# Camera Calibration in High-Speed Robotic Assembly Operations
## 1 Introduction
The increase in positioning accuracy and repeatability allows the integration of robots in assembly operations using guidance systems (structured applications) or video acquisition systems (unstructured applications) [1]. In the case of the guidance systems, the assembly requires the existence of additional stages of guiding and repositioning the assembled landmarks, stages that entail additional times and, implicitly, a reduction in productivity. Unlike structured applications, unstructured applications (e.g., Pick and Place applications) require the existence of a video camera system capable of identifying workobject shape and position and transmitting the coordinates to the robotic assembly systems. In this case, robots with compliant systems are used to carry out the assembly and video systems are used to check the positioning accuracy. Industrial robots used in automated production lines are programmed to use predefined trajectories for assembly operations [2; 3]. Using this programming method, robots can work with high precision, but they cannot prevent any unforeseen changes in the position of the manipulated components. These disadvantages can be corrected by integrating a robot vision system. Typically, industrial vision systems are mounted outside the working area in a predefined position and focus on a well-defined task such as measuring a gap, checking the correct position of a part, pattern recognition, detecting various surface defects, etc. This approach has several disadvantages, such as a limited field of view in certain assembly operations when the view is obstructed by the robot. Additionally, different tasks may require different cameras or different camera types, and, sometimes, it is necessary to move the robotic arm to clear the camera's field of view. Some of these disadvantages can be eliminated by using a mobile camera mounted on the robotic arm. This way, the robot arm is not obstructing the camera's field of view, and image acquisition can be performed when the robot moves along working paths. Using this approach, the assembly total time could be greatly improved. The only drawback of this method is related to the camera accuracy and calibration. Usually, camera calibration is performed before every measurement task. As previously mentioned, vision systems are particularly valuable in applications that are most likely to include uncertainties regarding part shape, position, and orientation. 3D cameras are more likely to be encountered in robotic tasks such as assembly or pick and place. [PERSON] et al. [7] presented the case of a pocket calculator assembly process. The vision system is used to identify the part position and ensure the reliable picking of components and correct placement within the assembly. Using the camera software, the coordinates of each component are extracted as it enters the workspace. For component placement within the assembly, the system compares the current coordinates of each part to the required coordinates and computes the offset. Vision systems are also widely used in mobile phone assembly. In a study by [PERSON] et al. [8], an application involving a camera mounted on a robot arm was explored. The assembly process was divided into four stages: camera calibration, part identification, picking, and placement. Components were delivered via a conveyor belt, with parts randomly positioned. After calibration, the camera was employed to determine the position and orientation of each workpiece using coordinate systems and offsets. The vision system also facilitated part placement within the assembly by utilizing object recognition and minimum rectangle fitting techniques. Accurate calibration ensures precise measurements and reliable analysis by correcting distortions. Camera calibration refers to both the intrinsic and extrinsic calibration.