Human–swarm interaction is a frontier in the realms of swarm robotics and human-factors engineering. However, no holistic theory has been explicitly formulated that can inform how humans and robot swarms should interact through an interface while considering real-world demands, the relative capabilities of the components, as well as the desired joint-system behaviours. In this article, we apply a holistic perspective that we refer to as joint human–swarm loops, that is, a cybernetic system made of human, swarm and interface. We argue that a solution for human–swarm interaction should make the joint human–swarm loop an intelligent system that balances between centralized and decentralized control. The swarm-amplified human is suggested as a possible design that combines perspectives from swarm robotics, human-factors engineering and theoretical neuroscience to produce such a joint human–swarm loop. Essentially, it states that the robot swarm should be integrated into the human’s low-level nervous system function. This requires modelling both the robot swarm and the biological nervous system as self-organizing systems. We discuss multiple design implications that follow from the swarm-amplified human, including a computational experiment that shows how the robot swarm itself can be a self-organizing interface based on minimal computational logic.

人-群交互是群机器人和人因工程领域的前沿。然而，还没有明确制定出整体理论可以告知人类和机器人群应该如何通过界面进行交互，同时考虑现实世界的需求、组件的相对能力以及所需的关节系统行为。在本文中，我们应用了一个整体视角，我们称之为联合人-群循环，即由人、群和界面组成的控制论系统。我们认为，人-群交互的解决方案应该使联合人-群循环成为一个在集中控制和分散控制之间取得平衡的智能系统。建议将群体放大的人类作为一种可能的设计，结合群体机器人技术的观点，人因工程和理论神经科学来产生这样一个联合的人 - 群循环。从本质上讲，它指出机器人群应该集成到人类的低级神经系统功能中。这需要将机器人群和生物神经系统建模为自组织系统。我们讨论了群体放大后的人类的多种设计含义，包括一个计算实验，该实验展示了机器人群体本身如何成为基于最小计算逻辑的自组织界面。