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Indoor localization for pedestrians with real-time capability using multi-sensor smartphones / Catia Real Ehrlich in Geo-spatial Information Science, vol 22 n° 2 (June 2019)  

Public [article]  inGeo-spatial Information Science > vol 22 n° 2 (June 2019) . - pp 73 - 88 Titre : Indoor localization for pedestrians with real-time capability using multi-sensor smartphones Type de document : Article/Communication Auteurs : Catia Real Ehrlich, Auteur ; Jörg Blankenbach, Auteur Année de publication : 2019 Article en page(s) : pp 73 - 88 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes descripteurs IGN] altitude barométrique [Termes descripteurs IGN] Bluetooth [Termes descripteurs IGN] méthode de Monte-Carlo [Termes descripteurs IGN] microsystème électromécanique [Termes descripteurs IGN] navigation à l'estime [Termes descripteurs IGN] navigation pédestre [Termes descripteurs IGN] positionnement en intérieur [Termes descripteurs IGN] téléphone intelligent Résumé : (Auteur) The localization of persons or objects usually refers to a position determined in a spatial reference system. Outdoors, this is usually accomplished with Global Navigation Satellite Systems (GNSS). However, the automatic positioning of people in GNSS-free environments, especially inside of buildings (indoors) poses a huge challenge. Indoors, satellite signals are attenuated, shielded or reflected by building components (e.g. walls or ceilings). For selected applications, the automatic indoor positioning is possible based on different technologies (e.g. WiFi, RFID, or UWB). However, a standard solution is still not available. Many indoor positioning systems are only suitable for specific applications or are deployed under certain conditions, e.g. additional infrastructures or sensor technologies. Smartphones, as popular cost-effective multi-sensor systems, is a promising indoor localization platform for the mass-market and is increasingly coming into focus. Today’s devices are equipped with a variety of sensors that can be used for indoor positioning. In this contribution, an approach to smartphone-based pedestrian indoor localization is presented. The novelty of this approach refers to a holistic, real-time pedestrian localization inside of buildings based on multi-sensor smartphones and easy-to-install local positioning systems. For this purpose, the barometric altitude is estimated in order to derive the floor on which the user is located. The 2D position is determined subsequently using the principle of pedestrian dead reckoning based on user's movements extracted from the smartphone sensors. In order to minimize the strong error accumulation in the localization caused by various sensor errors, additional information is integrated into the position estimation. The building model is used to identify permissible (e.g. rooms, passageways) and impermissible (e.g. walls) building areas for the pedestrian. Several technologies contributing to higher precision and robustness are also included. For the fusion of different linear and non-linear data, an advanced algorithm based on the Sequential Monte Carlo method is presented. Numéro de notice : A2019-325 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2019.1613778 date de publication en ligne : 21/05/2019 En ligne : https://doi.org/10.1080/10095020.2019.1613778 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93327 [article]

Low-complexity online correction and calibration of pedestrian dead reckoning using map matching and GPS / Fabian Hölzke in Geo-spatial Information Science, vol 22 n° 2 (June 2019)  

Public [article]  inGeo-spatial Information Science > vol 22 n° 2 (June 2019) . - pp 114 - 127 Titre : Low-complexity online correction and calibration of pedestrian dead reckoning using map matching and GPS Type de document : Article/Communication Auteurs : Fabian Hölzke, Auteur ; Johann-P. Wolff, Auteur ; Frank Golatowski, Auteur ; Christian Haubelt, Auteur Année de publication : 2019 Article en page(s) : pp 114 - 127 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes descripteurs IGN] carte d'intérieur [Termes descripteurs IGN] données GPS [Termes descripteurs IGN] navigation à l'estime [Termes descripteurs IGN] navigation pédestre [Termes descripteurs IGN] positionnement en intérieur Résumé : (Auteur) Dead Reckoning is a relative positioning scheme that is used to infer the change of position relative to a point of origin by measuring the traveled distance and orientation change. Pedestrian Dead Reckoning (PDR) applies this concept to walking persons. The method can be used to track someone's movement in a building after a known landmark like the building's entrance is registered. Here, the movement of a foot and the corresponding direction change is measured and summed up, to infer the current position. Measuring and integrating the corresponding physical parameters, e.g. using inertial sensors, introduces small errors that accumulate quickly into large distance errors. Knowledge of a buildings geography may reduce these errors as it can be used to keep the estimated position from moving through walls and onto likely paths. In this paper, we use building maps to improve localization based on a single foot-mounted inertial sensor. We describe our localization method using zero velocity updates to accurately compute the length of individual steps and a Madgwick filter to determine the step orientation. Even though the computation of individual steps is quite accurate, small errors still accumulate in the long term. We show how correction algorithms using likely and unlikely paths can rectify errors intrinsic to pedestrian dead reckoning tasks, such as orientation and displacement drift, and discuss restrictions and disadvantages of these algorithms. We also present a method of deriving the initial position and orientation from GPS measurements. We verify our PDR correction methods analyzing the corrected and raw trajectories of six participants walking four routes of varying length and complexity through an office building, walking each route three times. Our quantitative results show an endpoint accuracy improvement of up to 60% when using likely paths and 23% when using unlikely paths. However, both approaches can also decrease accuracy in certain scenarios. We identify those scenarios and offer further ideas for improving Pedestrian Dead Reckoning methods. Numéro de notice : A2019-323 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2019.1617528 date de publication en ligne : 30/05/2019 En ligne : https://doi.org/10.1080/10095020.2019.1617528 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93323 [article]

