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This paper aims to estimate the blood velocity to enhance the navigation of an aggregate in the human vasculature. The considered system is a polymer-binded aggregate of ferromagnetic nanorobots immersed in a blood vessel. The drag force depends on the blood velocity and especially acts on the aggregate dynamics. In the design of advanced control laws, the blood velocity is usually assumed to be known or set to a constant mean value to achieve the control objectives. We provide theoretical tools to online estimate the blood velocity from the sole measurement of the aggregate position and combine the state estimator with a backstepping control law. Two state estimation approaches are addressed and compared through simulations: a high-gain observer and a receding horizon estimator. Simulations illustrate the efficiency of the proposed approach combining online estimation and control for the navigation of an aggregate of nanorobots.