  In this paper, we investigate the visual tracking problem for robotic systems
without image-space velocity measurement, simultaneously taking into account
the uncertainties of the camera model and the manipulator kinematics and
dynamics. We propose a new image-space observer that exploits the image-space
velocity information contained in the unknown kinematics, upon which, we design
an adaptive controller without using the image-space velocity signal where the
adaptations of the depth-rate-independent kinematic parameter and depth
parameter are driven by both the image-space tracking errors and observation
errors. The major superiority of the proposed observer-based adaptive
controller lies in its simplicity and the separation of the handling of
multiple uncertainties in visually servoed robotic systems, thus avoiding the
overparametrization problem of the existing work. Using Lyapunov analysis, we
demonstrate that the image-space tracking errors converge to zero
asymptotically. The performance of the proposed adaptive control scheme is
illustrated by a numerical simulation.
