一项使用仿生鱼机器人的新研究表明，鱼类成群游泳可以为它们提供水动力优势。

来源：康斯坦茨大学 （University of Konstanz） 翻译：廖璐

A fish school is a striking demonstration of synchronicity. Yet centuries of study have left a basic question unanswered: do fish save energy by swimming in schools? Now, scientists from the Max Planck Institute of Animal Behavior (MPI-AB), the University of Konstanz, and Peking University have provided an answer that has long been suspected but never conclusively supported by experiments: yes. 鱼类成群而行是同步性的惊人展示。然而，数百年来的研究仍未解决一个基本问题：鱼类成群游泳是否更省力？来自马克斯·普朗克动物行为研究所（MPI-AB），康斯坦茨大学和北京大学的科学家提供了一个长期以来存在质疑但从未得到实验最终验证的答案：是的。

Using biomimetic fish-like robots, the researchers show that fish could take advantage of the swirls of water generated by those in front by applying a simple behavioural rule. By adjusting their tail beat relative to near neighbours -- a strategy called vortex phase matching -- robots were shown to benefit hydrodynamically from a near neighbour no matter where they are positioned with respect to that neighbour. The previously unknown rule, revealed by the robots, was subsequently shown to be the strategy used by free swimming fish. The study is reported on 26 October 2020 in Nature Communications. 研究人员应用仿生鱼机器人，表明鱼可以通过应用简单的行为规则来充分利用前面的鱼所产生的水漩涡。通过调整相对于近邻鱼的尾巴节拍（一种称为涡旋相位匹配的策略），无论相对于近邻鱼的位置如何，机器人都可以从近邻获得流体动力。由机器人揭示的先前未知的规则随后被证明是自由游鱼使用的策略。该研究报告于2020年10月26日发表在《自然通讯》上。

"Fish schools are highly dynamic, social systems," says senior author Iain Couzin, Director of the MPI-AB who also co-directs the Cluster of Excellence 'Centre for the Advanced Study of Collective Behaviour' at the University of Konstanz. "Our results provide an explanation for how fish can profit from the vortices generated by near neighbours without having to keep fixed distances from each other." MPI-AB主任，资深作者Iain Couzin说：“鱼类成群而行是高度动态的社会系统。”他也是康斯坦茨大学卓越集群“集体行为高级研究中心”的负责人。“我们的结果为鱼类如何从近邻产生的涡流中获利而不必彼此保持固定距离提供了一种解释。”

Robotic solution 机器人解决方案

Answering the question of whether or not fish can save energy by swimming with others requires measuring their energy expenditure. Accurately doing so in free swimming fish has so far not been possible, and so past studies have sought to answer this question instead through theoretical models and predictions. 要回答鱼是否可以通过与其他鱼结群游泳来节省能量的问题，需要测量其能量消耗。到目前为止，在自由游泳的鱼中准确地做到这一点是不可能的，因此过去的研究试图通过理论模型和预测来回答这个问题。

The new study, however, has overcome this barrier to experimental testing. The researchers developed a 3D robotic fish that has a soft tail fin and swims with an undulating motion that mimics accurately the movement of a real fish. But unlike their live counterparts, the robots allow for direct measurement of the power consumption associated with swimming together versus alone. 但是，这项新研究克服了实验测试的这一障碍。研究人员开发了一种3D机器人鱼，它具有柔软的尾鳍，并以起伏的运动方式游泳，准确地模拟了真实鱼的运动。但是，与真鱼不同，这些机器人可以直接测量其群游或单游相关的能量消耗。

"We developed a biomimetic robot to solve the fundamental problem of finding out how much energy is used in swimming," says Liang Li, a postdoctoral fellow at the MPI-AB and first author on the study. "If we then have multiple robots interacting, we gain an efficient way to ask how different strategies of swimming together impact the costs of locomotion." MPI-AB的博士后研究员，这项研究的第一作者梁立（音译）说：“我们开发了一种仿生鱼机器人，以发现游泳中消耗多少能量的根本问题。”“倘若之后有多个鱼机器人进行交互，我们将获得一种有效的方式来询问不同的游泳策略如何共同影响运动成本。”

A simple rule for swimming in a school 成群游泳的一项简单规则

The researchers studied robotic fish swimming in pairs versus alone. Running over 10,000 trials, they tested follower fish in every possible position relative to leaders -- and then compared energy use with solo swimming. 研究人员研究了单游和成对游泳鱼机器人。他们进行了10,000多次试验，在相对于游在前方的鱼各个可能位置测试了游在其后的鱼类，然后将能量消耗与单独游泳进行了比较。

