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In this paper, the uncalibrated visual servoing problem of robot manipulators with motor dynamics will be addressed for the fixed-camera configuration. A new adaptive image-space visual servoing strategy is presented to handle uncertainties in the camera intrinsic and extrinsic parameters, robot kinematic and dynamic parameters, and motor dynamic parameters. To deal with the nonlinear dependence of image Jacobian matrix on the unknown parameters, the proposed scheme is developed based on the concept of depth-independent interaction matrix. In this way, the camera parameters and the robot kinematic parameters in the closed-loop dynamics can be linearly parameterized such that adaptive laws can be designed to estimate them on-line. Adaptive algorithms are also developed to provide estimation of unknown robot dynamic and motor dynamic parameters. Stability analysis will be performed to show asymptotic convergence of image errors using Lyapunov theory based on both rigid-link robot dynamics and full motor dynamics. Simulation results based on a two-link planar robot manipulators will be given to illustrate the performance of the proposed scheme.