OLT: A Toolkit for Object Labeling Applied to Robotic RGB-D Datasets

In this work we present the Object Labeling Toolkit (OLT), a set of software components publicly available for helping in the management and labeling of sequential RGB-D observations collected by a mobile robot. Such a robot can be equipped with an arbitrary number of RGB-D devices, possibly integrating other sensors (e.g. odometry, 2D laser scanners, etc.). OLT first merges the robot observations to generate a 3D reconstruction of the scene from which object segmentation and labeling is conveniently accomplished. The annotated labels are automatically propagated by the toolkit to each RGB-D observation in the collected sequence, providing a dense labeling of both intensity and depth images. The resulting objects’ labels can be exploited for many robotic oriented applications, including high-level decision making, semantic mapping, or contextual object recognition. Software components within OLT are highly customizable and expandable, facilitating the integration of already-developed algorithms. To illustrate the toolkit suitability, we describe its application to robotic RGB-D sequences taken in a home environment.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Spanish grant pro- gram FPU-MICINN 2010 and the Spanish projects TAROTH: New developments toward a Robot at Home (DPI2011-25483) and PROMOVE: Advances in mobile robotics for promoting independent life of elders (DPI2014-55826-R

Probability and Common-Sense: Tandem Towards Robust Robotic Object Recognition in Ambient Assisted Living

The suitable operation of mobile robots when providing Ambient Assisted Living (AAL) services calls for robust object recognition capabilities. Probabilistic Graphical Models (PGMs) have become the de-facto choice in recognition systems aiming to e ciently exploit contextual relations among objects, also dealing with the uncertainty inherent to the robot workspace. However, these models can perform in an inco herent way when operating in a long-term fashion out of the laboratory, e.g. while recognizing objects in peculiar con gurations or belonging to new types. In this work we propose a recognition system that resorts to PGMs and common-sense knowledge, represented in the form of an ontology, to detect those inconsistencies and learn from them. The utilization of the ontology carries additional advantages, e.g. the possibility to verbalize the robot's knowledge. A primary demonstration of the system capabilities has been carried out with very promising results.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Experiences on a motivational learning approach for robotics in undergraduate courses

This paper presents an educational experience carried out in robotics undergraduate courses from two different degrees: Computer Science and Industrial Engineering, having students with diverse capabilities and motivations. The experience compares two learning strategies for the practical lessons of such courses: one relies on code snippets in Matlab to cope with typical robotic problems like robot motion, localization, and mapping, while the second strategy opts for using the ROS framework for the development of algorithms facing a competitive challenge, e.g. exploration algorithms. The obtained students’ opinions were instructive, reporting, for example, that although they consider harder to master ROS when compared to Matlab, it might be more useful in their (robotic related) professional careers, which enhanced their disposition to study it. They also considered that the challenge-exercises, in addition to motivate them, helped to develop their skills as engineers to a greater extent than the skeleton-code based ones. These and other conclusions will be useful in posterior courses to boost the interest and motivation of the students.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

UPGMpp: a Software Library for Contextual Object Recognition

Object recognition is a cornerstone task towards the scene understanding problem. Recent works in the field boost their perfor- mance by incorporating contextual information to the traditional use of the objects’ geometry and/or appearance. These contextual cues are usually modeled through Conditional Random Fields (CRFs), a partic- ular type of undirected Probabilistic Graphical Model (PGM), and are exploited by means of probabilistic inference methods. In this work we present the Undirected Probabilistic Graphical Models in C++ library (UPGMpp), an open source solution for representing, training, and per- forming inference over undirected PGMs in general, and CRFs in par- ticular. The UPGMpp library supposes a reliable and comprehensive workbench for recognition systems exploiting contextual information, in- cluding a variety of inference methods based on local search, graph cuts, and message passing approaches. This paper illustrates the virtues of the library, i.e. it is efficient, comprehensive, versatile, and easy to use, by presenting a use-case applied to the object recognition problem in home scenes from the challenging NYU2 dataset.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Spanish grant program FPU-MICINN 2010 and the Spanish projects “TAROTH: New developments toward a robot at home” (Ref. DPI2011-25483) and “PROMOVE: Advances in mobile robotics for promoting independent life of elders” (Ref. DPI2014-55826-R

Online Context-based Object Recognition for Mobile Robots

This work proposes a robotic object recognition system that takes advantage of the contextual information latent in human-like environments in an online fashion. To fully leverage context, it is needed perceptual information from (at least) a portion of the scene containing the objects of interest, which could not be entirely covered by just an one-shot sensor observation. Information from a larger portion of the scenario could still be considered by progressively registering observations, but this approach experiences difficulties under some circumstances, e.g. limited and heavily demanded computational resources, dynamic environments, etc. Instead of this, the proposed recognition system relies on an anchoring process for the fast registration and propagation of objects’ features and locations beyond the current sensor frustum. In this way, the system builds a graphbased world model containing the objects in the scenario (both in the current and previously perceived shots), which is exploited by a Probabilistic Graphical Model (PGM) in order to leverage contextual information during recognition. We also propose a novel way to include the outcome of local object recognition methods in the PGM, which results in a decrease in the usually high CRF learning complexity. A demonstration of our proposal has been conducted employing a dataset captured by a mobile robot from restaurant-like settings, showing promising results.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Improvement of the sensory and autonomous capability of robots through olfaction: the IRO Project

Proyecto de Excelencia Junta de Andalucía TEP2012-530Olfaction is a valuable source of information about the environment that has not been su ciently exploited in mobile robotics yet. Certainly, odor information can contribute to other sensing modalities, e.g. vision, to successfully accomplish high-level robot activities, such as task planning or execution in human environments. This paper describes the developments carried out in the scope of the IRO project, which aims at making progress in this direction by investigating mechanisms that exploit odor information (usually coming in the form of the type of volatile and its concentration) in problems like object recognition and scene-activity understanding. A distinctive aspect of this research is the special attention paid to the role of semantics within the robot perception and decisionmaking processes. The results of the IRO project have improved the robot capabilities in terms of efciency, autonomy and usefulness.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Automated analysis of feature models: Quo vadis?

