Human and Object Recognition with a High-resolution tactile sensor

This paper 1 describes the use of two artificial intelligence methods for object recognition via pressure images from a high-resolution tactile sensor. Both meth- ods follow the same procedure of feature extraction and posterior classification based on a supervised Supported Vector Machine (SVM). The two approaches differ on how features are extracted: while the first one uses the Speeded-Up Robust Features (SURF) descriptor, the other one employs a pre-trained Deep Convolutional Neural Network (DCNN). Besides, this work shows its applica- tion to object recognition for rescue robotics, by distinguishing between differ- ent body parts and inert objects. The performance analysis of the proposed methods is carried out with an experiment with 5-class non-human and 3-class human classification, providing a comparison in terms of accuracy and compu-tational load. Finally, it is discussed how feature-extraction based on SURF can be obtained up to five times faster compared to DCNN. On the other hand, the accuracy achieved using DCNN-based feature extraction can be 11.67% superior to SURF.Proyecto DPI2015-65186-R European Commission under grant agreement BES-2016-078237. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Mobile Robot Lab Project to Introduce Engineering Students to Fault Diagnosis in Mechatronic Systems

This document is a self-archiving copy of the accepted version of the paper. Please find the final published version in IEEEXplore: http://dx.doi.org/10.1109/TE.2014.2358551This paper proposes lab work for learning fault detection and diagnosis (FDD) in mechatronic systems. These skills are important for engineering education because FDD is a key capability of competitive processes and products. The intended outcome of the lab work is that students become aware of the importance of faulty conditions and learn to design FDD strategies for a real system. To this end, the paper proposes a lab project where students are requested to develop a discrete event dynamic system (DEDS) diagnosis to cope with two faulty conditions in an autonomous mobile robot task. A sample solution is discussed for LEGO Mindstorms NXT robots with LabVIEW. This innovative practice is relevant to higher education engineering courses related to mechatronics, robotics, or DEDS. Results are also given of the application of this strategy as part of a postgraduate course on fault-tolerant mechatronic systems.This work was supported in part by the Spanish CICYT under Project DPI2011-22443

Transfer learning or design a custom CNN for tactile object recognition

International Workshop on Robotac: New Progress in Tactile Perception and Learning in RoboticsNovel tactile sensors allow treating pressure lectures as standard images due to its highresolution. Therefore, computer vision algorithms such as Convolutional Neural Networks (CNNs) can be used to identify objects in contact. In this work, a high-resolution tactile sensor has been attached to a robotic end-effector to identify objects in contact. Moreover, two CNNs-based approaches have been tested in an experiment of classification of pressure images. These methods include a transfer learning approach using a pre-trained CNN on an RGB images dataset and a custom-made CNN trained from scratch with tactile information. A comparative study of performance between them has been carried out.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Spanish project DPI2015-65186-R, the European Commission under grant agreement BES-2016-078237, the educational project PIE-118 of the University of Malag

Clasificación de información táctil para la detección de personas

Este artículo presenta el diseño de un efector final táctil y la aplicación de técnicas de inteligencia artificial para la detección de personas mediante un brazo manipulador ligero de 6 grados de libertad. Este efector está compuesto por un sensor táctil de alta resolución que permite obtener imágenes de presión. El sistema extrae información háptica en situaciones de catástrofe en las que, generalmente, existe baja visibilidad, con el propósito de evaluar el estado de las víctimas en función de la urgencia de atención (triaje). Se han implementado dos métodos de inteligencia artificial para clasificar imágenes obtenidas por el sensor táctil, distinguiendo los contactos con personas de objetos inertes en escenarios de desastre. Cada método dispone de un extractor de características de imágenes de presión y un clasificador, obtenido por aprendizaje supervisado. Para validar los métodos se han realizado experimentos de clasificación en clases Humano y No humano. Finalmente, se ha realizado una comparación de ambos métodos en términos de porcentaje de acierto y tiempo empleado para la clasificación, en base a los resultados de los experimentos.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Methods for autonomous wristband placement with a search-and-rescue aerial manipulator

A new robotic system for Search And Rescue (SAR) operations based on the automatic wristband placement on the victims’ arm, which may provide identification, beaconing and remote sensor readings for continuous health monitoring. This paper focuses on the development of the automatic target localization and the device placement using an unmanned aerial manipulator. The automatic wrist detection and localization system uses an RGB-D camera and a convolutional neural network based on the region faster method (Faster R-CNN). A lightweight parallel delta manipulator with a large workspace has been built, and a new design of a wristband in the form of a passive detachable gripper, is presented, which under contact, automatically attaches to the human, while disengages from the manipulator. A new trajectory planning method has been used to minimize the torques caused by the external forces during contact, which cause attitude perturbations. Experiments have been done to evaluate the machine learning method for detection and location, and for the assessment of the performance of the trajectory planning method. The results show how the VGG-16 neural network provides a detection accuracy of 67.99%. Moreover, simulation experiments have been done to show that the new trajectories minimize the perturbations to the aerial platform.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Dataset with Tactile and Kinesthetic Information from a Human Forearm and Its Application to Deep Learning

