MACHINE VISION FOR AUTOMATICVISUAL INSPECTION OF WOODENRAILWAY SLEEPERS USING UNSUPERVISED NEURAL NETWORKS

The motivation for this thesis work is the need for improving reliability of equipment and quality of service to railway passengers as well as a requirement for cost-effective and efficient condition maintenance management for rail transportation. This thesis work develops a fusion of various machine vision analysis methods to achieve high performance in automation of wooden rail track inspection.The condition monitoring in rail transport is done manually by a human operator where people rely on inference systems and assumptions to develop conclusions. The use of conditional monitoring allows maintenance to be scheduled, or other actions to be taken to avoid the consequences of failure, before the failure occurs. Manual or automated condition monitoring of materials in fields of public transportation like railway, aerial navigation, traffic safety, etc, where safety is of prior importance needs non-destructive testing (NDT).In general, wooden railway sleeper inspection is done manually by a human operator, by moving along the rail sleeper and gathering information by visual and sound analysis for examining the presence of cracks. Human inspectors working on lines visually inspect wooden rails to judge the quality of rail sleeper. In this project work the machine vision system is developed based on the manual visual analysis system, which uses digital cameras and image processing software to perform similar manual inspections. As the manual inspection requires much effort and is expected to be error prone sometimes and also appears difficult to discriminate even for a human operator by the frequent changes in inspected material. The machine vision system developed classifies the condition of material by examining individual pixels of images, processing them and attempting to develop conclusions with the assistance of knowledge bases and features.A pattern recognition approach is developed based on the methodological knowledge from manual procedure. The pattern recognition approach for this thesis work was developed and achieved by a non destructive testing method to identify the flaws in manually done condition monitoring of sleepers.In this method, a test vehicle is designed to capture sleeper images similar to visual inspection by human operator and the raw data for pattern recognition approach is provided from the captured images of the wooden sleepers. The data from the NDT method were further processed and appropriate features were extracted.The collection of data by the NDT method is to achieve high accuracy in reliable classification results. A key idea is to use the non supervised classifier based on the features extracted from the method to discriminate the condition of wooden sleepers in to either good or bad. Self organising map is used as classifier for the wooden sleeper classification.In order to achieve greater integration, the data collected by the machine vision system was made to interface with one another by a strategy called fusion. Data fusion was looked in at two different levels namely sensor-level fusion, feature- level fusion. As the goal was to reduce the accuracy of the human error on the rail sleeper classification as good or bad the results obtained by the feature-level fusion compared to that of the results of actual classification were satisfactory.

A multimedia environment for supporting the teaching of robotics systems

This paper aims at describing an educational system for teaching and learning robotic systems. Multimedia resources were used to construct a virtual laboratory where users are able to use functionalities of a virtual robotic arm, by moving and clicking the mouse without caring about the detailed internal robot operation. Moreover through the multimedia system the user can interact with a real robot arm. The engineering students are the target public of the developed system. With its contents and interactive capabilities, it has been used as a support to the traditional face-to-face classes on the subject of robotics.. In the paper it is first introduced the metaphor of Virtual Laboratory used in the system. Next, it is described the Graphical and Multimedia Environment approach: an interactive graphic user interface with a 3D environment for simulation. Design and implementation issues of the real-time interactive multimedia learning system, which supports the W3C SMIL standard for presenting the real-time multimedia teaching material, are described. Finally, some preliminary conclusions and possible future works from this research are presented.

Teaching robotics systems in a multimedia environment

This paper describes the development of a multimedia educational system to teach and learn robotic systems. Multimedia resources have been used to build a virtual laboratory where users are able to utilize functions of a robotic arm, by moving and clicking the mouse without worrying about the detailed robot internal operation. The multimedia system is integrated with a real robotic arm, which was also developed at the university. Through robotic topic presentations and interactive capabilities provided by this system and its tools, students can devote themselves on the learning process just as they do in the traditional face-to-face classes. and the target public of this system are the engineering students themselves.

