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Outdoor Localization through GPS Data and Matching of Lane Markers for a Mobile Robot

Yong Ji, Ji-Hun Bae, Jae-Bok Song, Jae Kwan Ryu, Joo Hyun Baek

Year
2012
Citations
6
Access
Open access

Abstract

Accurate localization is very important to stable navigation of a mobile robot. This paper deals with local localization of a mobile robot especially for outdoor environments. The GPS information is the easiest way to obtain the outdoor position information. However, the GPS accuracy can be severely affected by environmental conditions. To deal with this problem, the GPS and wheel odometry can be combined using an EKF (Extended Kalman Filter). However, this is not enough for safe navigation of a mobile robot in outdoor environments. This paper proposes a novel method using lane features from the road image. The pose data of a mobile robot can be corrected by analyzing the detected lane features. This can improve the accuracy of the localization process substantially.

Keywords

OdometryGlobal Positioning SystemComputer visionMobile robotMobile robot navigationComputer scienceArtificial intelligenceExtended Kalman filterRobotVisual odometry

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