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In this paper, we propose a new information theoretic approach to achieve visual servoing directly utilizing the information (as defined by Shannon) contained in the images. A metric derived from information theory, i.e., mutual information, is considered. Mutual information is widely used in multimodal image registration since it is insensitive to changes in the lighting condition and to a wide class of nonlinear image transformations. In this paper, mutual information is used as a new visual feature for visual servoing, which allows us to build a new control law that can control the six degrees of freedom (DOF) of a robot. Among various advantages, this approach requires no matching or tracking step, is robust to large illumination variations, and allows the consideration of different image modalities within the same task. Experiments on a real robot demonstrate the efficiency of the proposed visual-servoing approach.