Position estimation using artificial generated magnetic fields

Blankenbach, Jörg; Norrdine, Abdelmoumen

doi:10.1109/ipin.2010.5646739

Cited by 65 publications

(33 citation statements)

References 4 publications

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“…Still, the localization depends entirely on the coverage of the beacons, which is not always a given. On a similar note, Blankenbach and Norrdine [10] have achieved indoor localization through the use of magnetic field generators outside of buildings. While magnetic fields can, for the most part.…”

Section: Localization With External Sensorsmentioning

confidence: 96%

Indoor Localization for Augmented Reality Devices Using BIM, Point Clouds, and Template Matching

Herbers

König

2019

Applied Sciences

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Mobile devices are a common target for augmented reality applications, especially for showing contextual information in buildings or construction sites. A prerequisite of contextual information display is the localization of objects and the device in the real world. In this paper, we present our approach to the problem of mobile indoor localization with a given building model. The approach does not use external sensors or input. Accurate external sensors such as stationary cameras may be expensive and difficult to set up and maintain. Relying on already existing external sources may also prove to be difficult, as especially inside buildings, Internet connections can be unreliable and GPS signals can be inaccurate. Therefore, we try to find a localization solution for augmented reality devices that can accurately localize itself only with data from internal sensors and preexisting information about the building. If a building has an accurate model of its geometry, we can use modern spatial mapping techniques and point-cloud matching to find a mapping between local device coordinates and global model coordinates. We use normal analysis and 2D template matching on an inverse distance map to determine this mapping. The proposed algorithm is designed to have a high speed and efficiency, as mobile devices are constrained by hardware limitations. We show an implementation of the algorithm on the Microsoft HoloLens, test the localization accuracy, and offer use cases for the technology.

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Section: Localization With External Sensorsmentioning

confidence: 96%

Indoor Localization for Augmented Reality Devices Using BIM, Point Clouds, and Template Matching

Herbers

König

2019

Applied Sciences

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show abstract

“…Systems based on magnetic field has centimeter accuracy and can cover an area of 10 m [34]. Different approaches range from systems dedicated for medical purposes using an artificial quasi-static magnetic field with less than 1 m 3 volume operating at mm-accuracy level.…”

Section: Indoor Localization Systemsmentioning

confidence: 99%

Static and Dynamic Evaluation of an UWB Localization System for Industrial Applications

Delamare¹,

Boutteau²,

Savatier³

et al. 2020

Sci

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Many applications in the context of Industry 4.0 require precise localization. However, indoor localization remains an open problem, especially in complex environments such as industrial environments.In recent years, we have seen the emergence of Ultra WideBand (UWB) localization systems. The aim of this article is to evaluate the performance of a UWB system to estimate the position of a person moving in an indoor environment. To do so, we implemented an experimental protocol to evaluate the accuracy of the UWB system both statically and dynamically. The UWB system is compared to a ground truth obtained by a motion capture system with a millimetric accuracy.

show abstract

“…System based on magnetic field has centimeter-accuracy and can cover an area of 10 m [33]. Different approaches range from systems dedicated for medical purposes using an artificial quasi static magnetic field with less than 1 m 3 volume operating at mm-accuracy level.…”

Section: Indoor Localization Systemsmentioning

confidence: 99%

Static and Dynamic Evaluation of an UWB Localization System for Industrial Applications

Delamare¹,

Boutteau²,

Savatier³

et al. 2019

Sci

View full text Add to dashboard Cite

Many applications in the context of Industry 4.0 require precise localization. However, indoor localization remains an open problem, especially in complex environments such as industrial environments. In recent years, we have seen the emergence of Ultra WideBand (UWB) localization systems. The aim of this article is to evaluate the performance of a UWB system to estimate the position of a person moving in an indoor environment. To do so, we implemented an experimental protocol to evaluate the accuracy of the UWB system both statically and dynamically. The UWB system is compared to a ground truth obtained by a motion capture system with a millimetric accuracy.

show abstract

Position estimation using artificial generated magnetic fields

Cited by 65 publications

References 4 publications

Indoor Localization for Augmented Reality Devices Using BIM, Point Clouds, and Template Matching

Indoor Localization for Augmented Reality Devices Using BIM, Point Clouds, and Template Matching

Static and Dynamic Evaluation of an UWB Localization System for Industrial Applications

Static and Dynamic Evaluation of an UWB Localization System for Industrial Applications

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