Diseño de una máquina cilindradora para madera para la elaboración de mangos de utensilios de limpieza

El presente trabajo desarrolla el “Diseño de una Máquina Cilindradora para Madera para la Elaboración de Mangos de Utensilios de Limpieza”, para lo cual, primeramente se seleccionaron las maderas para el proceso de producción, se realizó el diseño de forma definitivo de la máquina, se dimensionó el anillo giratorio y se comprobó su resistencia de diseño, luego se determinó la fuerza de corte en base a la dureza normal a las fibras que tienen estas maderas para calcular los esfuerzos que esta produce tanto en la cuchilla como en el porta cuchilla, se seleccionó la forma y el material de las cuchillas en base al desgaste y al esfuerzo de compresión a que están sometidas. Se calculó la velocidad de corte y de avance, para luego seleccionar el reductor de velocidad. En base a la fuerza de corte y la velocidad angular se determinó la potencia del motor, se escogió la parte más crítica del diseño de la estructura para seleccionar el perfil laminado que soporte la carga a que esta sometida, se seleccionaron los componentes mecánicos para su funcionamiento, finalmente se obtuvo el costo de construcción de la máquina y el precio del producto maquinado

An Analytical Solution to the IMU Initialization Problem for Visual-Inertial Systems

The fusion of visual and inertial measurements is becoming more and more popular in the robotics community since both sources of information complement well each other. However, in order to perform this fusion, the biases of the Inertial Measurement Unit (IMU) as well as the direction of gravity must be initialized first. Additionally, in case of a monocular camera, the metric scale is also needed. The most popular visual-inertial initialization approaches rely on accurate vision-only motion estimates to build a non-linear optimization problem that solves for these parameters in an iterative way. In this paper, we rely on the previous work in [1] and propose an analytical solution to estimate the accelerometer bias, the direction of gravity and the scale factor in a maximum-likelihood framework. This formulation results in a very efficient estimation approach and, due to the non-iterative nature of the solution, avoids the intrinsic issues of previous iterative solutions. We present an extensive validation of the proposed IMU initialization approach and a performance comparison against the state-of-the-art approach described in [2] with real data from the publicly available EuRoC dataset, achieving comparable accuracy at a fraction of its computational cost and without requiring an initial guess for the scale factor. We also provide a C++ open source reference implementation

Cytomegalovirus drug resistance mutations in transplant recipients with suspected resistance

Resistant CMV infections are challenging complications after SOT and HSCT. Prompt recognition of ARMs is imperative for appropriate therapy. 108 plasma samples from 96 CMV + transplant recipients with suspected resistance were analysed in CNM in a retrospective nationwide study from January 2018 to July 2022 for resistance genotyping. ARMs in UL97 and UL54 were found in 26.87% (18/67) and 10.60% (7/66) of patients, respectively. Patients' ARM distribution in UL97 was as follows: L595S n = 3; L595S/M460I n = 1; L595S/N510S n = 1; L595W n = 1; C603W n = 4; A594V n = 3; A594E n = 1; C607Y n = 1; L397R/T409M/H411L/M460I n = 1; L397I n = 1; H520Q n = 1; four patients showed ARMs in UL54 as well (F412C n = 1; T503I n = 2; P522S n = 1), whereas three patients exhibited ARMs in UL54 only (L501I/T503I/L516R/A834P n = 1; A987G n = 2). L516R in UL54 and L397R/I and H411L in UL97 have been found for the first time in a clinical sample. L595S/W was the most prevalent ARM found to lend resistance to GCV. In UL54 all ARMs lent resistance to GCV and CDV. In addition, A834P, found in one patient, also lent resistance to FOS. CMV load did not differ significantly in patients with or without ARMs, and no differences were found either between patients with ARMs in UL97 or in UL97 and UL54. Despite extensive use of classical antivirals for the treatment of CMV infection after HSCT and SOT, ARMs occurred mainly in viral UL97 kinase, which suggests that CDV and mostly FOS continue to be useful alternatives to nucleoside analogues after genotypic detection of ARMs.This work was supported by a grant from Instituto de Salud Carlos III. AESI2021 PCIII00011-MPY434/2021. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.S

Detección de Lugares con Camaras RGB-D. Aplicación a Cierre de Bucles en SLAM

En este trabajo se propone un método que combina descriptores de imágenes de intensidad y de profundidad para detectar de manera robusta el problema de cierre de bucle en SLAM. La robustez del método, proporcionada por el empleo conjunto de información de diversa naturaleza, permite detectar lugares revisitados en situaciones donde m´etodos basados solo en intensidad o en profundidad presentan dificultades (p.e. condiciones de iluminación deficientes, o falta de geometría). Además, se ha diseñado el métod cuenta su eficiencia, recurriendo para ello al detector FAST para extraer las características de las observaciones y al descriptor binario BRIEF. La detección de bucle se completa con una Bolsa de Palabras binarias. El rendimiento del método propuesto se ha evaluado en condiciones reales, obteniéndose resultados muy satisfactorios.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Intrinsic calibration of depth cameras for mobile robots using a radial laser scanner

