In this article, we investigate the problem of controlling a multirobot team to follow a leader in formation, supported by a relative position estimate derived from distance and self-displacement measurements, thus waiving the need of external localization infrastructure. 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 by selecting proper parameters, it is shown that the PEARL-TVF ensures exponentially convergent localization, which leads to exponentially convergent formation when the leader's behavior is deterministic, and bounded formation error for a nondeterministic leader. Numerical simulations and experiments on quadcopters are provided to verify the theoretical findings.

中文翻译：

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机器人群的持续激励自适应相对定位和时变形成

在本文中，我们研究了控制多机器人团队跟随编队中的领导者的问题，由距离和自位移测量得出的相对位置估计支持，从而免除对外部定位基础设施的需求。该问题的主要挑战是同时完成相对定位和控制任务，通过将基于距离位移的持续激励自适应相对定位技术嵌入到具有有界控制输入的时变编队（PEARL）中，可以有效而新颖地解决-TVF）。通过假设领导者是全局可达的并通过选择适当的参数，表明 PEARL-TVF 确保指数收敛的本地化，当领导者' s 的行为是确定性的，并且对于非确定性领导者来说是有界的编队误差。提供了四轴飞行器的数值模拟和实验来验证理论发现。