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In this paper, we present a novel computer vision framework for precise localization of a mobile robot on sidewalks. In our framework, we combine stereo camera images, visual odometry, satellite map matching, and a sidewalk probability transfer function obtained from street maps in order to attain globally corrected localization results. The framework is capable of precisely localizing a mobile robot platform that navigates on sidewalks, without the use of traditional wheel odometry, GPS or INS inputs. On a complex 570-meter sidewalk route, we show that we obtain superior localization results compared to visual odometry and GPS.
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