Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- Robotic-computer vision system for 3D welding trajectories(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2021-06) Rodríguez Suárez, Jesús Braian; GOMEZ ESPINOSA, ALFONSO; 57957; Gómez Espinosa, Alfonso; emipsanchez; Escobedo Cabello, Jesús Arturo; Swenson Durie, Rick Leigh; Escuela de Ingeniería y Ciencias; Campus Monterrey; Cuan Urquizo, EnriqueThe necessity for intelligent welding robots that meet the demand in the real industrial production, according to the objectives of Industry 4.0, has been supported thanks to the rapid development of computer vision and the use of new technologies. In order to improve the efficiency in weld location for industrial robots, this work focuses on trajectory extraction based on color features identification over three-dimensional surfaces acquired with a depth-RGB sensor. The system is planned to be used with a low-cost Intel RealSense D435 sensor for the reconstruction of 3D models based on stereo vision and the built-in color sensor to quickly identify the objective trajectory, since the parts to be welded are previously marked with different colors, indicating the locations of the welding trajectories to be followed. This work focuses on the use of point cloud and a color data to obtain a three-dimensional model of the workpiece with which the points of the target trajectory are segmented by color thresholds in the RGB and the HSV color space, finally a spline cubic interpolation algorithm is implemented to obtain a smooth trajectory. Experimental results show that the RMSE error for V-type butt-joint path extraction is under 1.1 mm and below 0.6 mm for a straight butt joint, showing a suitable system for welding bead of various shapes and materials. It is important to note that to demonstrate its application in a robotic environment, the expected results will be presented in virtual environments created on the Robot Operating System (ROS) software.
- Development of pilot system of artificial vision for the acquisition of a point cloud using 3D vision technologies(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2015-05) Huamanchahua Canchanya, Deyby Maycol; HUAMANCHAHUA CANCHANYA, DEYBY MAYCOL; 550903; Guedea Elizalde, Federico; hermlugo, emipsanchez; Escuela de Ingeniería y Ciencias; Campus MonterreyOne of the goals of artificial vision is to permit that a computer analyzed a real scene, as if a person does. To achieve this purpose it is necessary to create a 3D model of that scene using a reconstruction. 3D reconstruction is the process by which the shape and the appearance of a three dimensional object or scene from a volume by analyzing the digital information provided by different types of sensors is recovered. The sensors may be passive (not interact with the object, such as different types of cameras based on the light of the visible spectrum) or active (the interaction comes from an object in response reflected waveform that is captured by the device). On the other hand, 3D reconstruction has several applications, such as robot navigation, allowing it to know in what part of the scene is located and being able to plan its movements without needing human help. It is also useful for determining quantities such as distances, areas or volumes, which may be applicable for quality controls as it can verify the processes and areas of objects that are being manufactured. Another application is the digitization of historical monuments and museums to create virtual tours, which users can access from the Internet. Besides, 3D reconstruction are given in the area of biomedical engineering. Anatomical reconstruction from medical images such as MRI structures has become an important tool in medical diagnosis and therapy planning and surgical procedures. Apart from the above applications, 3D reconstruction has many more applications in different areas. These are some of the many uses of three-dimensional reconstruction and for this reason there is a need to develop this project. The purpose of this project is to do an algorithm that, based on images, obtain a points cloud of an object. To achieve this aim, in first place; the different techniques developed about 3D reconstruction were studied in order to know the different possibilities. Some of these techniques such as telemetry laser, stereo vision, flight time or structured light which obtain models that are very accurate or not, but with the disadvantage of using expensive equipment in some cases. In second place, perform camera calibration using a calibration method. Finally, get the point cloud object to rebuild. This work shows that an algorithm can be done to reconstruct an object in three-dimensions, leaving for future developments the optimization for all kinds of objects. In addition it is an important basis for future developments, as many different techniques for image analysis were studied and compared.