Collineation estimation from two unmatched views of an unknown planar contour for visual servoing

In this paper we describe a method to compute the collineation matrix between two unmatched images of an unknown planar contour described using a B-spline snake. The two images of the contour are matched and the collineation matrix is used to servo a camera mounted on the robot end-effector using a 2 1/2 D visual servoing technique

Collineation Estimation From Two Unmatched Views of an Unknown Planar Contour for Visual Servoing

In this paper we describe a method to compute the collineation matrix between two unmatched images of an unknown planar contour described using a B-spline snake. The two images of the contour are matched and the collineation matrix is used to servo a camera mounted on the robot end-effector using a 2 1/2 D visual servoing technique. The experimental results, obtained using common planar objects, show that our method give very good results and allow the robot end-effector to be positioned with a great precision. 1 Introduction The visual servoing scheme of robot manipulators can be divided in three steps. In the first off-line learning step, the reference image of the object corresponding to a desired position of the robot is acquired and some image features are extracted. In general, objects are represented by free-form curves, i.e., arbitrary space curves of the type found in practice. A curve is usually described as a set of chained points. The reference image can be obtaine..