The results showed a clear difference in energy consumption for robots that swam alone versus those that swam in pairs. The cause of this, they discovered, is the way that fish in front influence the hydrodynamics of fish behind. The energy consumed by a follower fish is determined by two factors: its distance behind the leader and the relative timing of the tail beats of the follower with respect to that of the leader. In other words, it matters whether the follower fish is positioned close to the front or far behind the leader and how the follower adjusts its tail beats to exploit the vortices created by the leader. 结果表明，单独游泳的鱼机器人与成对游泳的机器人的能耗存在明显差异。他们发现，造成这种情况的原因是前排鱼类影响后排鱼类水动力的方式。 后排鱼消耗的能量取决于两个因素：后排鱼在前排鱼后面的距离及其摆动鱼尾与前排鱼摆动鱼尾的相对时间。换句话说，后排鱼是位于前排鱼附近还是落后很远，以及后排鱼如何调整其尾部摆动的节奏来利用前排鱼产生的涡旋动力都很重要。

To save energy, it turns out that the secret is in synchronisation. That is, follower fish must match their tail beat to that of the leader with a specific time lag based on the spatial position -- a strategy the researchers called "vortex phase matching." When followers are beside leader fish, the most energetically effective thing to do is to synchronise tail beats with the leader. But as followers fall behind, they should go out of synch having more and more lag as compared to the tail beat of the leader. 要想节省能量，事实证明秘诀在于同步性。 也就是说，游在后面的鱼必须基于空间位置在特定的时间差内使其尾部摆动节奏与游在前面鱼的尾部拍子相匹配-这种策略被研究人员称为“涡旋相位匹配”。当后面的鱼在前排鱼旁边时，最有效的省力方法是使尾部摆动节奏与前排鱼同步。但是，随着后排鱼渐渐落后，与前排鱼的尾巴摆动相比，其尾部摆动节奏逐渐失调，且滞后越来越多。

Visualising vortices 可视化漩涡

In order to visualise the hydrodynamics, researchers emitted tiny hydrogen bubbles into the water and imaged them with a laser -- a technique that made the vortices created by the swimming motion of the robots visible. This showed that vortices are shed by the leader fish and move downstream. It also showed that robots could utilise these vortices in various ways. "It's not just about saving energy. By changing the way they synchronise, followers can also use the vortices shed by other fish to generate thrust and help them accelerate," says co-author Mate Nagy, head of the Collective Behaviour 'Lendület' Research Group in the Hungarian Academy of Sciences and Eötvös University, who conducted the work when he was a postdoctoral fellow at the MPI-AB. 为了使流体动力学可视化，研究人员向水中喷出了微小的氢气泡，并用激光使其成像-该技术使得由机器人的游泳产生的涡流可视化。这表明旋涡被前排鱼驱散并向下游移动。它还表明，鱼机器人可以以各种方式利用这些涡流。共同作者Mate Nagy说：“这不只是节省能量。通过改变它们的同步方式，后排鱼还可以利用其他鱼类脱落的涡流来产生推力并帮助它们加速运动。”Mate 也是匈牙利科学院和Eötvös大学集体行为'Lendület' 研究小组负责人，做这项研究时，他还是MPI-AB的博士后研究员。

The result in real fish 真实鱼类情况

But do real fish use the strategy of vortex phase matching to save energy? To answer that, the researchers created a simple hydrodynamic model that predicts what real fish should do if they are using vortex phase matching. They used AI-assisted analysis of body posture of goldfish swimming together and found, indeed, that the strategy is being used in nature. 但是，真正的鱼类是否使用涡流相位匹配策略来节省能量？ 为了回答这个问题，研究人员创建了一个简单的流体动力学模型，该模型可以预测如果真鱼使用涡旋相位匹配该怎么做。 他们使用AI辅助分析了一起游动金鱼的身体姿势，并确实发现该策略已在自然界中使用。

Says Couzin: "We discovered a simple rule for synchronising with neighbours that allows followers to continuously exploit socially-generated vortices. But before our robotic experiments, we simply didn't know what to look for, and so this rule has been hidden in plain sight." Couzin说：“我们发现了一个与邻鱼同步的简单规则，该规则允许后方鱼不断利用社交产生的涡流。但是在进行机器人鱼实验之前，我们根本不知道要寻找什么，因此该规则在眼皮子底下被隐藏了。

Video: https://www.youtube.com/watch?v=J4T4hi8RO7s&feature=emb_logo

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