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Robot Localization using efficient planar features matching

Real-time accurate localization is a key component of an autonomous mobile robot. Visual localization algorithms usually rely on feature matching between the current view and a map using point descriptors. Many descriptors such as SIFT or SURF are designed to recognize features seen from different viewpoint. But in a robotic context, the robot movement can be modeled and bring useful information for the matching problem. In this paper we detail a way of matching features with a local 3D model of the features taking advantage of the motion model of the robot. We describe then methods to describe the motion model. The experimental results show how useful the motion model of robot movement is, and prove that use of other sensors can greatly improve precision and robustness of the localization.