Open AccessMOBILE ROBOT LOCALIZATION USING WLAN, ODOMETRY AND GYROSCOPE DATA
Author(s) -
Julian Lategahn,
Frank Kuenemund,
Christof Roehrig
Publication year - 2010
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.9.1.694
Subject(s) - odometry , computer science , mobile robot , gyroscope , computer vision , artificial intelligence , robot , kalman filter , extended kalman filter , sensor fusion , position (finance) , signal (programming language) , real time computing , engineering , programming language , finance , economics , aerospace engineering
In this paper a method for estimation of position and motion of a mobile robot in an indoor environment is introduced. The proposed method uses WLAN signal strength to estimate the global position of a mobile robot in an office building. Thus signal strengths of the received access points are stored in the radio map in calibration phase. In localization phase the stored values are compared with actually measured one’s. Therefore a fingerprinting algorithm, that was introduced before, is used. The improvement of the presented work is the multi sensor fusion using Kalman filter, which enhances the accuracy of fingerprinting algorithms and tracking of the robot. For this reason odometric and gyroscopic sensors of the robot are fused with the estimated position of the fingerprinting algorithm. The paper presents the experimental results of measurements made in an office building.