The Taub Faculty of Computer Science Events and Talks

Global localization for robotic vehicles is an essential backbone for robust autonomous navigation. While GPS systems offer effective solutions in outdoor environments, they are inadequate for providing positioning in indoor settings. In order to solve this problem, we investigate a special vision-based approach. Vision systems are particularly advantageous due to the amount of information they supply about the scene. To offer a system which has low cost and fast setup, we utilize a monocular camera. However, one issue with monocular vision is the inherent lack of scale when performing motion estimation. We resolve this by introducing the building floorplan and providing special algorithms to exploit this knowledge and obtain the unknown scale even when obstacles, both planar and non-planar, are present in the environment. Thus, our research presents a monocular vision-based system which provides global indoor positioning for small robotic vehicles.