This paper proposes a new way to achieve robotic tasks by visual servoing. Instead of using geometric features (points, straight lines, pose, homography, etc.) as it is usually done, we use directly the luminance of all pixels in the image. Since most of the classical control laws fail in this case, we turn the visual servoing problem into an optimization problem leading to a new control law. Experimental results validate the proposed approach and show its robustness regarding to approximated depths, non Lambertian objects and partial occlusions.

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In this work we propose a new way to achieve visual servoing using directly the information (as defined by Shannon) of the image. A metric derived from information theory, mutual information, is considered. Mutual information is widely used in multi-modal image registration (medical applications) since it is insensitive to changes in the lighting condition and to a wide class of non-linear image transformation. In this paper mutual-information is used as a new visual feature for visual servoing and allows us to build a new control law to control the 6 dof of the robot. Among various advantages, this approach does not require any matching nor tracking step, is robust to large illumination variation and allows to consider, within the same task, different image modalities. Experiments that demonstrate these advantages conclude the paper.

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Abstract — In this paper, we propose a new type of visual features for visual servoing: photometric moments. These global features do not require any segmentation, matching or tracking steps. The analytical form of the interaction matrix is developed in closed form for these features. Results from experiments carried out with photometric moments have been presented. The results validate our modelling and the control scheme. They perform well for large camera displacements and are endowed with a large convergence domain. From the properties exhibited, photometric moments hold promise as better candidates for IBVS over currently existing geometric and pure luminance features. I.