Abstract
Abstract This paper reports an unscented Kalman filter approach for localization of a mobile robot in an indoor environment. The method proposes a new model of measurement uncertainty which adjusts the error co-variance according to the measured distance. The method also uses non-zero off diagonal values in error co-variance matrices of motion uncertainty and measurement uncertainty. The method is tested through experi-ments in an indoor environment of 100*40 m working space using a differential drive robot which uses Laser range finder as an exteroceptive sensor. The results compare the localization performance of the pro-posed method with the conventional method which doesn’t use adaptive measurement uncertainty model. Also, the experiment verifies the improvement due to non-zero off diagonal elements in covariance matrices. This paper contributes to implementing and evaluating a practical UKF approach for mobile robot localization.Key Words : Mobile robot localization, Unscented Kalman Filter, Measurement uncertainty, Covariance matrix, exteroceptive measurement이 논문은 2013년도 정부(교육부)의 재원으로 한국연구재단의 지원을 받아 수행된 기초연구사업임(NO. NRF-2013R1A1A4A01012469)This is an Open-Access article distributed un-der the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/li-censes/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and re-production in any medium, provided the orig-inal work is properly cited.Received: Jan. 28, 2015Revised : May. 24, 2015Accepted: May. 24, 2015
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