Simultaneous 3D object tracking and camera parameter estimation by Bayesian methods and transdimensional MCMC sampling

Multi-camera 3D tracking systems with overlapping cameras represent a powerful mean for scene analysis, as they potentially allow greater robustness than monocular systems and provide useful 3D information about object location and movement. However, their performance relies on accurately calibrated camera networks, which is not a realistic assumption in real surveillance environments. Here, we introduce a multi-camera system for tracking the 3D position of a varying number of objects and simultaneously refin-ing the calibration of the network of overlapping cameras. Therefore, we introduce a Bayesian framework that combines Particle Filtering for tracking with recursive Bayesian estimation methods by means of adapted transdimensional MCMC sampling. Addi-tionally, the system has been designed to work on simple motion detection masks, making it suitable for camera networks with low transmission capabilities. Tests show that our approach allows a successful performance even when starting from clearly inaccurate camera calibrations, which would ruin conventional approaches.

ITER fast plant system controller prototype based on PXIe platform

The ITER CODAC design identifies slow and fast plant system controllers (PSC). The gast OSCs are based on embedded technologies, permit sampling rates greater than 1 KHz, meet stringent real-time requirements, and will be devoted to data acquisition tasks and control purposes. CIEMAT and UPM have implemented a prototype of a fast PSC based on commercial off-the-shelf (COTS) technologies with PXI hardware and software based on EPICS

ITER Fast Plant System Controller Prototype Based on Commercial PXI Platform

The ITER CODAC design identifies slow and fast plant system controllers (PSC). The gast OSCs are based on embedded technologies, permit sampling rates greater than 1 KHz, meet stringent real-time requirements, and will be devoted to data acquisition tasks and control purposes. CIEMAT and UPM have implemented a prototype of a fast PSC based on commercial off-the-shelf (COTS) technologies with PXI hardware and software based on EPICS

Unsupervised system to classify SO2 pollutant concentrations in Salamanca, Mexico

Salamanca is cataloged as one of the most polluted cities in Mexico. In order to observe the behavior and clarify the influence of wind parameters on the Sulphur Dioxide (SO2) concentrations a Self-Organizing Maps (SOM) Neural Network have been implemented at three monitoring locations for the period from January 1 to December 31, 2006. The maximum and minimum daily values of SO2 concentrations measured during the year of 2006 were correlated with the wind parameters of the same period. The main advantages of the SOM Neural Network is that it allows to integrate data from different sensors and provide readily interpretation results. Especially, it is powerful mapping and classification tool, which others information in an easier way and facilitates the task of establishing an order of priority between the distinguished groups of concentrations depending on their need for further research or remediation actions in subsequent management steps. For each monitoring location, SOM classifications were evaluated with respect to pollution levels established by Health Authorities. The classification system can help to establish a better air quality monitoring methodology that is essential for assessing the effectiveness of imposed pollution controls, strategies, and facilitate the pollutants reduction.

Intelligent automatic overtaking system using vision for vehicle detection

There is clear evidence that investment in intelligent transportation system technologies brings major social and economic benefits. Technological advances in the area of automatic systems in particular are becoming vital for the reduction of road deaths. We here describe our approach to automation of one the riskiest autonomous manœuvres involving vehicles – overtaking. The approach is based on a stereo vision system responsible for detecting any preceding vehicle and triggering the autonomous overtaking manœuvre. To this end, a fuzzy-logic based controller was developed to emulate how humans overtake. Its input is information from the vision system and from a positioning-based system consisting of a differential global positioning system (DGPS) and an inertial measurement unit (IMU). Its output is the generation of action on the vehicle’s actuators, i.e., the steering wheel and throttle and brake pedals. The system has been incorporated into a commercial Citroën car and tested on the private driving circuit at the facilities of our research center, CAR, with different preceding vehicles – a motorbike, car, and truck – with encouraging results.

Vision-based active safety system for automatic stopping

ntelligent systems designed to reduce highway fatalities have been widely applied in the automotive sector in the last decade. Of all users of transport systems, pedestrians are the most vulnerable in crashes as they are unprotected. This paper deals with an autonomous intelligent emergency system designed to avoid collisions with pedestrians. The system consists of a fuzzy controller based on the time-to-collision estimate – obtained via a vision-based system – and the wheel-locking probability – obtained via the vehicle’s CAN bus – that generates a safe braking action. The system has been tested in a real car – a convertible Citroën C3 Pluriel – equipped with an automated electro-hydraulic braking system capable of working in parallel with the vehicle’s original braking circuit. The system is used as a last resort in the case that an unexpected pedestrian is in the lane and all the warnings have failed to produce a response from the driver.

