Department of Collective Behavior, Max Planck Institute for Ornithology, Konstanz, Germany.
Department of Biology, University of Konstanz, Konstanz, Germany.
Sci Adv. 2020 Feb 5;6(6):eaay0792. doi: 10.1126/sciadv.aay0792. eCollection 2020 Feb.
Classical models of collective behavior often take a "bird's-eye perspective," assuming that individuals have access to social information that is not directly available (e.g., the behavior of individuals outside of their field of view). Despite the explanatory success of those models, it is now thought that a better understanding needs to incorporate the perception of the individual, i.e., how internal and external information are acquired and processed. In particular, vision has appeared to be a central feature to gather external information and influence the collective organization of the group. Here, we show that a vision-based model of collective behavior is sufficient to generate organized collective behavior in the absence of spatial representation and collision. Our work suggests a different approach for the development of purely vision-based autonomous swarm robotic systems and formulates a mathematical framework for exploration of perception-based interactions and how they differ from physical ones.
经典的群体行为模型通常采用“鸟瞰视角”，假设个体可以获得无法直接获取的社会信息（例如，个体视野之外的行为）。尽管这些模型具有解释力，但现在认为需要更好地理解个体的感知，即内部和外部信息是如何获取和处理的。特别是，视觉似乎是获取外部信息并影响群体集体组织的核心特征。在这里，我们展示了一种基于视觉的群体行为模型，即使在没有空间表示和碰撞的情况下，也足以产生有组织的集体行为。我们的工作为开发纯基于视觉的自主群体机器人系统提供了一种不同的方法，并为探索基于感知的相互作用以及它们与物理相互作用的不同之处制定了一个数学框架。
