Standard commercial education robotic platform: intermediate solution to teaching robotics

Teaching robotics to students at the beginning of their studies has become a huge challenge. Simulation environments can be an effective solution to that challenge where students can interact with simulated robots and have the first contact with robotic constraints. From our previous experience with simulation environments it was possible to observe that students with lower background knowledge in robotics where able to deal with a limited number of constraints, implement a simulated robotic platform and study several sensors. The question is: after this first phase what should be the best approach? Should the student start developing their own hardware? Hardware development is a very important part of an engineer's education but it can also be a difficult phase that could lead to discouragement and loss of motivation in some students. Considering the previous constraints and first year engineering students’ high abandonment rate it is important to develop teaching strategies to deal with this problem in a feasible way. The solution that we propose is the integration of a low-cost standard robotic platform WowWee Rovio as an intermediate solution between the simulation phase and the stage where the students can develop their own robots. This approach will allow the students to keep working in robotic areas such as: cooperative behaviour, perception, navigation and data fusion. The propose approach proved to be a motivation step not only for the students but also for the teachers. Students and teachers were able to reach an agreement between the level of demand imposed by the teachers and satisfaction/motivation of the students.

Ethernet Telemetry for Towed Arrays

The towed array electronics is essentially a multichannel real time data acquisition system. The major challenges involved in it are the simultaneous acquisition of data from multiple channels, telemetry of the data over tow cable (several kilometres in some systems) and synchronization with the onboard receiver for accurate reconstruction. A serial protocol is best suited to transmit the data to onboard electronics since number of wires inside the tow cable is limited. The best transmission medium for data over large distances is the optical fibre. In this a two step approach towards the realization of a reliable telemetry scheme for the sensor data using standard protocols is described. The two schemes are discussed in this paper. The first scheme is for conversion of parallel, time-multiplexed multi-sensor data to Ethernet. Existing towed arrays can be upgraded to ethernet using this scheme. Here the last lap of the transmission is by Ethernet over Fibre. For the next generation of towed arrays it is required to digitize and convert the data to ethernet close to the sensor. This is the second scheme. At the heart of this design is the Analog-to-Ethernet node. In addition to a more reliable interface, this helps in easier fault detection and firmware updates in the field for the towed arrays. The design challenges and considerations for incorporating a network of embedded devices within the array are highlighted

Multisensor Modeling Underwater with Uncertain Information

This thesis develops an approach to the construction of multidimensional stochastic models for intelligent systems exploring an underwater environment. It describes methods for building models by a three- dimensional spatial decomposition of stochastic, multisensor feature vectors. New sensor information is incrementally incorporated into the model by stochastic backprojection. Error and ambiguity are explicitly accounted for by blurring a spatial projection of remote sensor data before incorporation. The stochastic models can be used to derive surface maps or other representations of the environment. The methods are demonstrated on data sets from multibeam bathymetric surveying, towed sidescan bathymetry, towed sidescan acoustic imagery, and high-resolution scanning sonar aboard a remotely operated vehicle.

Pose Determination of a Grasped Object Using Limited Sensing

This report explores methods for determining the pose of a grasped object using only limited sensor information. The problem of pose determination is to find the position of an object relative to the hand. The information is useful when grasped objects are being manipulated. The problem is hard because of the large space of grasp configurations and the large amount of uncertainty inherent in dexterous hand control. By studying limited sensing approaches, the problem's inherent constraints can be better understood. This understanding helps to show how additional sensor data can be used to make recognition methods more effective and robust.

gvSIG Sensores

El protocolo SOS (Sensor Observation Service) es una especificación OGC dentro de la iniciativa Sensor Web Enablement (SWE), que permite acceder a las observaciones y datos de sensores heterogéneos de una manera estándar. En el proyecto gvSIG se ha abierto una línea de investigación entorno a la SWE, existiendo en la actualidad dos prototipos de clientes SOS para gvSIG y gvSIG Mobile. La especificación utilizada para describir las medidas proporcionadas por sensores es Observation & Measurement (O&M) y la descripción de los metadatos de los sensores (localización. ID, fenómenos medidos, procesamiento de los datos, etc) se obtiene a partir del esquema Sensor ML. Se ha implementado el siguiente conjunto de operaciones: GetCapabilities para la descripción del servicio; DescribeSensor para acceder a los metadatos del sensor y el GetObservation para recibir las observaciones. En el caso del prototipo para gvSIG escritorio se puede acceder a los datos procedentes de los distintos grupos de sensores “offerings” añadiéndolos en el mapa como nuevas capas. Los procedimientos o sensores que están incluidos en un “offering” son presentados como elementos de la capa que se pueden cartografiar en el mapa. Se puede acceder a las observaciones (GetObservation) de estos sensores filtrando los datos por intervalo de tiempo y propiedad del fenómeno observado. La información puede ser representada sobre el mapa mediante gráficas para una mejor comprensión con la posibilidad de comparar datos de distintos sensores. En el caso del prototipo para el cliente móvil gvSIG Mobile, se ha utilizado la misma filosofía que para el cliente de escritorio, siendo cada “offering” una nueva capa. Las observaciones de los sensores pueden ser visualizadas en la pantalla del dispositivo móvil y se pueden obtener mapas temáticos,con el objetivo de facilitar la interpretación de los datos

