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http://dx.doi.org/10.5391/JKIIS.2016.26.4.253

An Optimization Approach for Localization of an Indoor Mobile Robot  

Han, Jun Hee (Dept. Control and Inst. Eng., Chosun Univ.)
Ko, Nak Yong (Dept. Electronic Eng., Chosun Univ.)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.26, no.4, 2016 , pp. 253-258 More about this Journal
Abstract
This paper proposes a method that utilizes optimization approach for localization of an indoor mobile robot. Bayesian filters which have been widely used for localization of a mobile robot use many control parameters to take the uncertainties in measurement and environment into account. The estimation performance depends on the selection of these parameter values. Also, the performance of the Bayesian filters deteriorate as the non-linearity of the motion and measurement increases. On the other hand, the optimization approach uses fewer control parameters and is less influenced by the non-linearity than the Bayesian methods. This paper compares the localization performance of the proposed method with the performance of the extended Kalman filter to verify the feasibility of the proposed method. Measurements of ranges from beacons of ultrasonic satellite to the robot are used for localization. Mahalanobis distance is used for detection and rejection of outlier in the measurements. The optimization method sets performance index as a function of the measured range values, and finds the optimized estimation of the location through iteration. The method can improve the localization performance and reduce the computation time in corporation with Bayesian filter which provides proper initial location for the iteration.
Keywords
Mobile robot localization; Optimization technique; Extended Kalman Filter; Ultrasonic Satellites system; Outlier rejection;
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Times Cited By KSCI : 7  (Citation Analysis)
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