用小规模机器人子集实现高效群体决策，节省资源。
SubCDM: Collective Decision-Making with a Swarm Subset
- 仅用部分机器人参与决策，基于局部信息动态组建子集。
- 百台机器人仿真中，准确率接近全群决策，但所需机器人更少。
- 适合需要节能、灵活分配任务的群体机器人系统。
群体决策是自主机器人集群的关键功能，使其能根据环境特征达成行动共识。现有方法要求所有机器人参与决策，耗能高且无法兼顾其他任务。本文提出基于子集的群体决策（SubCDM），仅需使用集群子集即可完成决策。子集构建动态且去中心化，仅依赖本地信息。该方法可自适应调整子集规模，以应对共识难易程度的变化。在一百台机器人的仿真中，该方案达到与全群决策相当的准确率，同时显著减少参与决策的机器人数量，为集群机器人中的群体决策提供了资源高效的解决方案。
原文摘要 · Abstract (English)
Collective decision-making is a key function of autonomous robot swarms, enabling them to reach a consensus on actions based on environmental features. Existing strategies require the participation of all robots in the decision-making process, which is resource-intensive and prevents the swarm from allocating the robots to any other tasks. We propose Subset-Based Collective Decision-Making (SubCDM), which enables decisions using only a swarm subset. The construction of the subset is dynamic and decentralized, relying solely on local information. Our method allows the swarm to adaptively determine the size of the subset for accurate decision-making, depending on the difficulty of reaching a consensus. Simulation results using one hundred robots show that our approach achieves accuracy comparable to using the entire swarm while reducing the number of robots required to perform collective decision-making, making it a resource-efficient solution for collective decision-making in swarm robotics.
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