A Hybrid Localization Algorithm for Wearable Safety Devices

Authors: O. Tovar, F. Sottile, E. Kallias, C. Pastrone


Occupational safety and health (OSH) in industrial environments is gathering increasing attention in the era of Industry4.0. In this context, location based services (LBS) can be adopted to support workers’ safety in hazardous industrial environments. However, the provision of accurate location service in these harsh environments still faces big challenges. To address these challenges, this paper presents a robust hybrid localization algorithm that combines ultra-wideband (UWB) based ranging measurements and inertial measurement unit (IMU) data. The algorithm has been implemented on a proprietary wearable platform and its performance has been evaluated in an indoor environment. The experimental results show that the proposed hybrid algorithm outperforms a non-hybrid, UWB-based, P osition V elocity (PV) extended Kalman filter (EKF), which has been chosen as benchmark, in terms of both location accuracy and availability. Thanks to a modular approach, the proposed solution also leads to a lower computation processing compared to other hybrid solutions.


O. Tovar, F. Sottile, E. Kallias, C. Pastrone, “A Hybrid Localization Algorithm for Wearable Safety Devices”, in 11th EAI International Conference on Body Area Networks – BodyNets 2016, Turin, Italy, 15-16 December 2016

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