VISUAL-INERTIAL INTEGRATION FOR HUMAN MOTION TRACKING AND NAVIGATION IN FREE-LIVING ENVIRONMENTS

The aging population has become a burning issue for all modern societies around the world recently. There are two important issues existing now to be solved. One is how to continuously monitor the movements of those people having suffered a stroke in natural living environment for providing more valuable feedback to guide clinical interventions. The other one is how to guide those old people effectively when they are at home or inside other buildings and to make their life easier and convenient. Therefore, human motion tracking and navigation have been active research fields with the increasing number of elderly people. However, motion capture has been extremely challenging to go beyond laboratory environments and obtain accurate measurements of human physical activity especially in free-living environments, and navigation in free-living environments also poses some problems such as the denied GPS signal and the moving objects commonly presented in free-living environments. This thesis seeks to develop new technologies to enable accurate motion tracking and positioning in free-living environments. This thesis comprises three specific goals using our developed IMU board and the camera from the imaging source company: (1) to develop a robust and real-time orientation algorithm using only the measurements from IMU; (2) to develop a robust distance estimation in static free-living environments to estimate people’s position and navigate people in static free-living environments and simultaneously the scale ambiguity problem, usually appearing in the monocular camera tracking, is solved by integrating the data from the visual and inertial sensors; (3) in case of moving objects viewed by the camera existing in free-living environments, to firstly design a robust scene segmentation algorithm and then respectively estimate the motion of the vIMU system and moving objects. To achieve real-time orientation tracking, an Adaptive-Gain Orientation Filter (AGOF) is proposed in this thesis based on the basic theory of deterministic approach and frequency-based approach using only measurements from the newly developed MARG (Magnet, Angular Rate, and Gravity) sensors. To further obtain robust positioning, an adaptive frame-rate vision-aided IMU system is proposed to develop and implement fast vIMU ego-motion estimation algorithms, where the orientation is estimated in real time from MARG sensors in the first step and then used to estimate the position based on the data from visual and inertial sensors. In case of the moving objects viewed by the camera existing in free-living environments, a robust scene segmentation algorithm is firstly proposed to obtain position estimation and simultaneously the 3D motion of moving objects. Finally, corresponding simulations and experiments have been carried out.

Localization and Tracking in Energy-Constrained Networks with Dynamic Connectivity

