This report proposes a new way to achieve robotic tasks by 2D visual servoing. Indeed, instead of using classical geometric features such as points, straight lines, pose or an homography, as it is usually done, the luminance of all pixels in the image is here considered. The main advantage of this new approach is that it does not require any tracking or matching process. The key point of our approach relies on the analytic computation of the interaction matrix that links the time variation of the luminance to the camera motions. This computation is based either on a simple Lambertian model or on the Phong one so that complex illumination changes can be considered. However, since most of the classical control laws fail when considering the luminance as a visual feature, we turn the visual servoing problem into an optimization one leading to a new control law. Experimental results on positioning and tracking tasks validate the proposed approach and show its robustness regarding to approximated depths, Lambertian and non Lambertian objects, low textured objects and partial occlusions. Key-words:

Abstract-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.