The uncalibrated robotic hand–eye coordination problem is firstly modeled by a dynamic system, where the unknown hand–eye relationship is regarded as the system's unmodeled dynamics. A state observer is then designed to estimate impacts of this modeling error together with the system's external disturbances. With the estimation results as the compensation, the system control is thus accomplished based on a nonlinear combination of the system state errors. Convergence analysis of the whole system under the proposed control scheme is emphasized. Simulations and experiment results are presented to verify the performance of the proposed approach.