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

Hyunsuk Lee | Zendy; Jooyoung Park | Zendy; Woojin Chung | Zendy

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

Author(s) -

Hyunsuk Lee,

Jooyoung Park,

Woojin Chung

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/368961

Subject(s) - odometry , global positioning system , computer science , extended kalman filter , robot , artificial intelligence , mobile robot , kalman filter , computer vision , telecommunications

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

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