CLIPS – a camera and laser-based indoor positioning system

Tilch, Sebastian; Mautz, Rainer

doi:10.1080/17489725.2012.688643

Cited by 9 publications

(5 citation statements)

References 14 publications

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“…Valve has published that it is necessary that at least five diodes have to be observed by the lighthouse to estimate the position and the orientation of a device [14]. Other indoor positioning systems following an outside-in tracking procedure are for instance Bluetooth fingerprinting [15], High sensitivity GNSS [16], the iGPS system from Metris [12], or the CLIPS system of ETH Zurich [17]. In contrast to the outside-in tracking is the inside-out tracking procedure (Figure 1a), where the positioning system is independent from external reference signals as used in the HTC Vive Cosmos [18] or the Microsoft HoloLens [19].…”

Section: System Components Of the Htc Vive Promentioning

confidence: 99%

Accuracy Investigation of the Pose Determination of a VR System

Bauer

Lienhart

Jost

2021

Sensors

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The usage of VR gear in mixed reality applications demands a high position and orientation accuracy of all devices to achieve a satisfying user experience. This paper investigates the system behaviour of the VR system HTC Vive Pro at a testing facility that is designed for the calibration of highly accurate positioning instruments like geodetic total stations, tilt sensors, geodetic gyroscopes or industrial laser scanners. Although the experiments show a high reproducibility of the position readings within a few millimetres, the VR system has systematic effects with magnitudes of several centimetres. A tilt of about 0.4∘ of the reference plane with respect to the horizontal plane was detected. Moreover, our results demonstrate that the tracking algorithm faces problems when several lighthouses are used.

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Section: System Components Of the Htc Vive Promentioning

confidence: 99%

Accuracy Investigation of the Pose Determination of a VR System

Bauer

Lienhart

Jost

2021

Sensors

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“…Based on a literature review (see e.g. [16,18,22,23,6]), the characteristics of the requirements were determined. The results are shown in Figure 1.…”

Section: Characteristics and Requirements Of Indoor Location Systemsmentioning

confidence: 99%

Classification of Optical Technologies for the Mapping of Production Environments

Greger

Palm

Louw

et al. 2019

IFIP Advances in Information and Communication Technology

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Indoor localization systems are becoming more and more important with the digitalization of the industrial sector. Sensor data such as the current position of machines, transport vehicles, goods or tools represent an essential component of cyber-physical production systems (CCPS). However, due to the high costs of these sensors, they are not widespread and are used mainly in special scenarios. However, especially optical indoor positioning systems (OIPS) based on cameras have certain advantages due to their technological specifications. In this paper, the application scenarios and requirements as well as their characteristics are presented and a classification approach of OIPS is introduced.

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“…For instance, there are several proposals that use the propagation of signals, such as Bluetooth, Zigbee, WiFi and radio frequency identification (RFID), among others [5][6][7][8]. These proposals have proved their ability to develop accurate and robust ILS, through the use of sensors and diverse devices, allowing the development of commercial and well-known systems, e.g., LANDMARC [9], Bluepos [10], CLIPS [11], to mention some [12,13]. Nevertheless, the use of these approaches is complicated and expensive given the need of specific infrastructure that must be deployed in buildings where the ILS will be used.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Indoor Location Through Magnetic Field Data: An Approach Based On Convolutional Neural Networks

Galván-Tejada

Zanella-Calzada

García-Domínguez

et al. 2020

IJGI

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Estimation of indoor location represents an interesting research topic since it is a main contextual variable for location bases services (LBS), eHealth applications and commercial systems, among others. For instance, hospitals require location data of their employees, as well as the location of their patients to offer services based on these locations at the correct moments of their needs. Several approaches have been proposed to tackle this problem using different types of artificial or natural signals (i.e., wifi, bluetooth, rfid, sound, movement,etc).In this work, it is proposed the development of an indoor location estimator system, relying in the data provided by the magnetic field of the rooms, which has been demonstrated that is unique and quasi-stationary. For this purpose, it is analyzed the spectral evolution of the magnetic field data viewed as a bidimensional heatmap, avoiding temporal dependencies. A Fourier transform is applied to the bidimensional heatmap of the magnetic field data to feed a convolutional neural network (CNN) to generate a model to estimate the user's location in a building. The evaluation of the CNN model to deploy an indoor location system (ILS) is done through measuring the Receiver Operating Characteristic (ROC) curve to observe the behavior in terms of sensitivity and specificity. Our experiments achieve a 0.99 Area Under the Curve (AUC) in the training data-set and a 0.74 in a total blind data set.

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CLIPS – a camera and laser-based indoor positioning system

Cited by 9 publications

References 14 publications

Accuracy Investigation of the Pose Determination of a VR System

Accuracy Investigation of the Pose Determination of a VR System

Classification of Optical Technologies for the Mapping of Production Environments

Estimation of Indoor Location Through Magnetic Field Data: An Approach Based On Convolutional Neural Networks

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