Sensor Fusion System for Mobile Robot Localization Using Fault Detection Similarity Evaluation of Probability Distribution for Fault Detection

2017 ◽  
Vol 2017 (0) ◽  
pp. 2P2-C01
Author(s):  
Nozomu OHASHI ◽  
Yuki FUNABORA ◽  
Shinji DOKI ◽  
Kae DOKI
Keyword(s):  
Probability Distribution ◽  
Fault Detection ◽  
Mobile Robot ◽  
Sensor Fusion ◽  
Robot Localization ◽  
Fusion System ◽  
Mobile Robot Localization

scholarly journals MOBILE ROBOT LOCALIZATION USING WLAN, ODOMETRY AND GYROSCOPE DATA

2010 ◽  
pp. 22-30
Author(s):  
Julian Lategahn ◽  
Frank Kuenemund ◽  
Christof Roehrig
Keyword(s):  
Kalman Filter ◽  
Mobile Robot ◽  
Sensor Fusion ◽  
Indoor Environment ◽  
Signal Strength ◽  
Office Building ◽  
Robot Localization ◽  
Mobile Robot Localization ◽  
Radio Map ◽  
Made In

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.

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