Systems used for target localization, such as goods, individuals, or animals, commonly rely on operational means to meet the final application demands. However, what would happen if some means were powered up randomly by harvesting systems? And what if those devices not randomly powered had their duty cycles restricted? Under what conditions would such an operation be tolerable in localization services? What if the references provided by nodes in a tracking problem were distorted? Moreover, there is an underlying topic common to the previous questions regarding the transfer of conceptual models to reality in field tests: what challenges are faced upon deploying a localization network that integrates energy harvesting modules? The application scenario of the system studied is a traditional herding environment of semi domesticated reindeer (Rangifer tarandus tarandus) in northern Scandinavia. In these conditions, information on approximate locations of reindeer is as important as environmental preservation. Herders also need cost-effective devices capable of operating unattended in, sometimes, extreme weather conditions. The analyses developed are worthy not only for the specific application environment presented, but also because they may serve as an approach to performance of navigation systems in absence of reasonably accurate references like the ones of the Global Positioning System (GPS). A number of energy-harvesting solutions, like thermal and radio-frequency harvesting, do not commonly provide power beyond one milliwatt. When they do, battery buffers may be needed (as it happens with solar energy) which may raise costs and make systems more dependent on environmental temperatures. In general, given our problem, a harvesting system is needed that be capable of providing energy bursts of, at least, some milliwatts. Many works on localization problems assume that devices have certain capabilities to determine unknown locations based on range-based techniques or fingerprinting which cannot be assumed in the approach considered herein. The system presented is akin to range-free techniques, but goes to the extent of considering very low node densities: most range-free techniques are, therefore, not applicable. Animal localization, in particular, uses to be supported by accurate devices such as GPS collars which deplete batteries in, maximum, a few days. Such short-life solutions are not particularly desirable in the framework considered. In tracking, the challenge may times addressed aims at attaining high precision levels from complex reliable hardware and thorough processing techniques. One of the challenges in this Thesis is the use of equipment with just part of its facilities in permanent operation, which may yield high input noise levels in the form of distorted reference points. The solution presented integrates a kinetic harvesting module in some nodes which are expected to be a majority in the network. These modules are capable of providing power bursts of some milliwatts which suffice to meet node energy demands. The usage of harvesting modules in the aforementioned conditions makes the system less dependent on environmental temperatures as no batteries are used in nodes with harvesters--it may be also an advantage in economic terms. There is a second kind of nodes. They are battery powered (without kinetic energy harvesters), and are, therefore, dependent on temperature and battery replacements. In addition, their operation is constrained by duty cycles in order to extend node lifetime and, consequently, their autonomy. There is, in turn, a third type of nodes (hotspots) which can be static or mobile. They are also battery-powered, and are used to retrieve information from the network so that it is presented to users. The system operational chain starts at the kinetic-powered nodes broadcasting their own identifier. If an identifier is received at a battery-powered node, the latter stores it for its records. Later, as the recording node meets a hotspot, its full record of detections is transferred to the hotspot. Every detection registry comprises, at least, a node identifier and the position read from its GPS module by the battery-operated node previously to detection. The characteristics of the system presented make the aforementioned operation own certain particularities which are also studied. First, identifier transmissions are random as they depend on movements at kinetic modules--reindeer movements in our application. Not every movement suffices since it must overcome a certain energy threshold. Second, identifier transmissions may not be heard unless there is a battery-powered node in the surroundings. Third, battery-powered nodes do not poll continuously their GPS module, hence localization errors rise even more. Let's recall at this point that such behavior is tight to the aforementioned power saving policies to extend node lifetime. Last, some time is elapsed between the instant an identifier random transmission is detected and the moment the user is aware of such a detection: it takes some time to find a hotspot. Tracking is posed as a problem of a single kinetically-powered target and a population of battery-operated nodes with higher densities than before in localization. Since the latter provide their approximate positions as reference locations, the study is again focused on assessing the impact of such distorted references on performance. Unlike in localization, distance-estimation capabilities based on signal parameters are assumed in this problem. Three variants of the Kalman filter family are applied in this context: the regular Kalman filter, the alpha-beta filter, and the unscented Kalman filter. The study enclosed hereafter comprises both field tests and simulations. Field tests were used mainly to assess the challenges related to power supply and operation in extreme conditions as well as to model nodes and some aspects of their operation in the application scenario. These models are the basics of the simulations developed later. The overall system performance is analyzed according to three metrics: number of detections per kinetic node, accuracy, and latency. The links between these metrics and the operational conditions are also discussed and characterized statistically. Subsequently, such statistical characterization is used to forecast performance figures given specific operational parameters. In tracking, also studied via simulations, nonlinear relationships are found between accuracy and duty cycles and cluster sizes of battery-operated nodes. The solution presented may be more complex in terms of network structure than existing solutions based on GPS collars. However, its main gain lies on taking advantage of users' error tolerance to reduce costs and become more environmentally friendly by diminishing the potential amount of batteries that can be lost. Whether it is applicable or not depends ultimately on the conditions and requirements imposed by users' needs and operational environments, which is, as it has been explained, one of the topics of this Thesis.

