Network Science and Automation

From distributed sensing to autonomous vehicles, networks are a crucial component of almost all our automated systems. Indeed, automation requires a coordinated functionality among different, self-driven, autonomous units. For example, robots that must mobilize in unison, vehicles or drones that must safely share space with each other, and, of course, complex infrastructure networks, such as the Internet, which require cooperative dynamics among its millions of interdependent routers. At the heart of such multi-component coordination lies a complex network, capturing the patterns of interaction between its constituting autonomous nodes. This network allows the different units to exchange information, influence each other’s functionality, and, ultimately, achieve globally synchronous behavior. Here, we lay out the mathematical foundations for such emergent large-scale network-based cooperation. First, analyzing the structural patterns of networks in automation, and then showing how these patterns contribute to the system’s resilient and coordinated functionality. With this toolbox at hand, we discuss common applications, from cyber-resilience to sensor networks and coordinated robotic motion.