UWB Localization in a Smart Factory: Augmentation Methods and Experimental Assessment

Abstract

The advent of the fourth industrial revolution (Industry 4.0) aims at increasing automation and efficiency in manufacturing processes by the adoption of information and communication technologies. Several of the proposed solutions rely on precise localization of material, equipment, or operators. This article investigates the employment of ultrawideband (UWB) real-time location systems (RTLS) in a factory environment and proposes an augmentation technique to mitigate the impairments that arise in such a complex scenario. A Bayesian filtering method is developed to jointly track the motion dynamics and the time-varying visibility conditions of the UWB antennas, with particle-based implementation to deal with the nonlinearity of the UWB measurements. Laboratory tests and industrial experiments are carried out to evaluate the performance of three commercial off-the-shelf UWB technologies: Decawave, Sewio, and Ubisense. The experimental data are then used to calibrate and test the developed filtering technique, showing that it is possible to significantly reduce the positioning error originating from dense multipath and NLOS effects by jointly tracking the target dynamics and visibility conditions.