Using robust estimation for visual servoing based on dynamic vision

International audienceThe aim of this article is to achieve accurate visual servoing tasks when the shape of the object being observed as well as the final image are unknown. More precisely, we want to control the orientation of the tangent plane at a certain point on the object corresponding to the center of a region of interest and to move this point to the principal point to fulfill a fixation task. To do that, we perform a 3D reconstruction phase during the servoing. It is based on the measurement of the 2D displacement in the region of interest and on the measurement of the camera velocity. Since the 2D displacement depends on the scene, we introduce an unified motion model to deal with planar as well with non-planar objects. Unfortunately, this model is only an approximation. Thus, we propose to use robust estimation techniques and a 3D reconstruction based on discrete approach. Experimental results compare both approaches

Visual Servoing on Non-Planar Objects From Active Vision

Abstract — This paper presents a method to achieve visual servoing tasks when the shape of the object being observed as well as the final image are unknown. Therefore, a reconstruction phase has to be performed during the camera motion. More precisely, the reconstruction phase is based on the measurement of the 2D motion in a region of interest and on the measurement of the camera velocity. Since the 2D motion depends on the shape of objects being observed, we introduce an unified motion model to cope as well with planar as with non-planar objects. This is an improvement of our previous works described in [1], [2] where only planar objects had been considered. However, since this model is only an approximation, we propose to use active vision to enlarge its domain of validity. Experimental results validate the proposed approach. I

Visual Servoing on Non-Planar Objects From Active Vision

Abstract — This paper presents a method to achieve visual servoing tasks when the shape of the object being observed as well as the final image are unknown. Therefore, a reconstruction phase has to be performed during the camera motion. More precisely, the reconstruction phase is based on the measurement of the 2D motion in a region of interest and on the measurement of the camera velocity. Since the 2D motion depends on the shape of objects being observed, we introduce an unified motion model to cope as well with planar as with non-planar objects. This is an improvement of our previous works described in [1], [2] where only planar objects had been considered. However, since this model is only an approximation, we propose to use active vision to enlarge its domain of validity. Experimental results validate the proposed approach. I