Computer vision systems have demonstrated to be useful in applications of autonomous navigation, especially with the use of stereo vision systems for the three-dimensional mapping of the environment. This article presents a novel camera calibration method to improve the accuracy of stereo vision systems for three-dimensional point localization. The proposed camera calibration method uses the least square method to model the error caused by the image digitalization and the lens distortion. To obtain particular three-dimensional point coordinates, the stereo vision systems use the information of two images taken by two different cameras. Then, the system locates the two-dimensional pixel coordinates of the three-dimensional point in both images and coverts them into angles. With the obtained angles, the system finds the three-dimensional point coordinates through a triangulation process. The proposed camera calibration method is applied in the stereo vision systems, and a comparative analysis between the real and calibrated three-dimensional data points is performed to validate the improvements. Moreover, the developed method is compared with three classical calibration methods to analyze their advantages in terms of accuracy with respect to tested methods.

Nowadays, laser vision systems have allowed the development of different applications such as reverse engineering, manufacturing, navigation systems and, structural health monitoring (SHM). However, most of the machine vision systems for structural behavior analysis have restricted field of view, consume high levels of computational resources for image processing and require special illumination conditions to achieve lower error rates. Therefore, the purpose of this paper is to present a technical vision system (TVS) for structural behavior analysis using dynamic laser triangulation and k-Nearest Neighbor (k-NN) machine learning regression algorithm. The proposed vision system was tested in order to demonstrate the practicality of it, different deformations and displacements were analyzed over real structures in controlled laboratory conditions to assure the reproducibility of the experimentation. The TVS prototype proved to be a reliable option on SHM tasks, presenting balance between precision and operating ranges, without the issues aforementioned.

El estado del arte de los sistemas de posicionamiento ha demostrado que se requiere de redes complejas de sensores y de visión artificial para localizar con precisión objetos móviles en aplicaciones de navegación autónoma. Este documento presenta la metodología para el seguimiento de posición de objetos móviles utilizando Sistemas de Navegación Inercial con Filtro Kalman (INS/KF), en conjunto con la implementación de los algoritmos Zero Velocity Update y Zero Angle Rate Update (ZUPT/ZARUT). La principal contribución de este documento es la propuesta metodológica en la integración del INS-KF-ZUPT/ZARUT o IKZ al INS Strapdown re-alimentado, proporcionando propiedades restrictivas a los errores de deslice y mejorando significativamente la trayectoria, con una mayor definición al movimiento que fue expuesto el objeto. El IKZ propuesto fue probado con datos en bruto de una IMU MPU-9255 con el fin de analizar los diferentes resultados entre pruebas estáticas y movimientos lineales en los ejes X, Y y Z.

Laser vision systems have demonstrated to be useful in applications for autonomous navigation, structural health monitoring, manufacturing, reverse engineering, among others. A variant of these systems are the dynamic triangulation systems, where, these vision systems consist in a positioning laser, a scanning aperture and a fixed distance between them. The positioning laser points the laser beam over the surface to scan and it is detected by the scanning aperture. The purpose of this paper is to present the principle of operation of this system, the disadvantages when taking measures at different distances, and the implementation of the k-nearest neighbor algorithm (kNN) to solve these disadvantages.

Surface measurement systems (SMS) allow accurate measurements of surface geometry for three-dimensional computational models creation. There are cases where contact avoidance is needed; these techniques are known as non-contact surface measurement techniques. To perform non-contact surface measurements there are different operating modes and technologies, such as lasers, digital cameras, and integration of both. Each SMS is classified by its operation mode to get the data, so it can be divided into three basic groups: point-based techniques, line-based techniques, and area-based techniques. This chapter provides useful information about the different types of non-contact surface measurement techniques, theory, basic equations, system implementation, actual research topics, engineering applications, and future trends. This chapter is particularly valuable for students, teachers, and researchers that want to implement a vision system and need an introduction to all available options in order to use the most convenient for their purpose.

This paper presents a study of mathematical description for inertial navigation systems and integration of virtual sensors implementation. Virtual sensors allow to estimate quantities detecting events or changes in its environment, to calculate variables such velocity, position and attitude on rigid or mobile bodies of navigation systems. Recently, the creation of smaller devices and lightweight micro-machined electromechanical systems (MEMS) has opened the possibility to create artifacts that solve the positioning and orientation problems of navigation systems. This has increased the interest on topics of inertial navigation systems, typically in areas as artificial vision and robotics, especially on mobile robotics. The basic idea of mobile robotics is defined by transportation to reach an object or a specific position. Therefore it is necessary to provide environment value in real time for interpretation. This paper presents an implementation of navigation systems and a design of a Strapdown Inertial Navigation System (INS). Consequently, a simulation is conducted to verify and compare the performance between the implemented INS equations and a MATLAB SIMULINK 6DoF Euler Block. Furthermore an analysis of the simulation results is performed.