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      UWB Localization with Battery-Powered Wireless Backbone for Drone-Based Inventory Management

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          Abstract

          Current inventory-taking methods (counting stocks and checking correct placements) in large vertical warehouses are mostly manual, resulting in (i) large personnel costs, (ii) human errors and (iii) incidents due to working at large heights. To remedy this, the use of autonomous indoor drones has been proposed. However, these drones require accurate localization solutions that are easy to (temporarily) install at low costs in large warehouses. To this end, we designed a Ultra-Wideband (UWB) solution that uses infrastructure anchor nodes that do not require any wired backbone and can be battery powered. The resulting system has a theoretical update rate of up to 2892 Hz (assuming no hardware dependent delays). Moreover, the anchor nodes have an average current consumption of only 27 mA (compared to 130 mA of traditional UWB infrastructure nodes). Finally, the system has been experimentally validated and is available as open-source software.

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          Most cited references35

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          Real-Time Noncoherent UWB Positioning Radar With Millimeter Range Accuracy: Theory and Experiment

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            Experimental Evaluation of UWB Indoor Positioning for Sport Postures

            Radio frequency (RF)-based indoor positioning systems (IPSs) use wireless technologies (including Wi-Fi, Zigbee, Bluetooth, and ultra-wide band (UWB)) to estimate the location of persons in areas where no Global Positioning System (GPS) reception is available, for example in indoor stadiums or sports halls. Of the above-mentioned forms of radio frequency (RF) technology, UWB is considered one of the most accurate approaches because it can provide positioning estimates with centimeter-level accuracy. However, it is not yet known whether UWB can also offer such accurate position estimates during strenuous dynamic activities in which moves are characterized by fast changes in direction and velocity. To answer this question, this paper investigates the capabilities of UWB indoor localization systems for tracking athletes during their complex (and most of the time unpredictable) movements. To this end, we analyze the impact of on-body tag placement locations and human movement patterns on localization accuracy and communication reliability. Moreover, two localization algorithms (particle filter and Kalman filter) with different optimizations (bias removal, non-line-of-sight (NLoS) detection, and path determination) are implemented. It is shown that although the optimal choice of optimization depends on the type of movement patterns, some of the improvements can reduce the localization error by up to 31%. Overall, depending on the selected optimization and on-body tag placement, our algorithms show good results in terms of positioning accuracy, with average errors in position estimates of 20 cm. This makes UWB a suitable approach for tracking dynamic athletic activities.
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              The Constrained Application Protocol (CoAP)

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                23 January 2019
                February 2019
                : 19
                : 3
                : 467
                Affiliations
                IMEC, IDLab, Department of Information Technology, Ghent University, 9000 Ghent, Belgium; jan.bauwens2@ 123456ugent.be (J.B.); bart.jooris@ 123456ugent.be (B.J.); ben.vanherbruggen@ 123456ugent.be (B.V.H.); jen.rossey@ 123456ugent.be (J.R.); jeroen.hoebeke@ 123456ugent.be (J.H.)
                Author notes
                Author information
                https://orcid.org/0000-0003-2066-1570
                https://orcid.org/0000-0002-0043-8788
                https://orcid.org/0000-0003-2039-007X
                https://orcid.org/0000-0002-0214-5751
                Article
                sensors-19-00467
                10.3390/s19030467
                6386853
                30678128
                e6f5a3ef-c2f0-4e11-b082-5ffa422a789d
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 29 December 2018
                : 21 January 2019
                Categories
                Article

                Biomedical engineering
                ultra-wideband (uwb),drone inventory,low-energy,easy installation,infrastructure-light

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