Feature models have been used since the 90's to describe software product lines as a way of reusing common parts in a family of software systems. In 2010, a systematic literature review was published summarizing the advances and settling the basis of the area of Automated Analysis of Feature Models (AAFM). From then on, different studies have applied the AAFM in different domains. In this paper, we provide an overview of the evolution of this field since 2010 by performing a systematic mapping study considering 423 primary sources. We found six different variability facets where the AAFM is being applied that define the tendencies: product configuration and derivation; testing and evolution; reverse engineering; multi-model variability-analysis; variability modelling and variability-intensive systems. We also confirmed that there is a lack of industrial evidence in most of the cases. Finally, we present where and when the papers have been published and who are the authors and institutions that are contributing to the field. We observed that the maturity is proven by the increment in the number of journals published along the years as well as the diversity of conferences and workshops where papers are published. We also suggest some synergies with other areas such as cloud or mobile computing among others that can motivate further research in the future.Ministerio de Economía y Competitividad TIN2015-70560-RJunta de Andalucía TIC-186

Advanced exergy analysis for a bottoming organic rankine cycle coupled to an internal combustion engine

This paper deals with the evaluation and analysis of a bottoming ORC cycle coupled to an IC engine by means of conventional and advanced exergy analysis. Using experimental data of an ORC coupled to a 2 l turbocharged engine, both conventional and advanced exergy analysis are carried out. Splitting the exergy in the advanced exergy analysis into unavoidable and avoidable provides a measure of the potential of improving the efficiency of this component. On the other hand, splitting the exergy into endogenous and exogenous provides information between interactions among system components. The result of this study shows that there is a high potential of improvement in this type of cycles. Although, from the conventional analysis, the exergy destruction rate of boiler is greater than the one of the expander, condenser and pump, the advanced exergy analysis suggests that the first priority of improvement should be given to the expander, followed by the pump, the condenser and the boiler. A total amount of 3.75 kW (36.5%) of exergy destruction rate could be lowered, taking account that only the avoidable part of the exergy destruction rate can be reduced.This work is part of a research project called "Evaluation of bottoming cycles in IC engines to recover waste heat energies" funded by a National Project of the Spanish Government with reference TRA2013-46408-R. Authors want to acknowledge the "Apoyo para la investigacion y Desarrollo (PAID)" grant for doctoral studies (FPI S2 2015 1067).Galindo, J.; Ruiz Rosales, S.; Dolz Ruiz, V.; Royo-Pascual, L. (2016). Advanced exergy analysis for a bottoming organic rankine cycle coupled to an internal combustion engine. Energy Conversion and Management. 126:217-227. https://doi.org/10.1016/j.enconman.2016.07.080S21722712

Impactos ambientales producidos por el uso de maquinaria en el sector de la construcción

Trabajo de InvestigaciónEl trabajo tuvo como propósito investigar y analizar todo lo relacionado con los impactos ambientales que se producen por el uso de maquinaría en proyectos de construcción en Ingeniería Civil, teniendo en cuenta que esta actividad genera una alteración en el medio ambiente considerable, pero que es necesaria, por cuanto se deben desarrollar actividades de prevención, control y mitigación, es por esto que se hace investigó sobre los tipos de impactos ambientales que provoca el sector y específicamente el uso de maquinarías, así mismo se hace una recopilación de las medidas de control y prevención para cada tipo de impacto y finalmente un estudio de caso para verificar su cumplimiento.INTRODUCCIÓN 1. GENERALIDADES 2. CARACTERIZACIÓN DE IMPACTOS AMBIENTALES EN EL SECTOR DE LA CONSTRUCCIÓN 3. CARACTERIZACIÓN DE MAQUINARIAS DE CONSTRUCCIÓN Y SU IMPACTO AMBIENTAL 4. MANEJO AMBIENTAL DE MAQUINARÍAS DE CONSTRUCCIÓN 5. ANÁLISIS DEL MANEJO DE IMPACTOS AMBIENTALES GENERADOS POR EL USO DE MAQUINARÍAS EN OBRAS DE CONSTRUCCIÓN A PARTIR DE UN ESTUDIO DE CASO 6. CONCLUSIONES 7. RECOMENDACIONES BIBLIOGRAFÍA ANEXOSPregradoIngeniero Civi

Statistical complexity, Fisher-Shannon information, and Bohr orbits in the H-atom

The Fisher-Shannon information and a statistical measure of complexity are calculated in the position and momentum spaces for the wave functions of the H-atom. For each level of energy, it is found that these two indicators take their minimum values on the orbitals that correspond to the classical (circular) orbits in the Bohr atomic model, just those with the highest orbital angular momentum.Comment: 7 pages, 2 figure