Distributed control strategies for photovoltaic systems in urban environments

Este trabajo es una contribución a los sistemas fotovoltaicos (FV) con seguimiento distribuido del punto de máxima potencia (DMPPT), una topología que se caracteriza porque lleva a cabo el MPPT a nivel de módulo, al contrario de las topologías más tradicionales que llevan a cabo el MPPT para un número más elevado de módulos, pudiendo ser hasta cientos de módulos. Las dos tecnologías DMPPT que existen en el mercado son conocidos como microinversores y optimizadores de potencia, y ofrecen ciertas ventajas sobre sistemas de MPPT central como: mayor producción en situaciones de mismatch, monitorización individual de cada módulo, flexibilidad de diseño, mayor seguridad del sistema, etc. Aunque los sistemas DMPPT no están limitados a los entornos urbanos, se ha enfatizado en el título ya que es su mercado natural, siendo difícil una justificación de su sobrecoste en grandes huertas solares en suelo. Desde el año 2010 el mercado de estos sistemas ha incrementado notablemente y sigue creciendo de una forma continuada. Sin embargo, todavía falta un conocimiento profundo de cómo funcionan estos sistemas, especialmente en el caso de los optimizadores de potencia, de las ganancias energéticas esperables en condiciones de mismatch y de las posibilidades avanzadas de diagnóstico de fallos. El principal objetivo de esta tesis es presentar un estudio completo de cómo funcionan los sistemas DMPPT, sus límites y sus ventajas, así como experimentos varios que verifican la teoría y el desarrollo de herramientas para valorar las ventajas de utilizar DMPPT en cada instalación. Las ecuaciones que modelan el funcionamiento de los sistemas FVs con optimizadores de potencia se han desarrollado y utilizado para resaltar los límites de los mismos a la hora de resolver ciertas situaciones de mismatch. Se presenta un estudio profundo sobre el efecto de las sombras en los sistemas FVs: en la curva I-V y en los algoritmos MPPT. Se han llevado a cabo experimentos sobre el funcionamiento de los algoritmos MPPT en situaciones de sombreado, señalando su ineficiencia en estas situaciones. Un análisis de la ventaja del uso de DMPPT frente a los puntos calientes es presentado y verificado. También se presenta un análisis sobre las posibles ganancias en potencia y energía con el uso de DMPPT en condiciones de sombreado y este también es verificado experimentalmente, así como un breve estudio de su viabilidad económica. Para ayudar a llevar a cabo todos los análisis y experimentos descritos previamente se han desarrollado una serie de herramientas software. Una siendo un programa en LabView para controlar un simulador solar y almacenar las medidas. También se ha desarrollado un programa que simula curvas I-V de módulos y generador FVs afectados por sombras y este se ha verificado experimentalmente. Este mismo programa se ha utilizado para desarrollar un programa todavía más completo que estima las pérdidas anuales y las ganancias obtenidas con DMPPT en instalaciones FVs afectadas por sombras. Finalmente, se han desarrollado y verificado unos algoritmos para diagnosticar fallos en sistemas FVs con DMPPT. Esta herramienta puede diagnosticar los siguientes fallos: sombras debido a objetos fijos (con estimación de la distancia al objeto), suciedad localizada, suciedad general, posible punto caliente, degradación de módulos y pérdidas en el cableado de DC. Además, alerta al usuario de las pérdidas producidas por cada fallo y no requiere del uso de sensores de irradiancia y temperatura. ABSTRACT This work is a contribution to photovoltaic (PV) systems with distributed maximum power point tracking (DMPPT), a system topology characterized by performing the MPPT at module level, instead of the more traditional topologies which perform MPPT for a larger number of modules. The two DMPPT technologies available at the moment are known as microinverters and power optimizers, also known as module level power electronics (MLPE), and they provide certain advantages over central MPPT systems like: higher energy production in mismatch situations, monitoring of each individual module, system design flexibility, higher system safety, etc. Although DMPPT is not limited to urban environments, it has been emphasized in the title as it is their natural market, since in large ground-mounted PV plants the extra cost is difficult to justify. Since 2010 MLPE have increased their market share steadily and continuing to grow steadily. However, there still lacks a profound understanding of how they work, especially in the case of power optimizers, the achievable energy gains with their use and the possibilities in failure diagnosis. The main objective of this thesis is to provide a complete understanding of DMPPT technologies: how they function, their limitations and their advantages. A series of equations used to model PV arrays with power optimizers have been derived and used to point out limitations in solving certain mismatch situation. Because one of the most emphasized benefits of DMPPT is their ability to mitigate shading losses, an extensive study on the effects of shadows on PV systems is presented; both on the I-V curve and on MPPT algorithms. Experimental tests have been performed on the MPPT algorithms of central inverters and MLPE, highlighting their inefficiency in I-V curves with local maxima. An analysis of the possible mitigation of hot-spots with DMPPT is discussed and experimentally verified. And a theoretical analysis of the possible power and energy gains is presented as well as experiments in real PV systems. A short economic analysis of the benefits of DMPPT has also been performed. In order to aide in the previous task, a program which simulates I-V curves under shaded conditions has been developed and experimentally verified. This same program has been used to develop a software tool especially designed for PV systems affected by shading, which estimates the losses due to shading and the energy gains obtained with DMPPT. Finally, a set of algorithms for diagnosing system faults in PV systems with DMPPT has been developed and experimentally verified. The tool can diagnose the following failures: fixed object shading (with distance estimation), localized dirt, generalized dirt, possible hot-spots, module degradation and excessive losses in DC cables. In addition, it alerts the user of the power losses produced by each failure and classifies the failures by their severity and it does not require the use of irradiance or temperature sensors.