A regression model-based method for indoor positioning with compound location fingerprints / Tomofumi Takayama in Geo-spatial Information Science, vol 22 n° 2 (June 2019)  

Public [article]  inGeo-spatial Information Science > vol 22 n° 2 (June 2019) . - pp 107 - 113 Titre : A regression model-based method for indoor positioning with compound location fingerprints Type de document : Article/Communication Auteurs : Tomofumi Takayama, Auteur ; Takeshi Umezawa, Auteur ; Nobuyoshi Komuro, Auteur ; Noritaka Osawa, Auteur Année de publication : 2019 Article en page(s) : pp 107 - 113 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes descripteurs IGN] Bluetooth [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] navigation à l'estime [Termes descripteurs IGN] positionnement en intérieur [Termes descripteurs IGN] régression Résumé : (Auteur) This paper proposed and evaluated an estimation method for indoor positioning. The method combines location fingerprinting and dead reckoning differently from the conventional combinations. It uses compound location fingerprints, which are composed of radio fingerprints at multiple points of time, that is, at multiple positions, and displacements between them estimated by dead reckoning. To avoid errors accumulated from dead reckoning, the method uses short-range dead reckoning. The method was evaluated using 16 Bluetooth beacons installed in a student room with the dimensions of 11 × 5 m with furniture inside. The Received Signal Strength Indicator (RSSI) values of the beacons were collected at 30 measuring points, which were points at the intersections on a 1 × 1 m grid with no obstacles. A compound location fingerprint is composed of RSSI vectors at two points and a displacement vector between them. Random Forests (RF) was used to build regression models to estimate positions from location fingerprints. The root mean square error of position estimation was 0.87 m using 16 Bluetooth beacons. This error is lower than that received with a single-point baseline model, where a feature vector is composed of only RSSI values at one location. The results suggest that the proposed method is effective for indoor positioning. Numéro de notice : A2019-324 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2019.1612599 date de publication en ligne : 17/05/2019 En ligne : https://doi.org/10.1080/10095020.2019.1612599 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93324 [article]

Inferring user tasks in pedestrian navigation from eye movement data in real-world environments / Hua Liao in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > Vol 33 n° 3-4 (March - April 2019) . - pp 739 - 763 Titre : Inferring user tasks in pedestrian navigation from eye movement data in real-world environments Type de document : Article/Communication Auteurs : Hua Liao, Auteur ; Weihua Dong, Auteur ; Haosheng Huang, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 739 - 763 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] calcul d'itinéraire [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] inférence [Termes descripteurs IGN] navigation pédestre [Termes descripteurs IGN] oculométrie [Termes descripteurs IGN] représentation cognitive [Vedettes matières IGN] Géovisualisation Résumé : (Auteur) Eye movement data convey a wealth of information that can be used to probe human behaviour and cognitive processes. To date, eye tracking studies have mainly focused on laboratory-based evaluations of cartographic interfaces; in contrast, little attention has been paid to eye movement data mining for real-world applications. In this study, we propose using machine-learning methods to infer user tasks from eye movement data in real-world pedestrian navigation scenarios. We conducted a real-world pedestrian navigation experiment in which we recorded eye movement data from 38 participants. We trained and cross-validated a random forest classifier for classifying five common navigation tasks using five types of eye movement features. The results show that the classifier can achieve an overall accuracy of 67%. We found that statistical eye movement features and saccade encoding features are more useful than the other investigated types of features for distinguishing user tasks. We also identified that the choice of classifier, the time window size and the eye movement features considered are all important factors that influence task inference performance. Results of the research open doors to some potential real-world innovative applications, such as navigation systems that can provide task-related information depending on the task a user is performing. Numéro de notice : A2019-214 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1482554 date de publication en ligne : 26/06/2018 En ligne : https://doi.org/10.1080/13658816.2018.1482554 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92686 [article]

