Research Article
A Hybrid Localization Algorithm for Wearable Safety Devices
@INPROCEEDINGS{10.4108/eai.15-12-2016.2267783, author={Francesco Sottile and Orlando Tovar Ordo\`{o}ez and Emil Kallias and Claudio Pastrone}, title={A Hybrid Localization Algorithm for Wearable Safety Devices}, proceedings={11th International Conference on Body Area Networks}, publisher={ACM}, proceedings_a={BODYNETS}, year={2017}, month={4}, keywords={radio-based localization uwb imu wearable technology kalman filter}, doi={10.4108/eai.15-12-2016.2267783} }- Francesco Sottile
Orlando Tovar Ordoñez
Emil Kallias
Claudio Pastrone
Year: 2017
A Hybrid Localization Algorithm for Wearable Safety Devices
BODYNETS
EAI
DOI: 10.4108/eai.15-12-2016.2267783
Abstract
Occupational safety and health (OSH) in industrial environments is gathering increasing attention in the era of Industry 4.0. 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, Position-Velocity (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.
