PEARL-TVF: Persistently-Excited Adaptive Relative Localization and Time-Varying Formation of Robot Swarms

In this paper we investigate the problem of controlling a multi-robot team to follow a leader in formation without relying on external localization system. The main challenge of the problem, which is to simultaneously fulfill both relative localization and control tasks, is efficiently and novelly resolved by embedding a distance-displacement-based persistently excited adaptive relative localization technique into a time-varying formation with bounded control input (PEARL-TVF). By assuming that the leader is globally reachable and selecting proper parameters, it is shown that PEARL-TVF ensures exponentially convergent relative localization and formation errors when the leader’s behavior is deterministic, and bounded formation error for a non-deterministic leader.

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