Swarm Intelligence (SI) is a popular multi-agent framework that has been originally inspired by swarm behaviors observed in natural systems, such as ant and bee colonies. In a system designed after swarm intelligence, each agent acts autonomously, reacts on dynamic inputs, and, implicitly or explicitly, works collaboratively with other swarm members without a central control. The system as a whole is expected to exhibit global patterns and behaviors. Although well-designed swarms can show advantages in adaptability, robustness, and scalability, it must be noted that SI system have not really found their way from lab demonstrations to real-world applications, so far. This is particularly true for embodied SI, where the agents are physical entities, such as in swarm robotics scenarios. In this paper, we start from these observations, outline different definitions and characterizations, and then discuss present challenges in the perspective of future use of swarm intelligence. These include application ideas, research topics, and new sources of inspiration from biology, physics, and human cognition. To motivate future applications of swarms, we make use of the notion of cyber-physical systems (CPS). CPSs are a way to encompass the large spectrum of technologies including robotics, internet of things (IoT), Systems on Chip (SoC), embedded systems, and so on. Thereby, we give concrete examples for visionary applications and their challenges representing the physical embodiment of swarm intelligence in autonomous driving and smart traffic, emergency response, environmental monitoring, electric energy grids, space missions, medical applications, and human networks. We do not aim to provide new solutions for the swarm intelligence or CPS community, but rather build a bridge between these two communities. This allows us to view the research problems of swarm intelligence from a broader perspective and motivate future research activities in modeling, design, validation/verification, and human-in-the-loop concepts.

群智能（SI）是一种流行的多主体框架，最初是受自然系统中观察到的群行为（例如蚂蚁和蜂群）启发的。在群体智能设计的系统中，每个特工都自主行动，对动态输入做出反应，并在没有中央控制的情况下与其他群体成员隐式或显式地协同工作。整个系统有望展现出全局的模式和行为。尽管设计良好的集群可以在适应性，鲁棒性和可伸缩性方面显示出优势，但必须指出的是，到目前为止，SI系统尚未真正找到从实验室演示到实际应用的道路。这对于包含代理是物理实体的嵌入式SI尤其如此，例如在群体机器人场景中。在本文中，我们将从这些观察开始，概述不同的定义和特征，然后从未来使用群智能的角度讨论当前的挑战。其中包括应用思想，研究主题，以及来自生物学，物理学和人类认知的新灵感来源。为了激发群体的未来应用，我们利用了网络物理系统（CPS）的概念。CPS是一种涵盖众多技术的方式，包括机器人技术，物联网（IoT），片上系统（SoC），嵌入式系统等。因此，我们为有远见的应用及其挑战提供了具体的例子，这些挑战代表着群体智能在自动驾驶和智能交通，应急响应，环境监测，电力网格，太空任务，医疗应用和人为网络中的物理体现。我们的目标不是为群体情报或CPS社区提供新的解决方案，而是在这两个社区之间架起一座桥梁。这使我们能够从更广阔的角度观察群体智能的研究问题，并激发未来在建模，设计，验证/验证和人在环环相扣概念方面的研究活动。