Introducing Sustainability in a Robotic Engineering Degree: A Case Study

This paper describes a group activity concerning the topic of climate change, designed to introduce the concepts of sustainable development into a Robotic Engineering degree. The purpose of this activity was to make students reflect about the impact of their work on the planet as future engineers by asking them to design an environmentally friendly robot that also integrated social and economic aspects, covering the three dimensions of sustainability in this way. Students were surveyed in order to study different aspects of their commitment, attitudes, practices, and motivation towards sustainability. In addition to the overall analysis of the survey, three specific studies were carried out with the aim of comparing the responses of different population groups: (i) Students who completed the proposed assignment and students who did not, (ii) female and male students, and (iii) roles played in the assignment. The results of the analysis revealed the high commitment of the students with respect to sustainability, but also a lack of active participation and awareness of their impact as future engineers. The activity was not only a way to introduce sustainability concepts, but in many cases, it also became a motivation for the participants, especially for the female students.This research work was partially funded by the Spanish Government through project RTI2018-094653-B-C22

Numerical resolution of Emden's equation using Adomian polynomials

Purpose: In this paper the authors aim to show the advantages of using the decomposition method introduced by Adomian to solve Emden's equation, a classical non‐linear equation that appears in the study of the thermal behaviour of a spherical cloud and of the gravitational potential of a polytropic fluid at hydrostatic equilibrium. Design/methodology/approach: In their work, the authors first review Emden's equation and its possible solutions using the Frobenius and power series methods; then, Adomian polynomials are introduced. Afterwards, Emden's equation is solved using Adomian's decomposition method and, finally, they conclude with a comparison of the solution given by Adomian's method with the solution obtained by the other methods, for certain cases where the exact solution is known. Findings: Solving Emden's equation for n in the interval [0, 5] is very interesting for several scientific applications, such as astronomy. However, the exact solution is known only for n=0, n=1 and n=5. The experiments show that Adomian's method achieves an approximate solution which overlaps with the exact solution when n=0, and that coincides with the Taylor expansion of the exact solutions for n=1 and n=5. As a result, the authors obtained quite satisfactory results from their proposal. Originality/value: The main classical methods for obtaining approximate solutions of Emden's equation have serious computational drawbacks. The authors make a new, efficient numerical implementation for solving this equation, constructing iteratively the Adomian polynomials, which leads to a solution of Emden's equation that extends the range of variation of parameter n compared to the solutions given by both the Frobenius and the power series methods.This work has been supported by the Ministerio de Ciencia e Innovación, project TIN2009-10581

Learning Probabilistic Features for Robotic Navigation Using Laser Sensors

SLAM is a popular task used by robots and autonomous vehicles to build a map of an unknown environment and, at the same time, to determine their location within the map. This paper describes a SLAM-based, probabilistic robotic system able to learn the essential features of different parts of its environment. Some previous SLAM implementations had computational complexities ranging from O(Nlog(N)) to O(N2), where N is the number of map features. Unlike these methods, our approach reduces the computational complexity to O(N) by using a model to fuse the information from the sensors after applying the Bayesian paradigm. Once the training process is completed, the robot identifies and locates those areas that potentially match the sections that have been previously learned. After the training, the robot navigates and extracts a three-dimensional map of the environment using a single laser sensor. Thus, it perceives different sections of its world. In addition, in order to make our system able to be used in a low-cost robot, low-complexity algorithms that can be easily implemented on embedded processors or microcontrollers are used.This work has been supported by the Spanish Ministerio de Ciencia e Innovación (www.micinn.es), project TIN2009-10581

