Probabilistic localization of gas emission areas with a mobile robot in indoor environments

This work deals with the problem of gas source localization by a mobile robot with gas-sensing capabilities. Particularly, we address the problem for the case of indoor environments, where the presence of obstacles and the possibly complex structure with multiple rooms, inlets and outlets provoke the chaotic dispersion of the gases. Under these challenging conditions, where traditional approaches based on tracking or mathematical modeling of the plume cannot be applied, we propose a two-stage methodology to split the search into coarse and fine localization. Focusing on the broad localization, we contribute with a novel approach to estimate, from a set of sparse observations, the likelihood of different regions in the environment to hold a gas source. Experiments demonstrate that our approach is suitable to locate gas emission sources.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Estimación probabilística de áreas de emisión de gases con un robot móvil mediante la integracion temporal de observaciones de gas y viento

En este trabajo se aborda el uso de un robot m ovil para determinar la posición de una fuente de gas. Específicamente, nos centramos en el caso de entornos complejos, donde la presencia de múltiples habitaciones y obstáculos favorecen una dispersión caótica de los gases, lo cual dificulta en gran medida un modelado matemático del problema. Bajo estas condiciones, proponemos dividir la tarea de localización en dos fases: primero, determinar la zona del entorno donde se encuentra la fuente, y luego, determinar con precisión la localización de la misma dentro de la zona seleccionada. Centrándonos en la primera fase, proponemos el uso de un novedoso enfoque basado en un marco Bayesiano-probabilístico. Nuestro planteamiento se basa en la generación previa de un conjunto de mapas de dispersión de gas (empleando herramientas de simulación), atendiendo a las diferentes zonas del entorno y condiciones de viento. Comparando estos mapas con la información sensorial adquirida por el robot en cada instante de tiempo, derivamos la probabilidad de localización de la fuente, y guiamos el movimiento del robot hacia la dirección de máxima probabilidad. Para validar nuestro enfoque presentamos un total de 36 experimentos en los que un robot móvil localiza una fuente de gas en un entorno compuesto por múltiples habitaciones conexas.Este trabajo está financiado por el proyecto Español MINECO Retos AEROMAIN (DPI2014-5983-C2-1- R) así como por el proyecto AEROARMS (AErial RObotic system integrating multiple ARMS and advanced manipulation capabilities for inspection and maintenance), número de contrato 644271. La tesis de Alejandro Suárez está financiada por el Ministerio de Educación, Cultura y Deporte a través del programa FPU.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A Configurable Smart E-Nose for Spatio-Temporal Olfactory Analysis

This paper describes a novel electronic nose (enose) aimed at applications that require knowing not only the gas composition and concentration, but also its temporal and spatial evolution. This is done by capturing additional information related to the chemical substance such as the timestamp and geo-location of the measurements, as well as other physical magnitudes of the environment like temperature and humidity for correcting and interpreting the data. The device has been conceived following a modular architecture as a set of independent smart modules, which are interconnected and controlled through an I2C interface by a central processing unit. Each smart module can identify itself, store settings for autoconfiguration and perform signal pre-processing of the measured variables. Smart module types include: chemical sensors, communication interfaces, batteries, data storage, GPS, temperature and humidity.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Creating maps of VOC odors in urban areas by cycling with a portable e-nose

This work describes an application for monitoring volatile organic compounds (VOCs) in urban areas, likely coming from residential waste or the public sewage system. The objective is to obtain a spatial and temporal representation of such odors by means of a gas distribution map, from which valuable information such as the location, or the time-intervals of maximum strength of the nuisance odors can be inferred. The necessary data: chemical, temporal and spatial; is provided by a GPS and a specific e-nose accommodating eight metal oxide (MOX) gas sensors, both mounted on a bicycle. The results of a monitoring campaign carried out in a town in southern Spain are presented. The campaign comprises nine measurement runs distributed along three consecutive days, with a total path of more than 90Km. Fig.1 shows an illustrative example of the data collected during this process, and the generated geo-referenced gas distribution maps. As can be appreciated, the chemical, temporal and spatial data are successfully merged to obtain representative information about the presence of VOCs in the urban area. A deeper analysis comprising the study of the areas showing the higher VOCs concentration, as well as the temporal variability among the different days and hours within the day are also provided.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.Proyectos de Excelencia de la Junta de Andalucía: TEP08-4016 y TEP2012-53