Comparison of balloon-carried atmospheric motion sensors with Doppler lidar turbulence measurements

Magnetic sensors have been added to a standard weather balloon radiosonde package to detect motion in turbulent air. These measure the terrestrial magnetic field and return data over the standard uhf radio telemetry. Variability in the magnetic sensor data is caused by motion of the instrument package. A series of radiosonde ascents carrying these sensors has been made near a Doppler lidar measuring atmospheric properties. Lidar-retrieved quantities include vertical velocity (w) profile and its standard deviation (w). w determined over 1 h is compared with the radiosonde motion variability at the same heights. Vertical motion in the radiosonde is found to be robustly increased when w>0.75 m s−1 and is linearly proportional to w. ©2009 American Institute of Physics

Prosthesis grasp reflex via peripheral nerve control: an in vitro study

Here we present an economical and versatile platform for developing motor control and sensory feedback of a prosthetic hand via in vitro mammalian peripheral nerve activity. In this study, closed-loop control of the grasp function of the prosthetic hand was achieved by stimulation of a peripheral nerve preparation in response to slip sensor data from a robotic hand, forming a rudimentary reflex action. The single degree of freedom grasp was triggered by single unit activity from motor and sensory fibers as a result of stimulation. The work presented here provides a novel, reproducible, economic, and robust platform for experimenting with neural control of prosthetic devices before attempting in vivo implementation.

The Mathematics of Control Theory

This text contains papers presented at the Institute of Mathematics and its Applications Conference on Control Theory, held at the University of Strathclyde in Glasgow. The contributions cover a wide range of topics of current interest to theoreticians and practitioners including algebraic systems theory, nonlinear control systems, adaptive control, robustness issues, infinite dimensional systems, applications studies and connections to mathematical aspects of information theory and data-fusion.

Cloud-assisted body area networks: state-of-the-art and future challenges

Body area networks (BANs) are emerging as enabling technology for many human-centered application domains such as health-care, sport, fitness, wellness, ergonomics, emergency, safety, security, and sociality. A BAN, which basically consists of wireless wearable sensor nodes usually coordinated by a static or mobile device, is mainly exploited to monitor single assisted livings. Data generated by a BAN can be processed in real-time by the BAN coordinator and/or transmitted to a server-side for online/offline processing and long-term storing. A network of BANs worn by a community of people produces large amount of contextual data that require a scalable and efficient approach for elaboration and storage. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of body sensor data streams. In this paper, we motivate the introduction of Cloud-assisted BANs along with the main challenges that need to be addressed for their development and management. The current state-of-the-art is overviewed and framed according to the main requirements for effective Cloud-assisted BAN architectures. Finally, relevant open research issues in terms of efficiency, scalability, security, interoperability, prototyping, dynamic deployment and management, are discussed.

A novel MAP-MRF approach for multispectral image contextual classification using combination of suboptimal iterative algorithms

In this paper we present a novel approach for multispectral image contextual classification by combining iterative combinatorial optimization algorithms. The pixel-wise decision rule is defined using a Bayesian approach to combine two MRF models: a Gaussian Markov Random Field (GMRF) for the observations (likelihood) and a Potts model for the a priori knowledge, to regularize the solution in the presence of noisy data. Hence, the classification problem is stated according to a Maximum a Posteriori (MAP) framework. In order to approximate the MAP solution we apply several combinatorial optimization methods using multiple simultaneous initializations, making the solution less sensitive to the initial conditions and reducing both computational cost and time in comparison to Simulated Annealing, often unfeasible in many real image processing applications. Markov Random Field model parameters are estimated by Maximum Pseudo-Likelihood (MPL) approach, avoiding manual adjustments in the choice of the regularization parameters. Asymptotic evaluations assess the accuracy of the proposed parameter estimation procedure. To test and evaluate the proposed classification method, we adopt metrics for quantitative performance assessment (Cohen`s Kappa coefficient), allowing a robust and accurate statistical analysis. The obtained results clearly show that combining sub-optimal contextual algorithms significantly improves the classification performance, indicating the effectiveness of the proposed methodology. (C) 2010 Elsevier B.V. All rights reserved.

