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The Fourth Industrial Revolution, or Industry 4.0, aims at automating traditional manufacturing and industrial practices using modern smart technology. Autonomous mobile robots equipped with different sensors and employing different techniques have been proposed in the literature in the logistics and inventory warehouse management contexts. Efficient robot motion and planning depend on precise localization, mapping, and awareness of the environment. To properly localize items, recent attempts have been made employing radio frequency identification (RFID) in a 3D environment. This manuscript introduces four least mean squares methods to estimate the 3D positions of tags employing synthetic apertures and phase unwrapping. The proposed methods approach the localization problem solving a system of equations typical of multilateration methods to find the intersections of multiple hyperboloids. The novelty introduced here is the use of unwrapped phase distances to compute pseudo ranges for the multilateration problem. The use of such a technique is feasible thanks to precise mobile robot localization and custom navigation policies. All the analyzed methods are suitable for online localization due to reduced computation timings and have been tested on three different datasets. Two of them contain virtual data that has been generated by simulation, while the other one comes from an indoor experimental setup. Simulated tests show that combined antenna motions in 3D space (including  Z -axis) improve the localization obtaining errors under the centimeter for 3D localization. Experimental tests obtained results as low as 13 cm of mean accuracy for 3D localization and 0.21 cm for 2D localization.

Efficient localization in warehouse logistics: a comparison of LMS approaches for 3D multilateration of passive UHF RFID tags