Multisensor mobile robot localization

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Abstract
Presents the 2D version of the symmetries and perturbation model (SPmodel), a probabilistic representation model and an EKF integration mechanism for uncertain geometric information that is suitable for sensor fusion and integration in multisensor systems. The authors apply the SPmodel to the problem of location estimation in mobile robotics, experimenting with the mobile robot MACROBE. The authors have chosen two types of sensorial information whose complementary nature allows a mobile robot to localize itself precisely in a known environment: range images and intensity images obtained from a laser sensor. By measuring distance to objects, range basically provides position information. On the other hand, the intensity image provided by the laser sensor (equivalent to a monocular vision system) can be used to detect vertical edges, corresponding to corners, frames, etc., which mainly provide angular information. Results of these experiments show that fusing simple and computationally inexpensive sensorial information can allow a mobile robot to precisely locate itself. They also demonstrate the generality of the proposed fusion and integration mechanism.

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