ALBERT

Description: Methods in operational hydrology for real-time flash-flood forecasting need to be simple enough to match requirements of real-time system management. For this reason, hydrologic routing methods are widely used in river engineering. Among them, the popular Muskingum method is the most extended one, due to its simplicity and parsimonious formulation involving only two parameters. In the present application, two simple conceptual models with an error correction scheme were used. They were applied in practice to a mountain catchment located in the central Pyrenees (North of Spain), where occasional flash flooding events take place. Several relevant historical flood events have been selected for calibration and validation purposes. The models were designed to produce real-time predictions at the downstream gauge station, with variable lead times during a flood event. They generated accurate estimates of forecasted discharges at the downstream end of the river reach. For the validation data set and 2 h lead time, the estimated Nash-Sutcliffe coefficient was 0.970 for both models tested. The quality of the results, together with the simplicity of the formulations proposed, suggests an interesting potential for the practical use of these schemes for operational hydrology purposes.

Description: The paper presents how single-model robotized manufacturing lines are rebalanced to save energy. The key idea is to eliminate idle time that each robot has by means of adjusting the velocity. To do so, the proposed technique predicts the idle time for the next cycle time based on miniterm 4.0. This system measures in real-time the sub-cycle times (mini-terms) with the goal to detect disturbances that predict future machine failures. Mini-terms are used to compute the idle time and the allowed velocity reduction for the Industrial Robot without losing productivity. The proposed predictive control technique has been tested in a real production line located at Ford Almussafes plant (Valencia). The line has six stations where each one has an industrial robot. It is connected to miniterm 4.0 to perform a real test. A discussion, limitations of the technique, future implementations and conclusions are shown at the end of this paper.

Description: Over the last years, mobile robot platforms are having a key role in education worldwide. Among others, LEGO Robots and MATLAB/Simulink are being used mainly in universities to improve the teaching experience. Most LEGO systems used in the literature are based on NXT, as the EV3 version is relatively recent. In contrast to the previous versions, the EV3 allows the development of real-time applications for teaching a wide variety of subjects as well as conducting research experiments. The goal of the research presented in this paper was to develop and validate a novel real-time educational platform based on the MATLAB/Simulink package and the LEGO EV3 brick for academic use in the fields of robotics and computer science. The proposed framework is tested here in different university teaching situations and several case studies are presented in the form of interactive projects developed by students. Without loss of generality, the platform is used for testing different robot path planning algorithms. Classical algorithms like rapidly-exploring random trees or artificial potential fields, developed by robotics researchers, are tested by bachelor students, since the code is freely available on the Internet. Furthermore, recent path planning algorithms developed by the authors are also tested in the platform with the aim of detecting the limits of its applicability. The restrictions and advantages of the proposed platform are discussed in order to enlighten future educational applications.

Description: A necessity in the design of a path planning algorithm is to account for the environment. If the movement of the mobile robot is through a dynamic environment, the algorithm needs to include the main constraint: real-time collision avoidance. This kind of problem has been studied by different researchers suggesting different techniques to solve the problem of how to design a trajectory of a mobile robot avoiding collisions with dynamic obstacles. One of these algorithms is the artificial potential field (APF), proposed by O. Khatib in 1986, where a set of an artificial potential field is generated to attract the mobile robot to the goal and to repel the obstacles. This is one of the best options to obtain the trajectory of a mobile robot in real-time (RT). However, the main disadvantage is the presence of deadlocks. The mobile robot can be trapped in one of the local minima. In 1988, J.F. Canny suggested an alternative solution using harmonic functions satisfying the Laplace partial differential equation. When this article appeared, it was nearly impossible to apply this algorithm to RT applications. Years later a novel technique called proper generalized decomposition (PGD) appeared to solve partial differential equations, including parameters, the main appeal being that the solution is obtained once in life, including all the possible parameters. Our previous work, published in 2018, was the first approach to study the possibility of applying the PGD to designing a path planning alternative to the algorithms that nowadays exist. The target of this work is to improve our first approach while including dynamic obstacles as extra parameters.

Description: A novel algorithm called the Proper Generalized Decomposition (PGD) is widely used by the engineering community to compute the solution of high dimensional problems. However, it is well-known that the bottleneck of its practical implementation focuses on the computation of the so-called best rank-one approximation. Motivated by this fact, we are going to discuss some of the geometrical aspects of the best rank-one approximation procedure. More precisely, our main result is to construct explicitly a vector field over a low-dimensional vector space and to prove that we can identify its stationary points with the critical points of the best rank-one optimization problem. To obtain this result, we endow the set of tensors with fixed rank-one with an explicit geometric structure.

Description: The COVID-19 pandemic and its social implications generate adverse psychological effects that affect success in education where educational methodologies are not ready to overcome the problem. This article presents the design and evaluation of a gamification activity, the Escape Room, applied to the subjects in Pharmacy and Nursing. The objective of using the Escape Room is to reduce the impact that COVID-19 has on students’ academic performance due to the psychological effects and the change in educational modality with which the vast majority of activities are carried out online. The Escape Room presented in this article is based on the search for a scientist who is fleeing with the COVID-19 vaccine around the world and the students have to find it by passing tests and missions related to mathematics. Due to the COVID measures imposed by the university, where double presentiality was imposed, the proposed Escape Room has the peculiarity of being designed in dual format, that is, allowing students to connect in face-to-face mode, online, or a mixture of both, depending on the maximum capacity of the classroom, the number of positive cases in the group, quarantines, etc. As a result, a great impact is shown on the initial perception of students towards mathematics and a null impact of the COVID-19 effect on the academic performance of students.