"This thesis presents a human/robot interaction in pick & place operations with optical tracking. The optical tracking consisted of in a complete vision system. It was developed using OpenCV Library integrated in Qt creator. A graphical user interface was designed, which contains the necessary requirements in order to achieve an optical tracking. The whole project is based on three main algorithms: Camera Calibration Algorithm, Object Detection Algorithm and Tracking algorithm. A webcam is used for capturing video. Hence the camera calibration has to be carried out. The parameters from the calibration are applied for solving the radial distortion. Handling of objects is the main goal. An object detection method is realized, which is based on geometry of the objects. The geometry is analyzed through a contour processing. Therefore the Canny Edge Detection algorithm is applied. The detection for the mark is the same method used for the objects. Optical tracking is achieved using the CamShift algorithm. CamShift permits to track the mark through camera view, and it is always possible to know the actual position of the mark. The main functions are provided from OpenCV Library, tests and comparisons between them were realized in order to obtain a better response. The robot system consists of an industrial robot with 6 degrees of freedom. This robot is mounted to a gantry robot. A gripper for the pick & place operation has been mounted onto the robot. The communication within the system robots and user interface was based on network technology. The final results obtained from each algorithm were completely successfully. The camera calibration algorithm was able to solve the radial distortion. Therefore the response of the object detection algorithm was a linear response. Due to undistortion the system presented high accuracy. The tracking based on CamShift algorithm is one of the functions that OpenCV Library provides. The definition of the color as feature to tracking is a powerful option for this application."