The goal of this master’s thesis is the integration of Franka Emika robot in the ROS2 operating system and its adaptation for tracking a curved 3D surface tracking using built-in force and torque sensors. The thesis outlines the process of installing ROS2 operating system and its subsystems for successfully connecting the robot to the computer. The procedures for integrating Franka Emika robot into the ROS2 environment, adapting existing ROS2 packages such as MoveIt2, and customizing them to suit the needs of this research are also described in detail. For capturing the working environment, an Intel RealSense D435i camera was utilized. Its physical characteristics, along with the installation of necessary libraries and tools for use in the ROS2 system, as well as the “eye-in-hand” calibration process for precise spatial visualization are thoroughly explained. The mentioned “eye-in-hand” camera was used to generate a 3D image through point cloud data, allowing the user in the ROS2 environment to select positional markers as target points for the robotic arm. Regarding the construction aspect of this paper, the thesis documents the models of the depth camera mount for the "eye-in-hand" configuration and the tactile tool with a spherical tip, which can be mounted on a robot gripper and gripped by movable fingers. These models were constructed using a 3D printer and mounted on the flange and the gripper. The workpiece used for testing this system was not designed specifically for this thesis but is a sample from the CRTA laboratory used in several projects. The foundation of this research lies in the development of a controller enabling precise tracking of the curved surface and maintaining constant contact between the tool and the surface by regulating force and keeping its value within specified limits. Seven torque sensors distributed across all robot joints are employed to estimate the force at the tool, which is then regulated by discrete robot movements along the defined path. The point-to-point path is defined using MoveIt2 package to optimize the process. An experimental validation of the accuracy of tool positioning was conducted using a calibration board, which is also used for camera calibration. Also, the tracking of the 3D curved surface using the discrete force controller was validated using four and three point combinations.