Department of Mathematics and Computer Science, Free University Berlin, Berlin, Germany.
PLoS One. 2011;6(8):e21354. doi: 10.1371/journal.pone.0021354. Epub 2011 Aug 3.
The honeybee dance "language" is one of the most popular examples of information transfer in the animal world. Today, more than 60 years after its discovery it still remains unknown how follower bees decode the information contained in the dance. In order to build a robotic honeybee that allows a deeper investigation of the communication process we have recorded hundreds of videos of waggle dances. In this paper we analyze the statistics of visually captured high-precision dance trajectories of European honeybees (Apis mellifera carnica). The trajectories were produced using a novel automatic tracking system and represent the most detailed honeybee dance motion information available. Although honeybee dances seem very variable, some properties turned out to be invariant. We use these properties as a minimal set of parameters that enables us to model the honeybee dance motion. We provide a detailed statistical description of various dance properties that have not been characterized before and discuss the role of particular dance components in the commmunication process.
蜜蜂的舞蹈“语言”是动物界中最受欢迎的信息传递方式之一。自 60 多年前发现以来，至今仍不清楚跟随蜜蜂如何解码舞蹈中包含的信息。为了制造出一种能够更深入地研究蜜蜂的通讯过程的机器人蜜蜂，我们已经录制了数百个摇摆舞的视频。在本文中，我们分析了欧洲蜜蜂（Apis mellifera carnica）摇摆舞的高精准度视觉捕捉轨迹的统计数据。这些轨迹是使用一种新的自动跟踪系统产生的，代表了目前最详细的蜜蜂舞蹈运动信息。尽管蜜蜂的舞蹈看起来非常多变，但有些特性却不变。我们将这些特性用作最小的参数集，使我们能够对蜜蜂舞蹈动作进行建模。我们提供了对各种以前未被描述的舞蹈特性的详细统计描述，并讨论了特定舞蹈成分在通讯过程中的作用。