Sistema de adquisición de datos para una aplicación de detección del ruido de reversa en tiempo real

Entre todas las fuentes de ruido, la activación de la propulsión en reversa de un avión después de aterrizar es conocida por las autoridades del aeropuerto como una causa importante de impacto acústico, molestias y quejas en las proximidades vecinas de los aeropuertos. Por ello, muchos de los aeropuertos de todo el mundo han establecido restricciones en el uso de la reversa, especialmente en las horas de la noche. Una forma de reducir el impacto acústico en las actividades aeroportuarias es implementar herramientas eficaces para la detección de ruido en reversa en los aeropuertos. Para este proyecto de fin de carrera, aplicando la metodología TREND (Thrust Reverser Noise Detection), se pretende desarrollar un sistema software capaz de determinar que una aeronave que aterrice en la pista active el frenado en reversa en tiempo real. Para el diseño de la aplicación se plantea un modelo software, que se compone de dos módulos:  El módulo de adquisición de señales acústicas, simula un sistema de captación por señales de audio. Éste módulo obtiene muestra de señales estéreo de ficheros de audio de formato “.WAV” o del sistema de captación, para acondicionar las muestras de audio y enviarlas al siguiente módulo. El sistema de captación (array de micrófonos), se encuentra situado en una localización cercana a la pista de aterrizaje.  El módulo de procesado busca los eventos de detección aplicando la metodología TREND con las muestras acústicas que recibe del módulo de adquisición. La metodología TREND describe la búsqueda de dos eventos sonoros llamados evento 1 (EV1) y evento 2 (EV2); el primero de ellos, es el evento que se activa cuando una aeronave aterriza discriminando otros eventos sonoros como despegues de aviones y otros sonidos de fondo, mientras que el segundo, se producirá después del evento 1, sólo cuando la aeronave utilice la reversa para frenar. Para determinar la detección del evento 1, es necesario discriminar las señales ajenas al aterrizaje aplicando un filtrado en la señal capturada, después, se aplicará un detector de umbral del nivel de presión sonora y por último, se determina la procedencia de la fuente de sonido con respecto al sistema de captación. En el caso de la detección del evento 2, está basada en la implementación de umbrales en la evolución temporal del nivel de potencia acústica aplicando el modelo de propagación inversa, con ayuda del cálculo de la estimación de la distancia en cada instante de tiempo mientras el avión recorre la pista de aterrizaje. Con cada aterrizaje detectado se realiza una grabación que se archiva en una carpeta específica y todos los datos adquiridos, son registrados por la aplicación software en un fichero de texto. ABSTRACT. Among all noise sources, the activation of reverse thrust to slow the aircraft after landing is considered as an important cause of noise pollution by the airport authorities, as well as complaints and annoyance in the airport´s nearby locations. Therefore, many airports around the globe have restricted the use of reverse thrust, especially during the evening hours. One way to reduce noise impact on airport activities is the implementation of effective tools that deal with reverse noise detection. This Final Project aims to the development of a software system capable of detecting if an aircraft landing on the runway activates reverse thrust on real time, using the TREND (Thrust Reverser Noise Detection) methodology. To design this application, a two modules model is proposed: • The acoustic signals obtainment module, which simulates an audio waves based catchment system. This module obtains stereo signal samples from “.WAV” audio files or the catchment system in order to prepare these audio samples and send them to the next module. The catchment system (a microphone array) is located on a place near the landing runway. • The processing module, which looks for detection events among the acoustic samples received from the other module, using the TREND methodology. The TREND methodology describes the search of two sounds events named event 1 (EV1) and event 2 (EV2). The first is the event activated by a landing plane, discriminating other sound events such as background noises or taking off planes; the second one will occur after event one only when the aircraft uses reverse to slow down. To determine event 1 detection, signals outside the landing must be discriminated using a filter on the catched signal. A pressure level´s threshold detector will be used on the signal afterwards. Finally, the origin of the sound source is determined regarding the catchment system. The detection of event 2 is based on threshold implementations in the temporal evolution of the acoustic power´s level by using the inverse propagation model and calculating the distance estimation at each time step while the plane goes on the landing runway. A recording is made every time a landing is detected, which is stored in a folder. All acquired data are registered by the software application on a text file.

