Calibration of the robot and vision system is a process that establishes the spatial relationship between the robot gripper and the vision system. This calibration is essential for many applications involving robotic systems. The vision system captures an image that contains the desired object. The computer analyzes the image and determines the object’s position. Based on the calibration results, the computer determines the position to which the robot gripper must move to successfully handle the object. The topic of this thesis is the development of automated extrinsic calibration for "eye-in-hand” robotic systems. These are systems where the vision system is mounted on the robot arm, and the goal of calibration is to determine the transformation between the gripper and the camera coordinate system. The first part of the thesis describes the components used for the calibration process, including the camera specifications, the robotic controller, and the calibration object. Additionally, methods that solve the calibration problem are explained. The communication logic at the camera-computer and computer-robotic controller levels is described, ensuring a robust way of retrieving images from the camera and moving to desired positions. The next section presents the algorithm by which the system collects data with minimal operator involvement. After collecting a sufficient number of images and positions, the calibration process is performed using one of the previously described methods, and a comparison of methods is made depending on different calibration settings. Finally, the validation process for the obtained results of the selected method is conducted, and a procedure for error correction is implemented if such errors exist.