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Forklift Tracking: Industry 4.0 Implementation in Large-Scale Warehouses through UWB Sensor Fusion

Andrea Motroni, Alice Buffi, Paolo Nepa

2021Applied Sciences33 citationsDOIOpen Access PDF

Abstract

This article addresses the problem of determining the location of pallets carried by forklifts inside a warehouse, which are recognized thanks to an onboard Radio Frequency IDentification (RFID) system at the ultra-high-frequency (UHF) band. By reconstructing the forklift trajectory and orientation, the location of the pallets can be associated with the forklift position at the time of unloading events. The localization task is accomplished by means of an easy-to-deploy combination of onboard sensors, i.e., an inertial measurement unit (IMU) and an optical flow sensor (OFS), with a commercial ultra-wideband (UWB) system through an Unscented Kalman Filter (UKF) algorithm, which estimates the forklift pose over time. The proposed sensor fusion approach contributes to the localization error mitigation by preventing drifts in the trajectory reconstruction. The designed methos was at first evaluated by means of a simulation framework and then through an experimental analysis conducted in a large warehouse with a size of about 4000 m2.

Topics & Concepts

PalletInertial measurement unitComputer scienceUltra high frequencyReal-time computingKalman filterFrame (networking)Sensor fusionTrajectoryEngineeringComputer visionArtificial intelligenceTelecommunicationsMechanical engineeringAstronomyPhysicsIndoor and Outdoor Localization TechnologiesRobotics and Sensor-Based LocalizationRFID technology advancements
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