Abstract
This paper presents a constrained Kalman filter for Wi-Fi-based indoor localization. The contribution of this work is to introduce constraints on the object speed and to provide a numerically optimized form for fast computation. The proposed approach is suitable to flexible space organization, as in warehouses, and when objects can be spun around, for example barcode readers in a hand. We experimented with the proposed technique using a robot and three devices, on five different journeys, in a 6000 m2 warehouse equipped with six Wi-Fi access points. The results highlight that the proposed approach provides a 19% improvement in localization accuracy.
Highlights
IntroductionA Constrained Kalman Filter forWi-Fi-Based Indoor Localization withFlexible Space Organization
The constraint is about the object speed and only applies in some areas of the warehouse
The results highlight that the proposed approach improves the localization accuracy by
Summary
A Constrained Kalman Filter forWi-Fi-Based Indoor Localization withFlexible Space Organization. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations
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