Indoor Positioning Using the OpenHPS Framework

被引:4
作者
Van de Wynckel, Maxim [1 ]
Signer, Beat [1 ]
机构
[1] Vrije Univ Brussel, Web & Informat Syst Engn Lab, B-1050 Brussels, Belgium
来源
INTERNATIONAL CONFERENCE ON INDOOR POSITIONING AND INDOOR NAVIGATION (IPIN 2021) | 2021年
关键词
hybrid positioning; indoor positioning; process network; fingerprinting; pedestrian dead reckoning; SYSTEMS;
D O I
10.1109/IPIN51156.2021.9662569
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Hybrid positioning frameworks use various sensors and algorithms to enhance positioning through different types of fusion. The optimisation of the fusion process requires the testing of different algorithm parameters and optimal low-as well as high-level sensor fusion techniques. The presented OpenHPS open source hybrid positioning system is a modular framework managing individual nodes in a process network, which can be configured to support concrete positioning use cases or to adapt to specific technologies. This modularity allows developers to rapidly develop and optimise their positioning system while still providing them the flexibility to add their own algorithms. In this paper we discuss how a process network developed with OpenHPS can be used to realise a customisable indoor positioning solution with an offline and online stage, and how it can be adapted for high accuracy or low latency. For the demonstration and validation of our indoor positioning solution, we further compiled a publicly available dataset containing data from WLAN access points, BLE beacons as well as several trajectories that include IMU data.
引用
收藏
页数:8
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