Honeybees are renowned for their perfectly hexagonal honeycomb, hailed as the pinnacle of biological architecture for its ability to maximize storage area while minimizing building material. However, in natural nests, workers must regularly transition between different cell sizes, merge inconsistent combs, and optimize construction in constrained geometries. These spatial obstacles pose challenges to workers building perfect hexagons, but it is unknown to what extent workers act as architects versus simple automatons during these irregular building scenarios. Using automated image analysis to extract the irregularities in natural comb building, we show that some building configurations are more difficult for the bees than others, and that workers overcome these challenges using a combination of building techniques, such as: intermediate-sized cells, regular motifs of irregular shapes, and gradual modifications of cell tilt. Remarkably, by anticipating these building challenges, workers achieve high-quality merges using limited local sensing, on par with analytical models that require global optimization. Unlike automatons building perfectly replicated hexagons, these building irregularities showcase the active role that workers take in shaping their nest and the true architectural abilities of honeybees.

蜜蜂以其完美的六边形蜂窝而闻名，因其能够最大限度地增加存储面积同时最大限度地减少建筑材料而被誉为生物建筑的巅峰之作。然而，在自然巢穴中，工人们必须定期在不同的单元格大小之间转换，合并不一致的梳子，并优化受限几何形状的构造。这些空间障碍对建造完美六边形的工人提出了挑战，但在这些不规则的建筑场景中，工人在多大程度上充当建筑师而不是简单的自动机尚不清楚。使用自动图像分析来提取自然梳子建筑中的不规则性，我们表明某些建筑配置对蜜蜂来说比其他建筑配置更困难，并且工人使用建筑技术的组合克服了这些挑战，例如：中等大小的细胞，不规则形状的规则图案，以及细胞倾斜的逐渐修改。值得注意的是，通过预测这些建筑挑战，工作人员使用有限的局部传感实现了高质量的合并，与需要全局优化的分析模型相当。与机器人建造完美复制的六边形不同，这些不规则的建筑展示了工人在塑造巢穴中所扮演的积极角色以及蜜蜂真正的建筑能力。