Measurement and Control of Self-organised Behaviour in Robot Swarms

Today’s technical systems are becoming increasingly complex. Future systems will consist of a multitude of complex soft- and hardware components, which interact with each other to satisfy global system functional requirements. This trend bears the risk of more and more breakdowns and other unexpected behaviour. Organic Computing (OC) has the vision of addressing the challenges of complex distributed systems by making them more life-like (organic), i. e. endowing them with abilities such as self-organisation, self-configuration, self-repair, or adaptation. This can only be achieved by giving the system elements adequate degrees of freedom. This may result in an emergent behaviour, which can be positive as well as negative. Therefore, we need an observer/ controller architecture, which allows for self-organisation but at the same time enables adequate reactions to control the - sometimes completely unexpected - emerging global behaviour.
In this paper, we give an introduction to a generic observer/controller architecture, adapt this framework to a scenario of a self-organising robot swarm, and show how to control and prevent global, collective, unwanted behaviour based on observations of the local behaviour of the distributed agents.