Distributed control strategies for photovoltaic systems in urban environments : Versión definitiva

Este trabajo es una contribución a los sistemas fotovoltaicos (FV) con seguimiento distribuido del punto de máxima potencia (DMPPT), una topología que se caracteriza porque lleva a cabo el MPPT a nivel de módulo, al contrario de las topologías más tradicionales que llevan a cabo el MPPT para un número más elevado de módulos, pudiendo ser hasta cientos de módulos. Las dos tecnologías DMPPT que existen en el mercado son conocidos como microinversores y optimizadores de potencia, y ofrecen ciertas ventajas sobre sistemas de MPPT central como: mayor producción en situaciones de mismatch, monitorización individual de cada módulo, flexibilidad de diseño, mayor seguridad del sistema, etc. Aunque los sistemas DMPPT no están limitados a los entornos urbanos, se ha enfatizado en el título ya que es su mercado natural, siendo difícil una justificación de su sobrecoste en grandes huertas solares en suelo. Desde el año 2010 el mercado de estos sistemas ha incrementado notablemente y sigue creciendo de una forma continuada. Sin embargo, todavía falta un conocimiento profundo de cómo funcionan estos sistemas, especialmente en el caso de los optimizadores de potencia, de las ganancias energéticas esperables en condiciones de mismatch y de las posibilidades avanzadas de diagnóstico de fallos. El principal objetivo de esta tesis es presentar un estudio completo de cómo funcionan los sistemas DMPPT, sus límites y sus ventajas, así como experimentos varios que verifican la teoría y el desarrollo de herramientas para valorar las ventajas de utilizar DMPPT en cada instalación. Las ecuaciones que modelan el funcionamiento de los sistemas FVs con optimizadores de potencia se han desarrollado y utilizado para resaltar los límites de los mismos a la hora de resolver ciertas situaciones de mismatch. Se presenta un estudio profundo sobre el efecto de las sombras en los sistemas FVs: en la curva I-V y en los algoritmos MPPT. Se han llevado a cabo experimentos sobre el funcionamiento de los algoritmos MPPT en situaciones de sombreado, señalando su ineficiencia en estas situaciones. Un análisis de la ventaja del uso de DMPPT frente a los puntos calientes es presentado y verificado. También se presenta un análisis sobre las posibles ganancias en potencia y energía con el uso de DMPPT en condiciones de sombreado y este también es verificado experimentalmente, así como un breve estudio de su viabilidad económica. Para ayudar a llevar a cabo todos los análisis y experimentos descritos previamente se han desarrollado una serie de herramientas software. Una siendo un programa en LabView para controlar un simulador solar y almacenar las medidas. También se ha desarrollado un programa que simula curvas I-V de módulos y generador FVs afectados por sombras y este se ha verificado experimentalmente. Este mismo programa se ha utilizado para desarrollar un programa todavía más completo que estima las pérdidas anuales y las ganancias obtenidas con DMPPT en instalaciones FVs afectadas por sombras. Finalmente, se han desarrollado y verificado unos algoritmos para diagnosticar fallos en sistemas FVs con DMPPT. Esta herramienta puede diagnosticar los siguientes fallos: sombras debido a objetos fijos (con estimación de la distancia al objeto), suciedad localizada, suciedad general, posible punto caliente, degradación de módulos y pérdidas en el cableado de DC. Además, alerta al usuario de las pérdidas producidas por cada fallo y no requiere del uso de sensores de irradiancia y temperatura. ABSTRACT This work is a contribution to photovoltaic (PV) systems with distributed maximum power point tracking (DMPPT), a system topology characterized by performing the MPPT at module level, instead of the more traditional topologies which perform MPPT for a larger number of modules. The two DMPPT technologies available at the moment are known as