Depth cameras, typically in RGB-D configurations, are common devices in mobile robotic platforms given their appealing features: high frequency and resolution, low price and power requirements, among others. These sensors may come with significant, non-linear errors in the depth measurements that jeopardize robot tasks, like free-space detection, environment reconstruction or visual robot-human interaction. This paper presents a method to calibrate such systematic errors with the help of a second, more precise range sensor, in our case a radial laser scanner. In contrast to what it may seem at first, this does not mean a serious limitation in practice since these two sensors are often mounted jointly in many mobile robotic platforms, as they complement well each other. Moreover, the laser scanner can be used just for the calibration process and get rid of it after that. The main contributions of the paper are: i) the calibration is formulated from a probabilistic perspective through a Maximum Likelihood Estimation problem, and ii) the proposed method can be easily executed automatically by mobile robotic platforms. To validate the proposed approach we evaluated for both, local distortion of 3D planar reconstructions and global shifts in the measurements, obtaining considerably more accurate results. A C++ open-source implementation of the presented method has been released for the benefit of the community.Research projects WISER (DPI2017-84827-R), funded by the Spanish Government and the European Regional Development’s Funds (FEDER), MoveCare (ICT-26-2016b-GA-732158), funded by the European H2020 program, the European Social Found through the Youth Employment Initiative for the promotion of young researchers, and a postdoc contract from the IPPIT program of the University of Malaga. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

The UMA-VI dataset: Visual–inertial odometry in low-textured and dynamic illumination environments

Artículo de dataset. Disponible en http://mapir.uma.es/work/uma-visual-inertial-datasetThis article presents a visual–inertial dataset gathered in indoor and outdoor scenarios with a handheld custom sensor rig, for over 80 min in total. The dataset contains hardware-synchronized data from a commercial stereo camera (Bumblebee®2), a custom stereo rig, and an inertial measurement unit. The most distinctive feature of this dataset is the strong presence of low-textured environments and scenes with dynamic illumination, which are recurrent corner cases of visual odometry and simultaneous localization and mapping (SLAM) methods. The dataset comprises 32 sequences and is provided with ground-truth poses at the beginning and the end of each of the sequences, thus allowing the accumulated drift to be measured in each case. We provide a trial evaluation of five existing state-of-the-art visual and visual–inertial methods on a subset of the dataset. We also make available open-source tools for evaluation purposes, as well as the intrinsic and extrinsic calibration parameters of all sensors in the rig. The dataset is available for download at http://mapir.uma.es/work/uma-visual-inertial-datase

Data‐Driven Low‐Frequency Oscillation Event Detection Strategy for Railway Electrification Networks

Low-frequency oscillations (LFO) occur in railway electrification systems due to the incorporation of new trains with switching converters. As a result, the increased harmonic content can cause catenary stability problems under certain conditions. Most of the research published on this topic to date is focused on modelling the event and analysing it using frequency spectrums. However, in recent years, due to the new technologies linked to Big Data (BD) and data mining (DM), a new opportunity to study and detect LFO events by means of machine-learning (ML) methods has emerged. Trains continuously collect data from the most important catenary variables, which offers new resources for analysing this type of event. Therefore, this article presents the design and implementation of a data-driven LFO event detection strategy for AC railway network scenarios. Compared to previous investigations, a new approach to analyse and detect LFO events, based on field data and ML, is presented. To obtain the most appropriate detection approach for the context of this application, on the one hand, this investigation includes a comparison of machine-learning algorithms (support vector machine, logistic regression, random forest, k-nearest neighbours, naïve Bayes) which have been trained with real field data. On the other hand, an analysis of key parameters and features to optimize event detection is also included. Thus, the most significant result of this work is the high metric values of the solution, reaching values above 97% in accuracy and 93% in F-1 score with the random forest algorithm. In addition, the applicability and training of data-driven methods with real field data are demonstrated. This automatic detection strategy can help with speeding up and improving LFO detection tasks that used to be performed manually. Finally, it is worth mentioning that this research has been structured based on the CRISP-DM methodology, established as the de facto approach for industrial DM projects

Urban monitoring of unpleasant odors with a handheld electronic nose

This work describes a real application of artificial olfaction where a handheld electronic nose was used as a validation tool for a chemical spillage in a southern town in Spain. The objective was to check if the palliative and precautionary measurements taken by the authorities were working effectively, removing the elevated values of phenol that were detected in a wide area of the municipality of Coria del R´ıo (Spain). To this end, a gas distribution map of the affected neighborhoods was built with a portable electronic nose taking into consideration the likely presence of other volatile chemicals in the area. For the latter, we trained a volatile chemical classifier with a dataset of typical urban smells that we wanted to remove from the results (e.g. traffic emissions, garbage, fresh-air), as well as with a specific air-born phenol dataset. Results demonstrated that the palliative measures were in general satisfactory, but some hot-spots were located where the intensity of phenol-like smell was still higher than desired. Advice was given to the local authorities to doublecheck these locations with analytical gas-monitoring equipment.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Proyecto de Excelencia de la Junta de Andalucía TEP2012-53