Application of Texture Descriptors to Facial Emotion Recognition in Infants

The recognition of facial emotions is an important issue in computer vision and artificial intelligence due to its important academic and commercial potential. If we focus on the health sector, the ability to detect and control patients’ emotions, mainly pain, is a fundamental objective within any medical service. Nowadays, the evaluation of pain in patients depends mainly on the continuous monitoring of the medical staff when the patient is unable to express verbally his/her experience of pain, as is the case of patients under sedation or babies. Therefore, it is necessary to provide alternative methods for its evaluation and detection. Facial expressions can be considered as a valid indicator of a person’s degree of pain. Consequently, this paper presents a monitoring system for babies that uses an automatic pain detection system by means of image analysis. This system could be accessed through wearable or mobile devices. To do this, this paper makes use of three different texture descriptors for pain detection: Local Binary Patterns, Local Ternary Patterns, and Radon Barcodes. These descriptors are used together with Support Vector Machines (SVM) for their classification. The experimental results show that the proposed features give a very promising classification accuracy of around 95% for the Infant COPE database, which proves the validity of the proposed method.This work has been partially supported by the Spanish Research Agency (AEI) and the European Regional Development Fund (FEDER) under project CloudDriver4Industry TIN2017-89266-R, and by the Conselleria de Educación, Investigación, Cultura y Deporte, of the Community of Valencia, Spain, within the program of support for research under project AICO/2017/134

Trajectory-Based Morphological Operators: A Model for Efficient Image Processing

Mathematical morphology has been an area of intensive research over the last few years. Although many remarkable advances have been achieved throughout these years, there is still a great interest in accelerating morphological operations in order for them to be implemented in real-time systems. In this work, we present a new model for computing mathematical morphology operations, the so-called morphological trajectory model (MTM), in which a morphological filter will be divided into a sequence of basic operations. Then, a trajectory-based morphological operation (such as dilation, and erosion) is defined as the set of points resulting from the ordered application of the instant basic operations. The MTM approach allows working with different structuring elements, such as disks, and from the experiments, it can be extracted that our method is independent of the structuring element size and can be easily applied to industrial systems and high-resolution images

Face Detection Based on Skin Color Segmentation Using Fuzzy Entropy

Face detection is the first step of any automated face recognition system. One of the most popular approaches to detect faces in color images is using a skin color segmentation scheme, which in many cases needs a proper representation of color spaces to interpret image information. In this paper, we propose a fuzzy system for detecting skin in color images, so that each color tone is assumed to be a fuzzy set. The Red, Green, and Blue (RGB), the Hue, Saturation and Value (HSV), and the YCbCr (where Y is the luminance and Cb,Cr are the chroma components) color systems are used for the development of our fuzzy design. Thus, a fuzzy three-partition entropy approach is used to calculate all of the parameters needed for the fuzzy systems, and then, a face detection method is also developed to validate the segmentation results. The results of the experiments show a correct skin detection rate between 94% and 96% for our fuzzy segmentation methods, with a false positive rate of about 0.5% in all cases. Furthermore, the average correct face detection rate is above 93%, and even when working with heterogeneous backgrounds and different light conditions, it achieves almost 88% correct detections. Thus, our method leads to accurate face detection results with low false positive and false negative rates.This work has been supported by the Ministerio de Economía y Competitividad (Spain), Project TIN2013-40982-R. Project co-financed with FEDER funds

Partial Product Reduction based on Look-Up Tables

In this paper a new technique for partial product reduction based on the use of look-up tables for efficient processing is presented. We describe how to construct counter devices with pre-calculated data and their subsequent integration into the whole operation. The development of reduction trees organizations for this kind of devices uses the inherent integration benefits of computer memories and offers an alternative implementation to classic operation methods. Therefore, in our experiments we compare our implementation model with CMOS technology model in homogeneous terms

