Understanding the emergence of collective behaviour has long been a key research focus in the natural sciences. Besides the fundamental role of social interaction rules, a combination of theoretical and empirical work indicates individual speed may be a key process that drives the collective behaviour of animal groups. Socially induced changes in speed by interacting animals make it difficult to isolate the effects of individual speed on group-level behaviours. Here, we tackled this issue by pairing guppies with a biomimetic robot. We used a closed-loop tracking and feedback system to let a robotic fish naturally interact with a live partner in real time, and programmed it to strongly copy and follow its partner's movements while lacking any preferred movement speed or directionality of its own. We show that individual differences in guppies' movement speed were highly repeatable and in turn shaped key collective patterns: a higher individual speed resulted in stronger leadership, lower cohesion, higher alignment and better temporal coordination of the pairs. By combining the strengths of individual-based models and observational work with state-of-the-art robotics, we provide novel evidence that individual speed is a key, fundamental process in the emergence of collective behaviour.

理解集体行为的出现长期以来一直是自然科学的一个关键研究重点。除了社会互动规则的基本作用外，理论和实证工作的结合表明，个体速度可能是驱动动物群体集体行为的关键过程。通过互动的动物在社会上引起的速度变化使得很难隔离个体速度对群体水平行为的影响。在这里，我们通过将孔雀鱼与仿生机器人配对来解决这个问题。我们使用闭环跟踪和反馈系统让机器鱼自然地与实时伙伴进行实时交互，并对其进行编程以强烈复制和跟随其伙伴的动作，同时缺乏任何首选的移动速度或方向性。我们表明，孔雀鱼运动速度的个体差异是高度可重复的，进而塑造了关键的集体模式：更高的个体速度导致更强的领导力、更低的凝聚力、更高的一致性和更好的时间协调性。通过将基于个体的模型和观察工作的优势与最先进的机器人技术相结合，我们提供了新的证据，证明个体速度是集体行为出现的关键、基本过程。