A quality assessment system for fresh fruits in hypermarkets and fruit trading centres.

When the fresh fruit reaches the final markets from the suppliers, its quality is not always as good as it should, either because it has been mishandled during transportation or because it lacks an adequate quality control at the producer level, before being shipped. This is why it is necessary for the final markets to establish their own quality assessment system if they want to ensure to their customers the quality they want to sell. In this work, a system to control fruit quality at the last level of the distribution channel has been designed. The system combines rapid control techniques with laboratory equipment and statistical sampling protocols, to obtain a dynamic, objective process, which can substitute advantageously the quality control inspections carried out visually by human experts at the reception platform of most hypermarkets. Portable measuring equipment have been chosen (firmness tester, temperature and humidity sensors...) as well as easy-to-use laboratory equipment (texturometer, colorimeter, refractometer..,) combining them to control the most important fruit quality parameters (firmness, colour, sugars, acids). A complete computer network has been designed to control all the processes and store the collected data in real time, and to perform the computations. The sampling methods have been also defined to guarantee the confidence of the results. Some of the advantages of a quality assessment system as the proposed one are: the minimisation of human subjectivity, the ability to use modern measuring techniques, and the possibility of using it also as a supplier's quality control system. It can be also a way to clarify the quality limits of fruits among members of the commercial channel, as well as the first step in the standardisation of quality control procedures.

Multi-agent location system in wireless networks

In this paper we propose a flexible Multi-Agent Architecture together with a methodology for indoor location which allows us to locate any mobile station (MS) such as a Laptop, Smartphone, Tablet or a robotic system in an indoor environment using wireless technology. Our technology is complementary to the GPS location finder as it allows us to locate a mobile system in a specific room on a specific floor using the Wi-Fi networks. The idea is that any MS will have an agent known at a Fuzzy Location Software Agent (FLSA) with a minimum capacity processing at its disposal which collects the power received at different Access Points distributed around the floor and establish its location on a plan of the floor of the building. In order to do so it will have to communicate with the Fuzzy Location Manager Software Agent (FLMSA). The FLMSAs are local agents that form part of the management infrastructure of the Wi-Fi network of the Organization. The FLMSA implements a location estimation methodology divided into three phases (measurement, calibration and estimation) for locating mobile stations (MS). Our solution is a fingerprint-based positioning system that overcomes the problem of the relative effect of doors and walls on signal strength and is independent of the network device manufacturer. In the measurement phase, our system collects received signal strength indicator (RSSI) measurements from multiple access points. In the calibration phase, our system uses these measurements in a normalization process to create a radio map, a database of RSS patterns. Unlike traditional radio map-based methods, our methodology normalizes RSS measurements collected at different locations on a floor. In the third phase, we use Fuzzy Controllers to locate an MS on the plan of the floor of a building. Experimental results demonstrate the accuracy of the proposed method. From these results it is clear that the system is highly likely to be able to locate an MS in a room or adjacent room.

Reducing the dimensionality effect in importance sampling simulations

The dimensionality effect is avoided by the use of sufficient statistics in event probability estimators realised by importance sampling. If the system function is not a sufficient statistic, an approach is proposed to reduce the dimensionality effect in the estimators. Simulation results of false-alarm probability estimations, applied to radar detection, confirm a clear concordance with the theoretical results

A cooperative multi-agent robotics system: design and modelling

This paper presents the development of the robotic multi-agent system SMART. In this system, the agent concept is applied to both hardware and software entities. Hardware agents are robots, with three and four legs, and an IP-camera that takes images of the scene where the cooperative task is carried out. Hardware agents strongly cooperate with software agents. These latter agents can be classified into image processing, communications, task management and decision making, planning and trajectory generation agents. To model, control and evaluate the performance of cooperative tasks among agents, a kind of PetriNet, called Work-Flow Petri Net, is used. Experimental results shows the good performance of the system.

Tree and grazing influence on herbaceous pasture diversity in the Dehesa agroforestry system

Mediterranean Dehesas are one of the European natural habitat types of Community interest (43/92/EEC Directive), associated to high diversity levels and producer of important goods and services. In this work, tree contribution and grazing influence over pasture alpha diversity in a Dehesa in Central Spain was studied. We analyzed Richness and Shannon-Wiener (SW) indexes on herbaceous layer under 16 holms oak trees (64 sampling units distributed in two directions and in two distances to the trunk) distributed in four different grazing management zones (depending on species and stocking rate). Floristic composition by species or morphospecies and species abundance were analyzed for each sample unit. Linear mixed models (LMM) and generalized linear mixed models (GLMMs) were used to study relationships between alpha diversity measures and independent factors. Edge crown influence showed the highest values of Richness and SW index. No significant differences were found between orientations under tree crown influence. Grazing management had a significant effect over Richness and SW measures, specially the grazing species (cattle or sheep). We preliminary quantify and analyze the interaction of tree stratum and grazing management over herbaceous diversity in a year of extreme climatic conditions.