Quantum algorithms for approximate function loading

Loading classical data into quantum computers represents an essential stage in many relevant quantum algorithms, especially in the field of quantum machine learning. Therefore, the inefficiency of this loading process means a major bottleneck for the application of these algorithms. Here, we introduce two approximate quantum-state preparation methods inspired by the Grover-Rudolph algorithm, which partially solve the problem of loading real functions. Indeed, by allowing for an infidelity $\epsilon$ and under certain smoothness conditions, we prove that the complexity of Grover-Rudolph algorithm can be reduced from $\mathcal{O}(2^{n})$ to $\mathcal{O}(2^{k_0(\epsilon)})$, with $n$ the number of qubits and $k_0(\epsilon)$ asymptotically independent of $n$. This leads to a dramatic reduction in the number of required two-qubit gates. Aroused by this result, we also propose a variational algorithm capable of loading functions beyond the aforementioned smoothness conditions. Our variational ansatz is explicitly tailored to the landscape of the function, leading to a quasi-optimized number of hyperparameters. This allows us to achieve high fidelity in the loaded state with high speed convergence for the studied examples

Exploring Cognition and Affect during Human-Cobot Interaction

Collaborative robots (Cobots) have recently gained popularity due to their capability to work collaboratively with human operators. This collaborative relationship has been named under the robotics discipline of Human-Robot Collaboration (HRC), in which humans and robots work together to accomplish a common task while also being in the same physical space. An important part of collaboration is the human\u27s decision-making, which is largely affected by their affective and cognitive state. A cobot lacks this fundamental understanding of the human operator. In this research, we utilize a server-client program to communicate the affective states of a human user to a Raspberry Pi installed within the cobot. Furthermore, this research centers on the stress and focus levels of a user to further enhance Human-Robot collaboration within a manufacturing context

Twisted Nano-optics: Manipulating Light at the Nanoscale with Twisted Phonon Polaritonic Slabs

Recent discoveries have shown that when two layers of van der Waals (vdW) materials are superimposed with a relative twist angle between their respective in-plane principal axes, the electronic properties of the coupled system can be dramatically altered. Here, we demonstrate that a similar concept can be extended to the optics realm, particularly to propagating polaritons, hybrid light-matter interactions. To do this, we fabricate stacks composed of two twisted slabs of a polar vdW crystal (MoO3) supporting low-loss anisotropic phonon polaritons (PhPs), and image the propagation of the latter when launched by localized sources (metal antennas). Our images reveal that under a critical angle the PhPs isofrequency curve (determining the PhPs momentum at a fixed frequency) undergoes a topological transition. Remarkably, at this angle, the propagation of PhPs is strongly guided along predetermined directions (canalization regime) with no geometrical spreading (diffraction-less). These results demonstrate a new degree of freedom (twist angle) for controlling the propagation of polaritons at the nanoscale with potential for nano-imaging, (bio)-sensing, quantum applications and heat management

Effect of surface modifiers on the nanoparticles electro-driven assembly

Understanding the colloidal behavior of particles is mandatory to prepare stable and disperse suspensions suitable for EPD. Up today, most of the proposed models for the EPD kinetics have been formulated considering the electrophoresis process, where depositing features are quantified by the sticking factor, a probabilistic and empiric parameter. Proposed models have demonstrated that interparticles forces are also the clue to understand the way in which particles compact on the electrode under the influence of an electric field in an electrostatically stabilized suspension. Please click on the link below for the full content