Un sistema de bajo coste para la ayuda al prediagnóstico del temblor humano

Human tremor can be defined as a somewhat rhythmic and quick movement of one or more body parts. In some people, it is a symptom of a neurological disorder. From the mathematical point of view, human tremor can be defined as a weighted contribution of different sinusoidal signals which causes oscillations of some parts of the body. This sinusoidal is repeated over time, but its amplitude and frequency change slowly. This is why amplitude and frequency are considered important factors in the tremor characterization, and thus for its diagnosis. In this paper, a tool for the prediagnosis of the human tremor is presented. This tool uses a low cost device (<$40) and allows to compute the main factors of the human tremor accurately. Real cases have been tested using the algorithms developed in this investigation. The patients suffered from different tremor severities, and the components of amplitude and frequency were computed using a series of tests. These additional measures will help the experts to make better diagnoses allowing them to focus on specific stages of the test or get an overview of these tests. From the experimental, we stated that not all tests are valid for every patient to give a diagnosis. Guided by years of experience, the expert will decide which test or set of tests are the most appropriate for a patient.El temblor humano puede definirse como un movimiento rápido y, en cierta manera, rítmico de una o más partes del cuerpo. En algunas personas, este movimiento puede ser un síntoma de alguna alteración a nivel neurológico. Desde el punto de vista matemático, el temblor humano puede ser definido como una suma ponderada de diferentes señales sinusoidales que causan oscilaciones de algunas partes del cuerpo. Esta sinusoide se repite en el tiempo pero su amplitud y frecuencia cambian lentamente. Por esta razón, la amplitud y la frecuencia son consideradas factores importantes en la clasificación del temblor y por tanto útiles en su diagnóstico. En este artículo, se presenta una herramienta de ayuda al diagnóstico del temblor humano. Esta herramienta usa un dispositivo hardware de bajo coste (<$40) y permite calcular las principales componentes de esta sinusoide asociada al temblor de una manera precisa. Como casos de estudio se presentan su aplicación a dos casos reales para probar la bondad de los algoritmos desarrollados. Los casos muestran pacientes que sufrían temblores con distinta severidad y que han realizado una serie de tests con el dispositivo para que el sistema calculara las principales componentes del temblor. Estas medidas aportadas por el sistema ayudarían en un futuro a los expertos a tomar decisiones más precisas permitiéndoles centrarse en determinadas fases del test o la realización de tests más específicos para evaluar mejor las características propias del temblor del paciente. De la experimentación realizada podemos afirmar que no todos los tests son válidos para el diagnóstico para todos los pacientes. Será finalmente la experiencia del profesional el que decidirá finalmente qué test o conjunto de tests son los más apropiados para cada paciente

Energy-Efficient Swarm Behavior for Indoor UAV Ad-Hoc Network Deployment

Building an ad-hoc network in emergency situations can be crucial as a primary tool or even when used prior to subsequent operations. The use of mini and micro Unmanned Aerial Vehicles (UAVs) is increasing because of the wide range of possibilities they offer. Moreover, they have been proven to bring sustainability to many applications, such as agriculture, deforestation and wildlife conservation, among others. Therefore, creating a UAV network for an unknown environment is an important task and an active research field. In this article, a mobility model for the creation of ad-hoc networks using UAVs will be presented. This model will be based on pheromones for robust navigation. We will focus mainly on developing energy-efficient behavior, which is essential for this type of vehicle. Although there are in the literature several models of mobility for ad-hoc network creation, we find that either they are not adapted to the specific energy requirements of UAVs or the proposed motion models are unrealistic or not sufficiently robust for final implantation. We will present and analyze the operation of a distributed swarm behavior able to create an ad-hoc network. Then, an analytical model of the swarm energy consumption will be proposed. This model will provide a mechanism to effectively predict the energy consumption needed for the deployment of the network prior to its implementation. Determining the use of the mobility behavior is a requirement to establish and maintain a communication channel for the required time. Finally, this analytical model will be experimentally validated and compared to the Random Waypoint (RWP) mobility strategy.This work was partially supported by the Ministerio de Economía y Competitividad (Spain), project TIN2013-40982-R, the FEDER funds and the “Red de Investigación en el uso del aprendizaje colaborativo para la adquisición de competencias básicas. El caso Erasmus+ EUROBOTIQUE”, Red ICE3701, curso 2016–2017