On-line learning of a fuzzy controller for a precise vehicle cruise control system

Usually, vehicle applications require the use of artificial intelligent techniques to implement control methods, due to noise provided by sensors or the impossibility of full knowledge about dynamics of the vehicle (engine state, wheel pressure or occupiers weight). This work presents a method to on-line evolve a fuzzy controller for commanding vehicles? pedals at low speeds; in this scenario, the slightest alteration in the vehicle or road conditions can vary controller?s behavior in a non predictable way. The proposal adapts singletons positions in real time, and trapezoids used to codify the input variables are modified according with historical data. Experimentation in both simulated and real vehicles are provided to show how fast and precise the method is, even compared with a human driver or using different vehicles.

TITIM GIS-tool: A GIS-based decision support system for measuring the territorial impact of transport infrastructures

To achieve sustainability in the area of transport we need to view the decision-making process as a whole and consider all the most important socio-economic and environmental aspects involved. Improvements in transport infrastructures have a positive impact on regional development and significant repercussions on the economy, as well as affecting a large number of ecological processes. This article presents a DSS to assess the territorial effects of new linear transport infrastructures based on the use of GIS. The TITIM ? Transport Infrastructure Territorial Impact Measurement ? GIS tool allows these effects to be calculated by evaluating the improvement in accessibility, loss of landscape connectivity, and the impact on other local territorial variables such as landscape quality, biodiversity and land-use quality. The TITIM GIS tool assesses these variables automatically, simply by entering the required inputs, and thus avoiding the manual reiteration and execution of these multiple processes. TITIM allows researchers to use their own GIS databases as inputs, in contrast with other tools that use official or predefined maps. The TITIM GIS-tool is tested by application to six HSR projects in the Spanish Strategic Transport and Infrastructure Plan 2005?2020 (PEIT). The tool creates all 65 possible combinations of these projects, which will be the real test scenarios. For each one, the tool calculates the accessibility improvement, the landscape connectivity loss, and the impact on the landscape, biodiversity and land-use quality. The results reveal which of the HSR projects causes the greatest benefit to the transport system, any potential synergies that exist, and help define a priority for implementing the infrastructures in the plan

A linearization-based system reliability method with application to geotechnical analysis

