Reliable Range-Based Relative Localization Under Interval Excitation

Reliable relative localization using only onboard sensing is challenging for multi-robot systems operating in GPS-denied environments, particularly when robots exhibit limited mutual motion, under which the available measurements cannot provide persistently excited regression signals.To address this challenge, this letter proposes an adaptive online relative localization method that enables accurate relative-position estimation using only onboard measurements under a mild interval excitation (IE) condition. By introducing two dynamic auxiliary variables, the relative localization problem is reformulated as an online parameter estimation framework, which guarantees globally exponential convergence without persistent excitation (PE). Furthermore, an explicit lower bound on the estimation gain is provided in terms of the strength and duration of the interval excitation induced by the robots’ relative motion. Finally, simulations and physical experiments demonstrate that the proposed method achieves reliable localization performance under both interval and persistently excited motions.