Nonstationary feature extraction techniques for automatic classification of impact acoustic signals

Condition monitoring of wooden railway sleepers applications are generallycarried out by visual inspection and if necessary some impact acoustic examination iscarried out intuitively by skilled personnel. In this work, a pattern recognition solutionhas been proposed to automate the process for the achievement of robust results. Thestudy presents a comparison of several pattern recognition techniques together withvarious nonstationary feature extraction techniques for classification of impactacoustic emissions. Pattern classifiers such as multilayer perceptron, learning cectorquantization and gaussian mixture models, are combined with nonstationary featureextraction techniques such as Short Time Fourier Transform, Continuous WaveletTransform, Discrete Wavelet Transform and Wigner-Ville Distribution. Due to thepresence of several different feature extraction and classification technqies, datafusion has been investigated. Data fusion in the current case has mainly beeninvestigated on two levels, feature level and classifier level respectively. Fusion at thefeature level demonstrated best results with an overall accuracy of 82% whencompared to the human operator.

Machine learning and small robot navigation

Developing successful navigation and mapping strategies is an essential part of autonomous robot research. However, hardware limitations often make for inaccurate systems. This project serves to investigate efficient alternatives to mapping an environment, by first creating a mobile robot, and then applying machine learning to the robot and controlling systems to increase the robustness of the robot system. My mapping system consists of a semi-autonomous robot drone in communication with a stationary Linux computer system. There are learning systems running on both the robot and the more powerful Linux system. The first stage of this project was devoted to designing and building an inexpensive robot. Utilizing my prior experience from independent studies in robotics, I designed a small mobile robot that was well suited for simple navigation and mapping research. When the major components of the robot base were designed, I began to implement my design. This involved physically constructing the base of the robot, as well as researching and acquiring components such as sensors. Implementing the more complex sensors became a time-consuming task, involving much research and assistance from a variety of sources. A concurrent stage of the project involved researching and experimenting with different types of machine learning systems. I finally settled on using neural networks as the machine learning system to incorporate into my project. Neural nets can be thought of as a structure of interconnected nodes, through which information filters. The type of neural net that I chose to use is a type that requires a known set of data that serves to train the net to produce the desired output. Neural nets are particularly well suited for use with robotic systems as they can handle cases that lie at the extreme edges of the training set, such as may be produced by "noisy" sensor data. Through experimenting with available neural net code, I became familiar with the code and its function, and modified it to be more generic and reusable for multiple applications of neural nets.

Evolução tectono-estrutural do Campo de Xaréu (Sub-bacia de Mundaú, Bacia do Ceará - NE do Brasil: abordagem multiescala e pluriferramental

