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Article

Simultaneous Indoor Pedestrian Localization and House Mapping Based on Inertial Measurement Unit and Bluetooth Low-Energy Beacon Data

1
Telematics Engineering Research Group, Telematics Department, Universidad Del Cauca (Unicauca), Popayán 190002, Colombia
2
Machine Learning and Data Analytics Lab, Computer Science Department, Friedrich-Alexander University, Erlangen-Nürnberg (FAU), 91052 Erlangen, Germany
*
Authors to whom correspondence should be addressed.
Sensors 2020, 20(17), 4742; https://doi.org/10.3390/s20174742
Received: 21 June 2020 / Revised: 27 July 2020 / Accepted: 3 August 2020 / Published: 22 August 2020
(This article belongs to the Special Issue Advanced Approaches for Indoor Localization and Navigation)
Indoor location estimation is crucial to provide context-based assistance in home environments. In this study, a method for simultaneous indoor pedestrian localization and house mapping is proposed and evaluated. The method fuses a person’s movement data from an Inertial Measurement Unit (IMU) with proximity and activity-related data from Bluetooth Low-Energy (BLE) beacons deployed in the indoor environment. The person’s and beacons’ localization is performed simultaneously using a combination of particle and Kalman Filters. We evaluated the method using data from eight participants who performed different activities in an indoor environment. As a result, the average participant’s localization error was 1.05 ± 0.44 m, and the average beacons’ localization error was 0.82 ± 0.24 m. The proposed method is able to construct a map of the indoor environment by localizing the BLE beacons and simultaneously locating the person. The results obtained demonstrate that the proposed method could point to a promising roadmap towards the development of simultaneous localization and home mapping system based only on one IMU and a few BLE beacons. To the best of our knowledge, this is the first method that includes the beacons’ data movement as activity-related events in a method for pedestrian Simultaneous Localization and Mapping (SLAM). View Full-Text
Keywords: indoor localization; indoor tracking; SLAM; particle filter indoor localization; indoor tracking; SLAM; particle filter
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MDPI and ACS Style

Ceron, J.D.; Kluge, F.; Küderle, A.; Eskofier, B.M.; López, D.M. Simultaneous Indoor Pedestrian Localization and House Mapping Based on Inertial Measurement Unit and Bluetooth Low-Energy Beacon Data. Sensors 2020, 20, 4742. https://doi.org/10.3390/s20174742

AMA Style

Ceron JD, Kluge F, Küderle A, Eskofier BM, López DM. Simultaneous Indoor Pedestrian Localization and House Mapping Based on Inertial Measurement Unit and Bluetooth Low-Energy Beacon Data. Sensors. 2020; 20(17):4742. https://doi.org/10.3390/s20174742

Chicago/Turabian Style

Ceron, Jesus D., Felix Kluge, Arne Küderle, Bjoern M. Eskofier, and Diego M. López 2020. "Simultaneous Indoor Pedestrian Localization and House Mapping Based on Inertial Measurement Unit and Bluetooth Low-Energy Beacon Data" Sensors 20, no. 17: 4742. https://doi.org/10.3390/s20174742

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