用机器人集群追踪人员位置，实现动态环境持续监控。
Collective perception for tracking people with a robot swarm
- 利用集群中每个机器人的感知能力，形成集体环境认知。
- 在四种办公室环境中，不同规模集群均能快速检测并传播人员位置变化。
- 适合需要连续监控的动态场景，如智能安防或协同作业。
群体感知指机器人集群利用个体机器人的感知能力，形成对环境的集体认知。其分布式特性使集群能在空间中持续存在，从而持续监控动态环境。本研究在模拟环境中开展初步实验，使用不同规模的机器人集群追踪人员。实验覆盖四个真实办公环境，机器人图像来自真实办公场景数据集。测量了机器人发现人员位置变化并将其信息传播给集群更大比例成员所需的时间分布。结果表明，机器人集群在监控动态环境方面展现出显著潜力。
原文摘要 · Abstract (English)
Swarm perception refers to the ability of a robot swarm to utilize the perception capabilities of each individual robot, forming a collective understanding of the environment. Their distributed nature enables robot swarms to continuously monitor dynamic environments by maintaining a constant presence throughout the space.In this study, we present a preliminary experiment on the collective tracking of people using a robot swarm. The experiment was conducted in simulation across four different office environments, with swarms of varying sizes. The robots were provided with images sampled from a dataset of real-world office environment pictures.We measured the time distribution required for a robot to detect a person changing location and to propagate this information to increasing fractions of the swarm. The results indicate that robot swarms show significant promise in monitoring dynamic environments.
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