The Xaréu Oil Field, located in the center-southern portion of the Mundaú Sub-Basin (eastern portion of the Ceará Basin), is characterized by a main Iramework of NW-trending and NE-dipping faults. The faults in the Xaréu Oil Field, among which the Xaréu Fautt stands out, are arranged according to an extensional-listriclan, rooted on a detachment surface corresponding to the Mundaú Fault, the border fautt of Mundaú Sub-Basin. During the tectonic-structural evolution of the Xaréu Oil Field and the Mundaú Sub-Basin, the Mundaú Fault played a crucial role on the control of the geometry of both compartments. The main carbonatic unit in the Xaréu Oil Field, named the Trairí Member(Paracuru Formation of Late Aptian to Early Albian age), contains the largest oil volume in the field, concentrated in structurally-controlled accumulations. The Trairí Member is composed by a variety of carbonatic rocks (massive, bedded or laminated calcilutites, ostracodites, calcarenites and carbonatic rudites, all of them presenting variable degrees of dolomitization). The carbonatic rocks are interbedded into thick packages of black shales and marls, besides local beds of siliciclastic conglomerates, sandstones, siltnes and argillites. From the spatial association and the genetic relationships between the carbonatic and siliciclastic units, it is possible to group them in three lithofacies associations (Marginal Plain, Ramp and Lacustrine Interior) that, together, were developed in a lacustrine system associated to a marginal sabkha. Structural studies based on drill coresthat sample the Trairí Member in the Xaréu Oil Field allowed to characterize two generations of meso- to microscale structures: the D1 group presents a typical hydroplastic character, being characterized by intra/interstratal to oblique-bedding shear zones. The hydroplastic character related to these structures allowed to infer their development at an early-lithilication stage of the Trairí Member, leading to infer an Early Cretaceous age to them. The second group of structures identified in the drill cores, nominated D2 and ascribed to a Neogene age, presents a strictly brttle character, being typilied by normal faults and slickenfibers of re-crystallized clayminerals, ali olthem displaying variable orientations. Although the present faults in the Xaréu Oil Field (and, consequently, in the Mundaú Sub-Basin) were classically relerred as struetures of essentially normal displacement, the kinematics analysis of the meso-to microscaie D1 struetures in the drill cores led to deline oblique displacements (normal with a clockwise strike-slip component) to these faults, indicating a main tectonic transport to ENE. These oblique movements would be responsible for the installation of a transtensive context in the Mundaú Sub-Basin, as part of the transcurrent to translormant opening of the Atlantic Equatorial Margin. The balancing of four struetural cross-sections ofthe Xaréu Oil Field indicates that the Mundaú Fault was responsible for more than 50% of the total stretching (ß factor) registered during the Early Aptian. At the initial stages of the "rifting", during Early Aptianuntil the Holocene, the Mundaú Sub-Basin (and consequently the Xaréu Oil Fleld) accumulated a total stretching between 1.21 and 1.23; in other words, the crust in this segment of the Atlantic Equatorial Margin was subjeeted to an elongation of about 20%. From estimates of oblique displacements related to the faults, it ws possible to construct diagrams that allow the determination of stretching factors related to these displacements. Using these diagrams and assuming the sense 01 dominant teetonictransport towards ENE, it was possible to calculate the real stretching lactors related to the oblique movement 0 of the faults in the Mundaú Sub-Basin. which reached actual values between 1.28 and 1.42. ln addnion to the tectonic-structural studies in the Xaréu Oil Field, the interpretation of remote sensing products, coupled wnh characterization of terrain analogues in seleeted areas along the northern Ceará State (continental margins of the Ceará and Potiguar basins), provided addnional data and constraints about the teetonic-structural evolution of the oil lield. The work at the analogue sites was particularly effective in the recognition and mapping, in semidetail scale, several generations of struetures originated under a brittle regime. Ali the obtained information (from the Xaréu Oil Field, the remote sensor data and the terrain analogues) were jointly interpreted, culminating with the proposnion of an evolutionary model lor this segment of the Atlantic Equatorial Margin; this model that can be applied to the whole Margin, as well. This segmentof the Atlantic Equatorial Margin was delormedin an early E-W (when considered lhe present-day position of the South American Plate) transcurrent to transform regime with dextral kinematics, started Irom, at least, the Early Aptian, which left its record in several outcrops along the continental margin of the Ceará State and specilically in the Xaréu off Field. The continuous operation of the regime, through the Albian and later periods, led to the definitive separation between the South American and African plates, with the formation of oceanic lithosphere between the two continental blocks, due to the emplacement off spreading centers. This process involved the subsequent transition of the transcurrent to a translorm dextral regime, creating lhe Equatorial Atlantic Oceano With the separation between the South American and African plates already completed and the increasing separation between lhe continental masses, other tecton ic mechanisms began to act during the Cenozoic (even though the Cretaceous tectonic regime lasted until the Neogene), like an E-W compressive stress líeld (related to the spreading olthe oceanic floor along lhe M id-Atlantic Ridge and to the compression of the Andean Chain) effective Irom the Late Cretaceous, and a state of general extension olthe horizontal surface (due to the thermal uplift ofthe central portion of Borborema Province), effective during the Neogene. The overlap of these mechanisms during the Cenozoic led to the imprint of a complex tectonic framework, which apparently influenced the migration and entrapment 01 hydrocarbon in the Ceará Basin

Intercontinental transport of nitrogen oxide pollution plumes

We describe the first satellite observation of intercontinental transport of nitrogen oxides emitted by power plants, verified by simulations with a particle tracer model. The analysis of such episodes shows that anthropogenic NOx plumes may influence the atmospheric chemistry thousands of kilometers away from its origin, as well as the ocean they traverse due to nitrogen fertilization. This kind of monitoring became possible by applying an improved algorithm to extract the tropospheric fraction of NO2 from the spectral data coming from the GOME instrument.As an example we show the observation of NO2 in the time period 4-14 May, 1998, from the South African Plateau to Australia which was possible due to favourable weather conditions during that time period which availed the satellite measurement. This episode was also simulated with the Lagrangian particle dispersion model FLEXPART which uses NOx emissions taken from an inventory for industrial emissions in South Africa and is driven with analyses from the European Centre for Medium-RangeWeather Forecasts. Additionally lightning emissions were taken into account by utilizing Lightning Imaging Sensor data. Lightning was found to contribute probably not more than 25% of the resulting concentrations. Both, the measured and simulated emission plume show matching patterns while traversing the Indian Ocean to Australia and show great resemblance to the aerosol and CO2 transport observed by Piketh et al. (2000).

Characterization of the temperature, load and damage effects using piezoelectric transducer patches based on fuzzy clustering

Structural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in a structure. One of the critical challenges for practical implementation of SHM system is the ability to detect damage under changing environmental conditions. This paper aims to characterize the temperature, load and damage effects in the sensor measurements obtained with piezoelectric transducer (PZT) patches. Data sets are collected on thin aluminum specimens under different environmental conditions and artificially induced damage states. The fuzzy clustering algorithm is used to organize the sensor measurements into a set of clusters, which can attribute the variation in sensor data due to temperature, load or any induced damage.