There are physical Human–Robot Interaction (pHRI) applications where the robot has to grab the human body, such as rescue or assistive robotics. Being able to precisely estimate the grasping location when grabbing a human limb is crucial to perform a safe manipulation of the human. Computer vision methods provide pre-grasp information with strong constraints imposed by the field environments. Force-based compliant control, after grasping, limits the amount of applied strength. On the other hand, valuable tactile and proprioceptive information can be obtained from the pHRI gripper, which can be used to better know the features of the human and the contact state between the human and the robot. This paper presents a novel dataset of tactile and kinesthetic data obtained from a robot gripper that grabs a human forearm. The dataset is collected with a three-fingered gripper with two underactuated fingers and a fixed finger with a high-resolution tactile sensor. A palpation procedure is performed to record the shape of the forearm and to recognize the bones and muscles in different sections. Moreover, an application for the use of the database is included. In particular, a fusion approach is used to estimate the actual grasped forearm section using both kinesthetic and tactile information on a regression deep-learning neural network. First, tactile and kinesthetic data are trained separately with Long Short-Term Memory (LSTM) neural networks, considering the data are sequential. Then, the outputs are fed to a Fusion neural network to enhance the estimation. The experiments conducted show good results in training both sources separately, with superior performance when the fusion approach is considered.This research was funded by the University of Málaga, the Ministerio de Ciencia, Innovación y Universidades, Gobierno de España, grant number RTI2018-093421-B-I00 and the European Commission, grant number BES-2016-078237. Partial funding for open access charge: Universidad de Málag

Novel ion-doped mesoporous glasses for bone tissue engineering: Study of their structural characteristics influenced by the presence of phosphorous oxide

Ion-doped binary SiO2-CaO and ternary SiO2-CaO-P2O5 mesoporous bioactive glasses were synthesized and characterized to evaluate the influence of P2O5 in the glass network structure. Strontium, copper and cobalt oxides in a proportion of 0.8 mol% were selected as dopants because the osteogenic and angiogenic properties reported for these elements. Although the four glass compositions investigated presented analogous textural properties, TEM analysis revealed that the structure of those containing P2O5 exhibited an increased ordered mesoporosity. Furthermore, 29Si NMR revealed that the incorporation of P2O5 increased the network connectivity and that this compound captured the Sr2 +, Cu2 + and Co2 + ions preventing them to behave as modifiers of the silica network. In addition, 31P NMR results revealed that the nature of the cation directly influences the characteristics of the phosphate clusters. In this study, we have proven that phosphorous oxide entraps doping-metallic ions, granting these glasses with a greater mesopores order

Monitorización de víctimas con manipuladores aéreos en operaciones de búsqueda y rescate

En este trabajo se presenta el primer dispositivo de monitorización de víctimas para su colocación automática con robots manipuladores aéreos. Se trata de un sistema sensorial distribuido para la evaluación de forma continua del estado de salud de víctimas de catástrofes. Se describen el sensor diseñado y el sistema de comunicaciones, así como la aplicación mediante la colocación del sensor basado en el uso de sistemas aéreos no tripulados (UAS) o robots manipuladores aéreos. El dispositivo de monitorización continua ofrece ventajas sobre el sistema de triage actual ya que permite obtener datos de la evolución de cada víctima. Recoge medidas de las constantes vitales de las víctimas, que son publicadas mediante protocolos de Internet de las Cosas (IoT) que permiten su procesado de forma remota. Además, posee métodos basados en aprendizaje profundo para la detección automática de la posición relativa de la muñeca del brazo de una persona con respecto al manipulador aéreo. Se han realizado experimentos preliminares de obtención de medidas y de colocación de sensores mediante una versión preliminar del sensor, cuyos resultados se incluyenUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Control a Baja Velocidad de una Rueda con Motor de Accionamiento Directo mediante Ingeniería Basada en Modelos

Los motores de corriente continua sin escobillas (BLDC) con accionamiento directo suponen una solución compacta para la tracción en vehículos eléctricos, si bien requieren detectar la posición del rotor, habitualmente mediante un codificador angular de efecto Hall dentro del mismo motor. No obstante, la ausencia de reductora y a la dificultad de añadir un codificador angular de precisión suponen un reto para lograr un control preciso a baja velocidad, especialmente si se hace uso de controladoras industriales donde las posibilidades de programación son limitadas. Este trabajo propone aplicar una estrategia de ingeniería basada en modelos (MDE) para el control a baja velocidad de una rueda con motor BLDC de accionamiento directo. En particular, se presenta la solución para un caso de estudio basado en hardware de bajo coste que incluye una tarjeta Arduino Due, una controladora Roboteq HBL2360 y un interfaz de comunicación de bus CAN. La solución MDE basada en Simulink ofrece simplicidad conceptual, capacidad de adaptación a nuevas especificaciones de diseño usando herramientas de diseño avanzadas y generación de código automática. El artículo ofrece resultados experimentales obtenidos sobre el sistema real.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech, CICYT DPI2015-65186-R y el proyecto de Innovación educativa de la Universidad de Málaga PIE 15-18

Ensayos galénicos de formas sólidas orales de acción retardada: Revisión de técnicas y dispositivos

Se estudian los ensayos galénicos a que se someten las formas farmacéuticas de administración oral y acción retardada y, en especial, los de liberación de la sustancia activa "in vitro". Aunque la revisión de las distintas técnicas y dispositivos se realiza con cierto detalle, se presta especial atención a la descripción de un método original para el estudio de la disgregación-disolución de las formas antes aludidas, con un sistema de medida continuo y directo, ya utilizado en el ensayo de formas sólidas de dosificación convencional y aplicado posteriormente en trabajos experimentales a preparados de acción prolongada. Se mencionan asimismo, los ensayos "in vivo" y clínicos con el fin de ofrecer una visión de conjunto sobre el control de las preparaciones sólidas de acción retardada, facilitando el acceso a los trabajes experimentales que sobre el tema puedan desarrollarse