Visually guided object grasping

We present a visual serving approach to the problem of object grasping and more generally, to the problem of aligning an end-effector with an object. First, we extend the method proposed by Espiau et al. (1992) to the case of a camera which is not mounted onto the robot being controlled, and we stress the importance of the real-time estimation of the image Jacobian. Next, we show how to represent a grasp or more generally, an alignment between two solids in 3D projective space using an uncalibrated stereo rig. Such a 3D projective representation is view-invariant in the sense that it can be easily mapped into an image set-point without any knowledge about the camera parameters. Finally, we perform an analysis of the performances of the visual servoing algorithm and of the grasping precision that can be expected from this type of approach.