Since the last years, we are interested in visual servo-ing and we h a ve d e v eloped many visual servoing applications using 2D visual features. The aim of this paper is to study how w e c a n i n troduce 3D visual features in a robot control loop. We consider a camera mounted on the end e ector of the manipulator robot to estimate the pose of the target object. The required positioning task is to reach a speci c pose between the sensor frame and a target object frame. Knowing the target object model, we can localize the object in the 3D visual sensor frame and obtain the pose between the camera and the target object at each iteration. To insure the visual servoing task, we h a ve d e v eloped two approaches. The rst approach is based on the task function approach i n troduced by Samson and Espiau at the end of 80's. We considered a 3D visual sensor which gives the 3D visual pose of an object in the sensor frame. In this case, the sensor signal (dimen-sion 6) is composed of the position and the orientation of the frame object in the sensor frame. The second approach consists to split the trajectory between the current and the desired pose in a set of elementaries screwing tasks. At e a c h iteration, the situation between the sensor and the object is computed, and then the trajectory is updated.