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Mathematical Problems in Engineering
Volume 2014, Article ID 368961, 12 pages
Research Article

Localization of Outdoor Mobile Robots Using Curb Features in Urban Road Environments

1Department of Mechanical Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-713, Republic of Korea
2Department of Control and Instrumentation, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-713, Republic of Korea

Received 12 December 2013; Revised 13 February 2014; Accepted 13 February 2014; Published 8 April 2014

Academic Editor: Leo Chen

Copyright © 2014 Hyunsuk Lee et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Urban road environments that have pavement and curb are characterized as semistructured road environments. In semistructured road environments, the curb provides useful information for robot navigation. In this paper, we present a practical localization method for outdoor mobile robots using the curb features in semistructured road environments. The curb features are especially useful in urban environment, where the GPS failures take place frequently. A curb extraction is conducted on the basis of the Kernel Fisher Discriminant Analysis (KFDA) to minimize false detection. We adopt the Extended Kalman Filter (EKF) to combine the curb information with odometry and Differential Global Positioning System (DGPS). The uncertainty models for the sensors are quantitatively analyzed to provide a practical solution.