Los análisis de fiabilidad representan una herramienta adecuada para contemplar las incertidumbres inherentes que existen en los parámetros geotécnicos. En esta Tesis Doctoral se desarrolla una metodología basada en una linealización sencilla, que emplea aproximaciones de primer o segundo orden, para evaluar eficientemente la fiabilidad del sistema en los problemas geotécnicos. En primer lugar, se emplean diferentes métodos para analizar la fiabilidad de dos aspectos propios del diseño de los túneles: la estabilidad del frente y el comportamiento del sostenimiento. Se aplican varias metodologías de fiabilidad — el Método de Fiabilidad de Primer Orden (FORM), el Método de Fiabilidad de Segundo Orden (SORM) y el Muestreo por Importancia (IS). Los resultados muestran que los tipos de distribución y las estructuras de correlación consideradas para todas las variables aleatorias tienen una influencia significativa en los resultados de fiabilidad, lo cual remarca la importancia de una adecuada caracterización de las incertidumbres geotécnicas en las aplicaciones prácticas. Los resultados también muestran que tanto el FORM como el SORM pueden emplearse para estimar la fiabilidad del sostenimiento de un túnel y que el SORM puede mejorar el FORM con un esfuerzo computacional adicional aceptable. Posteriormente, se desarrolla una metodología de linealización para evaluar la fiabilidad del sistema en los problemas geotécnicos. Esta metodología solamente necesita la información proporcionada por el FORM: el vector de índices de fiabilidad de las funciones de estado límite (LSFs) que componen el sistema y su matriz de correlación. Se analizan dos problemas geotécnicos comunes —la estabilidad de un talud en un suelo estratificado y un túnel circular excavado en roca— para demostrar la sencillez, precisión y eficiencia del procedimiento propuesto. Asimismo, se reflejan las ventajas de la metodología de linealización con respecto a las herramientas computacionales alternativas. Igualmente se muestra que, en el caso de que resulte necesario, se puede emplear el SORM —que aproxima la verdadera LSF mejor que el FORM— para calcular estimaciones más precisas de la fiabilidad del sistema. Finalmente, se presenta una nueva metodología que emplea Algoritmos Genéticos para identificar, de manera precisa, las superficies de deslizamiento representativas (RSSs) de taludes en suelos estratificados, las cuales se emplean posteriormente para estimar la fiabilidad del sistema, empleando la metodología de linealización propuesta. Se adoptan tres taludes en suelos estratificados característicos para demostrar la eficiencia, precisión y robustez del procedimiento propuesto y se discuten las ventajas del mismo con respecto a otros métodos alternativos. Los resultados muestran que la metodología propuesta da estimaciones de fiabilidad que mejoran los resultados previamente publicados, enfatizando la importancia de hallar buenas RSSs —y, especialmente, adecuadas (desde un punto de vista probabilístico) superficies de deslizamiento críticas que podrían ser no-circulares— para obtener estimaciones acertadas de la fiabilidad de taludes en suelos. Reliability analyses provide an adequate tool to consider the inherent uncertainties that exist in geotechnical parameters. This dissertation develops a simple linearization-based approach, that uses first or second order approximations, to efficiently evaluate the system reliability of geotechnical problems. First, reliability methods are employed to analyze the reliability of two tunnel design aspects: face stability and performance of support systems. Several reliability approaches —the first order reliability method (FORM), the second order reliability method (SORM), the response surface method (RSM) and importance sampling (IS)— are employed, with results showing that the assumed distribution types and correlation structures for all random variables have a significant effect on the reliability results. This emphasizes the importance of an adequate characterization of geotechnical uncertainties for practical applications. Results also show that both FORM and SORM can be used to estimate the reliability of tunnel-support systems; and that SORM can outperform FORM with an acceptable additional computational effort. A linearization approach is then developed to evaluate the system reliability of series geotechnical problems. The approach only needs information provided by FORM: the vector of reliability indices of the limit state functions (LSFs) composing the system, and their correlation matrix. Two common geotechnical problems —the stability of a slope in layered soil and a circular tunnel in rock— are employed to demonstrate the simplicity, accuracy and efficiency of the suggested procedure. Advantages of the linearization approach with respect to alternative computational tools are discussed. It is also found that, if necessary, SORM —that approximates the true LSF better than FORM— can be employed to compute better estimations of the system’s reliability. Finally, a new approach using Genetic Algorithms (GAs) is presented to identify the fully specified representative slip surfaces (RSSs) of layered soil slopes, and such RSSs are then employed to estimate the system reliability of slopes, using our proposed linearization approach. Three typical benchmark-slopes with layered soils are adopted to demonstrate the efficiency, accuracy and robustness of the suggested procedure, and advantages of the proposed method with respect to alternative methods are discussed. Results show that the proposed approach provides reliability estimates that improve previously published results, emphasizing the importance of finding good RSSs —and, especially, good (probabilistic) critical slip surfaces that might be non-circular— to obtain good estimations of the reliability of soil slope systems.

Face, content, and construct validity of the EndoViS training system for objective assessment of psychomotor skills of laparoscopic surgeons

Background The aim of this study is to present face, content, and constructs validity of the endoscopic orthogonal video system (EndoViS) training system and determines its efficiency as a training and objective assessment tool of the surgeons’ psychomotor skills. Methods Thirty-five surgeons and medical students participated in this study: 11 medical students, 19 residents, and 5 experts. All participants performed four basic skill tasks using conventional laparoscopic instruments and EndoViS training system. Subsequently, participants filled out a questionnaire regarding the design, realism, overall functionality, and its capabilities to train hand–eye coordination and depth perception, rated on a 5-point Likert scale. Motion data of the instruments were obtained by means of two webcams built into a laparoscopic physical trainer. To identify the surgical instruments in the images, colored markers were placed in each instrument. Thirteen motion-related metrics were used to assess laparoscopic performance of the participants. Statistical analysis of performance was made between novice, intermediate, and expert groups. Internal consistency of all metrics was analyzed with Cronbach’s α test. Results Overall scores about features of the EndoViS system were positives. Participants agreed with the usefulness of tasks and the training capacities of EndoViS system (score >4). Results presented significant differences in the execution of three skill tasks performed by participants. Seven metrics showed construct validity for assessment of performance with high consistency levels. Conclusions EndoViS training system has been successfully validated. Results showed that EndoViS was able to differentiate between participants of varying laparoscopic experience. This simulator is a useful and effective tool to objectively assess laparoscopic psychomotor skills of the surgeons.