Discrete-time robot visual feedback in 3-D positioning tasks with depth adaptation

In this paper, an adaptive visual feedback scheme is designed to perform 3-D positioning tasks. The dynamic camera-object interaction model is derived in discrete time, since the visual sampling time is not negligible at the current state of technology. Active contours are used to track the 2-D projection of the visible object's surface in the image plane. Uniform asymptotic stability of the image reference set-point is proved using Lyapunov's direct method, and a 3-D estimation procedure, based on prediction errors, is used to cope with the unknown depth of the object. Experimental results with a 6-DOF robot manipulator in eye-in-hand configuration validate the theoretical framework in real conditions.