Use of FIA systems for on-line dilution in multielement determination by ICP-MS

A flow-injection (FI) system to match concentrations was used as an auto-diluter in multielement determination by inductively coupled plasma-mass spectrometry (ICP-MS). The flow system comprised loop-based injection or a timed valve that introduced a variable sample volume info a spray chamber through a standard Meinhard nebulizer of an ICP-MS. Routinely analyzed samples such as water, plant, and steel were selected. The accuracy of multielement determination was checked against water standard reference material from the National Institute of Standards and Technology (1643d), plant standard reference material from the National Bureau of Standards (1572 citrus leaves), and steel standard reference material from the National Bureau of Standards (AISI 4340). The measuring system was calibrated with a multielement solution, yielding a linear plot with good precision [relative standard deviation (RSD) < 3%, n = 12]. The results were in agreement at a 95% confidence level with the certified values for the reference materials and also with those obtained by continuous aspiration and by (FI) with a discrete volume. (C) 1999 John Wiley & Sons, Inc.

Industrial Robotics Applied to Education

This work describes a ludic proposal for programming learning of industrial robots to be developed by groups of engineering students. Two projects are presented: Tic-tac-toe Opponent Robot and Environmentalist Robot. The first project use competitive search techniques of the Artificial Intelligence, computational vision, electronic and pneumatic concepts for ability decision making for a robotic agent on the tic-tae-toe game. The second project consists of a game that contains a questions and answers database about environmental themes. An algorithm selects the group of questions to be answered by the player, analyses the answers and sends the result to a industrial robot through serial port. According with the player performance, the robot makes congratulation movements and giving a gift to the winner player. Otherwise, the robot makes movements, disapproving the player performance.

Environment mapping for mobile robots navigation using hierarchical neural network and omnivision

Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.

Robotics learning based on collaborative projects

[EN]Nowadays companies demand graduates able to work in multidisciplinary and collaborative projects. Hence, new educational methods are needed in order to support a more advanced society, and progress towards a higher quality of life and sustainability. The University of the Basque Country belongs to the European Higher Education Area, which was created as a result of the Bologna process to ensure the connection and quality of European national educational systems. In this framework, this paper proposes an innovative teaching methodology developed for the "Robotics" subject course that belongs to the syllabus of the B.Sc. degree in Industrial Electronics and Automation Engineering. We present an innovative methodology for Robotics learning based on collaborative projects, aimed at responding to the demands of a multidisciplinary and multilingual society.

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.

Caracterización de Sistemas intensivos en Software desde un punto de vista de innovación=Characterizing Software-intensive Systems from the innovation point of view

