Collignon Bertrand, Séguret Axel, Halloy José
Université Paris Diderot , Sorbonne Paris Cité, LIED, UMR 8236, 75013 Paris, France.
R Soc Open Sci. 2016 Jan 13;3(1):150473. doi: 10.1098/rsos.150473. eCollection 2016 Jan.
Collective motion is one of the most ubiquitous behaviours displayed by social organisms and has led to the development of numerous models. Recent advances in the understanding of sensory system and information processing by animals impels one to revise classical assumptions made in decisional algorithms. In this context, we present a model describing the three-dimensional visual sensory system of fish that adjust their trajectory according to their perception field. Furthermore, we introduce a stochastic process based on a probability distribution function to move in targeted directions rather than on a summation of influential vectors as is classically assumed by most models. In parallel, we present experimental results of zebrafish (alone or in group of 10) swimming in both homogeneous and heterogeneous environments. We use these experimental data to set the parameter values of our model and show that this perception-based approach can simulate the collective motion of species showing cohesive behaviour in heterogeneous environments. Finally, we discuss the advances of this multilayer model and its possible outcomes in biological, physical and robotic sciences.
集体运动是社会有机体表现出的最普遍的行为之一，并促使众多模型的发展。动物在感觉系统和信息处理方面的最新进展促使人们修正决策算法中的经典假设。在此背景下，我们提出了一个描述鱼类三维视觉感觉系统的模型，该系统根据其感知场调整轨迹。此外，我们引入了一个基于概率分布函数的随机过程，以便在目标方向上移动，而不是像大多数经典模型那样基于影响向量的总和。同时，我们展示了斑马鱼（单独或10条一组）在均匀和异质环境中游泳的实验结果。我们利用这些实验数据来设置模型的参数值，并表明这种基于感知的方法可以模拟在异质环境中表现出凝聚行为的物种的集体运动。最后，我们讨论了这个多层模型的进展及其在生物学、物理学和机器人科学中可能产生的结果。
