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We address the problem of finding the current position and heading angle ofan autonomous vehicle in real-time using a single camera. Compared to methodswhich require LiDARs and high definition (HD) 3D maps in real-time, theproposed approach is easily scalable and computationally efficient, at theprice of lower precision.  The new method combines and adapts existing algorithms in three differentfields: image retrieval, mapping database, and particle filtering. The resultis a simple, real-time localization method using an image retrieval methodwhose performance is comparable to other monocular camera localization methodswhich use a map built with LiDARs.  We evaluate the proposed method using the KITTI odometry dataset and viaclosed-loop experiments with an indoor 1:10 autonomous vehicle. The testsdemonstrate real-time capability and a 10cm level accuracy. Also, experimentalresults of the closed-loop indoor tests show the presence of a positivefeedback loop between the localization error and the control error. Suchphenomena is analysed in details at the end of the article.

Monocular Camera Localization for Automated Vehicles Using Image Retrieval