Citation

Przemyslaw B, Pawel S. Sensors (Basel) 2012; 12(6): 6764-6801.

Affiliation

Institute of Electronics, Technical University of Lodz, Wolczanska 211/215, 90-924 Lodz, Poland; E-Mail: pawel.strumillo@p.lodz.pl.

Copyright

(Copyright © 2012, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/s120606764

PMID

22969321

Abstract

The paper presents an algorithm for estimating a pedestrian location in an urban environment. The algorithm is based on the particle filter and uses different data sources: a GPS receiver, inertial sensors, probability maps and a stereo camera. Inertial sensors are used to estimate a relative displacement of a pedestrian. A gyroscope estimates a change in the heading direction. An accelerometer is used to count a pedestrian's steps and their lengths. The so-called probability maps help to limit GPS inaccuracy by imposing constraints on pedestrian kinematics, e.g., it is assumed that a pedestrian cannot cross buildings, fences etc. This limits position inaccuracy to ca. 10 m. Incorporation of depth estimates derived from a stereo camera that are compared to the 3D model of an environment has enabled further reduction of positioning errors. As a result, for 90% of the time, the algorithm is able to estimate a pedestrian location with an error smaller than 2 m, compared to an error of 6.5 m for a navigation based solely on GPS.

Language: en