Pedestrian indoor positioning using smartphone multi-sensing, radio beacons, user positions probability map and IndoorOSM floor plan representation

Jose C. Aguilar Herrera, Paul Plöger, André Hinkenjann, Jens Maiero, A. Ramos
2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN), page 636--645 - October 2014

Abstract

Position awareness in unknown and large indoor spaces represents a great advantage for people, everyday pedestrians have to search for specific places, products and services. In this work a positioning solution able to localize the user based on data measured with a mobile device is described and evaluated. The position estimate uses data from smartphone built-in sensors, WiFi (Wireless Fidelity) adapter and map information of the indoor environment (e.g. walls and obstacles). A probability map derived from statistical information of the users tracked location over a period of time in the test scenario is generated and embedded in a map graph, in order to correct and combine the position estimates under a Bayesian representation. PDR (Pedestrian Dead Reckoning), beacon-based Weighted Centroid position estimates, map information obtained from building OpenStreetMap XML representation and probability map users path density are combined using a Particle Filter and implemented in a smartphone application. Based on evaluations, this work verifies that the use of smartphone hardware components, map data and its semantic information represented in the form of a OpenStreetMap structure provide 2.48 meters average error after 1,700 travelled meters and a scalable indoor positioning solution. The Particle Filter algorithm used to combine various sources of information, its radio WiFi-based observation, probability particle weighting process and the mapping approach allowing the inclusion of new indoor environments knowledge show a promising approach for an extensible indoor navigation system.

See also

The paper can be accessed online here.

BibTex references

@InProceedings{APHMR14,
  author       = {Aguilar Herrera, Jose C. and Pl{\"o}ger, Paul and Hinkenjann, Andr{\'e} and Maiero, Jens and Ramos, A.},
  title        = {Pedestrian indoor positioning using smartphone multi-sensing, radio beacons, user positions probability map and IndoorOSM floor plan representation },
  booktitle    = {2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN)},
  pages        = {636--645},
  month        = {October},
  year         = {2014},
}

Other publications in the database

» Jose C. Aguilar Herrera
» Paul Plöger
» André Hinkenjann
» Jens Maiero