聚类比例。
原文摘要 · Abstract (English)
The deployment of simple emergent behaviors in swarm robotics has been well-rehearsed in the literature. A recent study has shown how self-aggregation is possible in a multitask approach -- where multiple self-aggregation task instances occur concurrently in the same environment. The multitask approach poses new challenges, in special, how the dynamic of each group impacts the performance of others. So far, the multitask self-aggregation of groups of robots suffers from generating a circular formation -- that is not fully compact -- or is not fully autonomous. In this paper, we present a multitask self-aggregation where groups of homogeneous robots sort themselves into different compact clusters, relying solely on a line-of-sight sensor. Our multitask self-aggregation behavior was able to scale well and achieve a compact formation. We report scalability results from a series of simulation trials with different configurations in the number of groups and the number of robots per group. We were able to improve the multitask self-aggregation behavior performance in terms of the compactness of the clusters, keeping the proportion of clustered robots found in other studies.
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