La innovación en Sistemas Intesivos en Software está alcanzando relevancia por múltiples razones: el software está presente en sectores como automóvil, teléfonos móviles o salud. Las empresas necesitan conocer aquellos factores que afectan a la innovación para incrementar las probabilidades de éxito en el desarrollo de sus productos y, la evaluación de productos sofware es un mecanismo potente para capturar este conocimiento. En consecuencia, las empresas necesitan evaluar sus productos desde la perpectiva de innovación para reducir la distancia entre los productos desarrollados y el mercado. Esto es incluso más relevante en el caso de los productos intensivos en software, donde el tiempo real, la oportunidad, complejidad, interoperabilidad, capacidad de respuesta y compartción de recursos son características críticas de los nuevos sistemas. La evaluación de la innovación de productos ya ha sido estudiada y se han definido algunos esquemas de evaluación pero no son específicos para Sistemas intensivos en Sofwtare; además, no se ha alcanzado consenso en los factores ni el procedimiento de evaluación. Por lo tanto, tiene sentido trabajar en la definición de un marco de evaluación de innovación enfocado a Sistemas intesivos en Software. Esta tesis identifica los elementos necesarios para construir in marco para la evaluación de de Sistemas intensivos en Software desde el punto de vista de la innovación. Se han identificado dos componentes como partes del marco de evaluación: un modelo de referencia y una herramienta adaptativa y personalizable para la realización de la evaluación y posicionamiento de la innovación. El modelo de referencia está compuesto por cuatro elementos principales que caracterizan la evaluación de innovación de productos: los conceptos, modelos de innovación, cuestionarios de evaluación y la evaluación de productos. El modelo de referencia aporta las bases para definir instancias de los modelos de evaluación de innovación de productos que pueden se evaluados y posicionados en la herramienta a través de cuestionarios y que de forma automatizada aporta los resultados de la evaluación y el posicionamiento respecto a la innovación de producto. El modelo de referencia ha sido rigurosamente construido aplicando modelado conceptual e integración de vistas junto con la aplicación de métodos cualitativos de investigación. La herramienta ha sido utilizada para evaluar productos como Skype a través de la instanciación del modelo de referencia. ABSTRACT Innovation in Software intensive Systems is becoming relevant for several reasons: software is present embedded in many sectors like automotive, robotics, mobile phones or heath care. Firms need to have knowledge about factors affecting the innovation to increase the probability of success in their product development and the assessment of innovation in software products is a powerful mechanism to capture this knowledge. Therefore, companies need to assess products from an innovation perspective to reduce the gap between their developed products and the market. This is even more relevant in the case of SiSs, where real time, timeliness, complexity, interoperability, reactivity, and resource sharing are critical features of a new system. Many authors have analysed product innovation assessment and some schemas have been developed but they are not specific to SiSs; in addition, there is no consensus about the factors or the procedures for performing an assessment. Therefore, it has sense to work in the definition of a customized software product innovation evaluation framework. This thesis identifies the elements needed to build a framework to assess software products from the innovation perspective. Two components have been identified as part of the framework to assess Software intensive Systems from the innovation perspective: a reference-model and an adaptive and customizable tool to perform the assessment and to position product innovation. The reference-model is composed by four main elements characterizing product innovation assessment: concepts, innovation models, assessment questionnaires and product assessment. The reference model provides the umbrella to define instances of product innovation assessment models that can be assessed and positioned through questionnaires in the proposed tool that also provides automation in the assessment and positioning of innovation. The reference-model has been rigorously built by applying conceptual modelling and view integration integrated with qualitative research methods. The tool has been used to assess products like Skype through models instantiated from the reference-model.

An ontology-driven communication architecture for spontaneous interoperability in Home Automation systems

Current solutions to the interoperability problem in Home Automation systems are based on a priori agreements where protocols are standardized and later integrated through specific gateways. In this regards, spontaneous interoperability, or the ability to integrate new devices into the system with minimum planning in advance, is still considered a major challenge that requires new models of connectivity. In this paper we present an ontology-driven communication architecture whose main contribution is that it facilitates spontaneous interoperability at system model level by means of semantic integration. The architecture has been validated through a prototype and the main challenges for achieving complete spontaneous interoperability are also evaluated.

A Ground-Truth Video Dataset for the Development and Evaluation of Vision-based Sense-and-Avoid systems

The importance of vision-based systems for Sense-and-Avoid is increasing nowadays as remotely piloted and autonomous UAVs become part of the non-segregated airspace. The development and evaluation of these systems demand flight scenario images which are expensive and risky to obtain. Currently Augmented Reality techniques allow the compositing of real flight scenario images with 3D aircraft models to produce useful realistic images for system development and benchmarking purposes at a much lower cost and risk. With the techniques presented in this paper, 3D aircraft models are positioned firstly in a simulated 3D scene with controlled illumination and rendering parameters. Realistic simulated images are then obtained using an image processing algorithm which fuses the images obtained from the 3D scene with images from real UAV flights taking into account on board camera vibrations. Since the intruder and camera poses are user-defined, ground truth data is available. These ground truth annotations allow to develop and quantitatively evaluate aircraft detection and tracking algorithms. This paper presents the software developed to create a public dataset of 24 videos together with their annotations and some tracking application results.

Robotic control systems based on bioinspired multi-agent systems: application of the principles of neuroscience to robotics

Robotics is a field that presents a large number of problems because it depends on a large number of disciplines, devices, technologies and tasks. Its expansion from perfectly controlled industrial environments toward open and dynamic environment presents a many new challenges, such as robots household robots or professional robots. To facilitate the rapid development of robotic systems, low cost, reusability of code, its medium and long term maintainability and robustness are required novel approaches to provide generic models and software systems who develop paradigms capable of solving these problems. For this purpose, in this paper we propose a model based on multi-agent systems inspired by the human nervous system able to transfer the control characteristics of the biological system and able to take advantage of the best properties of distributed software systems.