Real-time monocular visual self-localization approach using natural circular landmarks for indoor navigation

As the most critical function of mobile robots, navigation substantially relies on self-localization. Among all the approaches, vision based localization is widely adopted. Unlike the complex algorithms developed before, we present a simple real-time visual localization approach which regards the circular lamps on the ceiling as the landmarks. Two sets of point correspondences are applied to solving Perspective-n-Point (PnP) problem. One set contains the centers of the ellipses in image and the centers of the circles in 3D. The other set contains the tangent points on the circles and ellipses. At least two lamps are required in the field of view to avoid ambiguities. The experimental results show that no blind zone exists since the required number of lamps is small. The position and orientation errors are small enough for indoor navigation. This approach is validated by experiments for real-time application.