This paper addresses the design of a control law for vision-based robot navigation. The method proposed is based on a topological representation of the environment. Within this context, a learning stage enables a graph to be built in which nodes represent views acquired by the camera, and edges denote the possibility for the robotic system to move from one image to an other. A path finding algorithm then gives the robot a collection of views describing the environment it has go through in order to reach its desired position. This article focuses on the control law used for controlling the robot motion's on-line. The particularity of this control law is that it does not require any reconstruction of the environment, and does not force the robot to converge towards each intermediary position in the path. Landmarks matched between each consecutive views of the path are considered as successive features that the camera has to observe within its eld of view. A visual servoing control law is designed using specific features which ensures that the robot navigates within the visibility path. Simulation results demonstrate the validity of the proposed approach.