Probabilistic Analysis of Long-Term Swarm Performance under Spatial Interferences

Swarm robotics is a branch of collective robotics that outperforms many other systems due to its large number of robots. It allows for performing several tasks that are beyond the capability of a single or multi robot systems. Its global behaviour emerges from the local rules implemented on the level of its individual robots. Thus, estimating the obtained performance in a self-organized manner represents one of the main challenges, especially under complex dynamics like spatial interferences. In this paper, we exploit the central limit theorem (CLT) to analyse and estimate the swarm performance over long-term deadlines and under potential spatial interferences. The developed model is tested on the well-known foraging task, however, it can be generalized to be applied on any constrictive robotic task.