A proposal to estimate the motion of an underwater vehicle through visual mosaicking

This thesis proposes a solution to the problem of estimating the motion of an Unmanned Underwater Vehicle (UUV). Our approach is based on the integration of the incremental measurements which are provided by a vision system. When the vehicle is close to the underwater terrain, it constructs a visual map (so called "mosaic") of the area where the mission takes place while, at the same time, it localizes itself on this map, following the Concurrent Mapping and Localization strategy. The proposed methodology to achieve this goal is based on a feature-based mosaicking algorithm. A down-looking camera is attached to the underwater vehicle. As the vehicle moves, a sequence of images of the sea-floor is acquired by the camera. For every image of the sequence, a set of characteristic features is detected by means of a corner detector. Then, their correspondences are found in the next image of the sequence. Solving the correspondence problem in an accurate and reliable way is a difficult task in computer vision. We consider different alternatives to solve this problem by introducing a detailed analysis of the textural characteristics of the image. This is done in two phases: first comparing different texture operators individually, and next selecting those that best characterize the point/matching pair and using them together to obtain a more robust characterization. Various alternatives are also studied to merge the information provided by the individual texture operators. Finally, the best approach in terms of robustness and efficiency is proposed. After the correspondences have been solved, for every pair of consecutive images we obtain a list of image features in the first image and their matchings in the next frame. Our aim is now to recover the apparent motion of the camera from these features. Although an accurate texture analysis is devoted to the matching pro-cedure, some false matches (known as outliers) could still appear among the right correspon-dences. For this reason, a robust estimation technique is used to estimate the planar transformation (homography) which explains the dominant motion of the image. Next, this homography is used to warp the processed image to the common mosaic frame, constructing a composite image formed by every frame of the sequence. With the aim of estimating the position of the vehicle as the mosaic is being constructed, the 3D motion of the vehicle can be computed from the measurements obtained by a sonar altimeter and the incremental motion computed from the homography. Unfortunately, as the mosaic increases in size, image local alignment errors increase the inaccuracies associated to the position of the vehicle. Occasionally, the trajectory described by the vehicle may cross over itself. In this situation new information is available, and the system can readjust the position estimates. Our proposal consists not only in localizing the vehicle, but also in readjusting the trajectory described by the vehicle when crossover information is obtained. This is achieved by implementing an Augmented State Kalman Filter (ASKF). Kalman filtering appears as an adequate framework to deal with position estimates and their associated covariances. Finally, some experimental results are shown. A laboratory setup has been used to analyze and evaluate the accuracy of the mosaicking system. This setup enables a quantitative measurement of the accumulated errors of the mosaics created in the lab. Then, the results obtained from real sea trials using the URIS underwater vehicle are shown.

Student self-assessment a feedback seeking strategy through competence evaluation

There is a body of literature that suggests that student self-assessment is a main goal in higher education (Boud et al., 1995; Tan, 2008); moreover new forms of work organization require a high level of skills and competences. The efforts to deal with competence gaps could be developed at many levels, such as employers, educational institutions, individuals and public agents. Employers could put into practice competence development programs to moderate these gaps. Educational institutions can restructure the curriculum to support students in attaining the competences that are essential in the labour market. Individuals themselves may deploy their resources (time and money) in general or specific competence training. Further, government agencies could fund competence promotion programs. Such challenges for education drive change in learning curricula and method, to properly include the competences required for developing global workers who can move beyond basic competence, to enhanced flexibility and adaptability. In performance assessment methods, there is a shift from the traditional exam-based assessments to more innovative task assessment, which considers performance in multiple different tasks carry out by students. ICTs make it technologically feasible to carry out a complete and complex selfassessment of competences, which provides immediate results to students or other recipients. In the case of students, the evaluation of competences is relevant as developing competences is part - if not all - of the objectives of education. Therefore, it is an important element of the quality of educational organizations (e.g., universities), and of their organizational success. Further, educational organizations may put special emphasis on some differentiating competences, which can be a means of positioning and differentiation from competitors. Competence assessment is an instrument to make students conscious of their strengths and weaknesses, leading to higher motivation to develop their own learning career

A Camera-Projector System for Robot Positioning by Visual Servoing

Positioning a robot with respect to objects by using data provided by a camera is a well known technique called visual servoing. In order to perform a task, the object must exhibit visual features which can be extracted from different points of view. Then, visual servoing is object-dependent as it depends on the object appearance. Therefore, performing the positioning task is not possible in presence of nontextured objets or objets for which extracting visual features is too complex or too costly. This paper proposes a solution to tackle this limitation inherent to the current visual servoing techniques. Our proposal is based on the coded structured light approach as a reliable and fast way to solve the correspondence problem. In this case, a coded light pattern is projected providing robust visual features independently of the object appearance

An approach to visual servoing based on coded light

Positioning a robot with respect to objects by using data provided by a camera is a well known technique called visual servoing. In order to perform a task, the object must exhibit visual features which can be extracted from different points of view. Then, visual servoing is object-dependent as it depends on the object appearance. Therefore, performing the positioning task is not possible in presence of non-textured objects or objects for which extracting visual features is too complex or too costly. This paper proposes a solution to tackle this limitation inherent to the current visual servoing techniques. Our proposal is based on the coded structured light approach as a reliable and fast way to solve the correspondence problem. In this case, a coded light pattern is projected providing robust visual features independently of the object appearance

Visual management of sags and incidents gathered in distribution substations for power quality management

Monitor a distribution network implies working with a huge amount of data coining from the different elements that interact in the network. This paper presents a visualization tool that simplifies the task of searching the database for useful information applicable to fault management or preventive maintenance of the network