Digital and mechatronic methods, paired with artificial intelligence and machine learning, are transformative technologies in behavioral science and biology. The central element of the most important pollinator species—honey bees—is the colony’s queen. Because honey bee self-regulation is complex and studying queens in their natural colony context is difficult, the behavioral strategies of these organisms have not been widely studied. We created an autonomous robotic observation and behavioral analysis system aimed at continuous observation of the queen and her interactions with worker bees and comb cells, generating behavioral datasets of exceptional length and quality. Key behavioral metrics of the queen and her social embedding within the colony were gathered using our robotic system. Data were collected continuously for 24 hours a day over a period of 30 days, demonstrating our system’s capability to extract key behavioral metrics at microscopic, mesoscopic, and macroscopic system levels. Additionally, interactions among the queen, worker bees, and brood were observed and quantified. Long-term continuous observations performed by the robot yielded large amounts of high-definition video data that are beyond the observation capabilities of humans or stationary cameras. Our robotic system can enable a deeper understanding of the innermost mechanisms of honey bees’ swarm-intelligent self-regulation. Moreover, it offers the possibility to study other social insect colonies, biocoenoses, and ecosystems in an automated manner. Social insects are keystone species in all terrestrial ecosystems; thus, developing a better understanding of their behaviors will be invaluable for the protection and even the restoration of our fragile ecosystems globally.

中文翻译：

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通过协作机器人长期自主跟踪蜜蜂的行为


数字和机电一体化方法与人工智能和机器学习相结合，是行为科学和生物学领域的变革性技术。最重要的传粉媒介物种——蜜蜂——的核心元素是蜂群的蜂王。由于蜜蜂的自我调节很复杂，而且很难在自然蜂群环境中研究蜂王，因此这些生物的行为策略尚未得到广泛研究。我们创建了一个自主机器人观察和行为分析系统，旨在连续观察蜂王及其与工蜂和梳状细胞的互动，生成具有特殊长度和质量的行为数据集。蜂王及其在蜂群中的社会嵌入的关键行为指标是使用我们的机器人系统收集的。在 30 天内每天 24 小时连续收集数据，证明了我们的系统能够在微观、中观和宏观系统级别提取关键行为指标。此外，还观察并量化了蜂王、工蜂和育雏之间的相互作用。机器人进行的长期连续观察产生了大量高清视频数据，这些数据超出了人类或固定摄像机的观察能力。我们的机器人系统可以更深入地了解蜜蜂群体智能自我调节的最内在机制。此外，它还提供了以自动化方式研究其他社会性昆虫群落、生物群落和生态系统的可能性。群居昆虫是所有陆地生态系统中的关键物种;因此，更好地了解它们的行为对于保护甚至恢复我们全球脆弱的生态系统将非常宝贵。