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Point clouds for direct pedestrian pathfinding in urban environments / Jesus Balado in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 148 (February 2019) . - pp 184 - 196 Titre : Point clouds for direct pedestrian pathfinding in urban environments Type de document : Article/Communication Auteurs : Jesus Balado, Auteur ; Lucia Diaz-Vilarino, Auteur ; Pedro Arias, Auteur ; Henrique Lorenzo, Auteur Année de publication : 2019 Article en page(s) : pp 184 - 196 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] accessibilité [Termes descripteurs IGN] chemin le plus court (algorithme) [Termes descripteurs IGN] détection de partie cachée [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] graphe [Termes descripteurs IGN] itinéraire piétionnier [Termes descripteurs IGN] milieu urbain [Termes descripteurs IGN] navigation pédestre [Termes descripteurs IGN] objet mobile [Termes descripteurs IGN] objet statique [Termes descripteurs IGN] semis de points Mots-clés libres : espace urbain navigable pour piéton Résumé : (Auteur) Pathfinding applications for the citizen in urban environments are usually designed from the perspective of a driver, not being effective for pedestrians. In addition, urban scenes have multiple elements that interfere with pedestrian routes and navigable space. In this paper, a methodology for the direct use of point clouds for pathfinding in urban environments is presented, solving the main limitations for this purpose: (a) the excessive number of points is reduced for transformation into nodes on the final graph, (b) urban static elements acting as permanent obstacles, such as furniture and trees, are delimited and differentiated from dynamic elements such as pedestrians, (c) occlusions on ground elements are corrected to enable a complete graph modelling, and (d) navigable space is delimited from free unobstructed space according to two motor skills (pedestrians without reduced mobility and wheelchairs). The methodology is tested into three different streets sampled as point clouds by mobile laser scanning (MLS) systems: an intersection of several streets with ground composed of sidewalks at different heights; an avenue with wide sidewalks, trees and cars parked on one side; and a street with a single-lane road and narrow sidewalks. By applying Dijkstra pathfinding algorithm to the resulting graphs, the correct viability of the generated routes has been verified based on a visual analysis of the generated routes on the point cloud and on the knowledge of the urban study area. The methodology enables the automatic generation of graphs representing the navigable urban space, on which safe and real routes for different motor skills can be calculated. Numéro de notice : A2019-074 Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.004 date de publication en ligne : 15/01/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.01.004 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92161 [article]

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L'information aéronautique à ciel ouvert / Pascal Sénard (2019)

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Multimodal scene understanding: algorithms, applications and deep learning, ch. 8. Multimodal localization for embedded systems: a survey / Imane Salhi (2019)  

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Adéquation algorithme architecture pour la localisation basée image sur système embarqué / David Vandergucht (2018)    

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Tight integration of INS/Stereo VO/Digital map for land vehicle navigation / Fei Liu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 1 (January 2018)  

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An effective spherical panoramic LoD model for a mobile street view service / Xianxiong Liu in Transactions in GIS, vol 21 n° 5 (October 2017)  

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Knowledge extraction from crowdsourced data for the enrichment of road networks / Gregor Jossé in Geoinformatica [en ligne], vol 21 n° 4 (October - December 2017)  

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Sailing : Cognition, action, communication / Thora Tenbrink in Journal of Spatial Information Science (JoSIS), n° 15 (September 2017)  

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vol 21 n° 3 - July - September 2017 - Special issue [included] on Map interaction (Bulletin de Geoinformatica [en ligne]) / Christian Kray  

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I’m walking here! Checking the accuracy of an inertial-based pedestrian navigation system with a drone / Marcin Uradzinski in GPS world, vol 28 n° 6 (June 2017)

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The bounds of distortion : truth, meaning and efficacy in digital geographic representation / Lucas Godfrey in International journal of cartography, vol 3 n° 1 (June 2017)  

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