microinverters and power optimizers, also known as module level power electronics (MLPE), and they provide certain advantages over central MPPT systems like: higher energy production in mismatch situations, monitoring of each individual module, system design flexibility, higher system safety, etc. Although DMPPT is not limited to urban environments, it has been emphasized in the title as it is their natural market, since in large ground-mounted PV plants the extra cost is difficult to justify. Since 2010 MLPE have increased their market share steadily and continuing to grow steadily. However, there still lacks a profound understanding of how they work, especially in the case of power optimizers, the achievable energy gains with their use and the possibilities in failure diagnosis. The main objective of this thesis is to provide a complete understanding of DMPPT technologies: how they function, their limitations and their advantages. A series of equations used to model PV arrays with power optimizers have been derived and used to point out limitations in solving certain mismatch situation. Because one of the most emphasized benefits of DMPPT is their ability to mitigate shading losses, an extensive study on the effects of shadows on PV systems is presented; both on the I-V curve and on MPPT algorithms. Experimental tests have been performed on the MPPT algorithms of central inverters and MLPE, highlighting their inefficiency in I-V curves with local maxima. An analysis of the possible mitigation of hot-spots with DMPPT is discussed and experimentally verified. And a theoretical analysis of the possible power and energy gains is presented as well as experiments in real PV systems. A short economic analysis of the benefits of DMPPT has also been performed. In order to aide in the previous task, a program which simulates I-V curves under shaded conditions has been developed and experimentally verified. This same program has been used to develop a software tool especially designed for PV systems affected by shading, which estimates the losses due to shading and the energy gains obtained with DMPPT. Finally, a set of algorithms for diagnosing system faults in PV systems with DMPPT has been developed and experimentally verified. The tool can diagnose the following failures: fixed object shading (with distance estimation), localized dirt, generalized dirt, possible hot-spots, module degradation and excessive losses in DC cables. In addition, it alerts the user of the power losses produced by each failure and classifies the failures by their severity and it does not require the use of irradiance or temperature sensors.

Investigando a compressão da percepção de distância em ambientes virtuais através da comparação entre dispositivos de visualização

The correct distance perception is important for executing various interactive tasks such as navigation, selection and manipulation. It is known, however, that, in general, there is a significant distance perception compression in virtual environments, mainly when using Head-Mounted Displays - HMDs. This perceived distance compression may bring various problems to the applications and even affect in a negative way the utility of those applications that depends on the correct judgment of distances. The scientific community, so far, have not been able to determine the causes of the distance perception compression in virtual environments. For this reason, it was the objective of this work to investigate, through experiments with users, the influence of both the field-of-view - FoV - and the distance estimation methods on this perceived compression. For that, an experimental comparison between the my3D device and a HMD, using 32 participants, seeking to find information on the causes of the compressed perception, was executed. The results showed that the my3D has inferior capabilities when compared to the HMD, resulting in worst estimations, on average, in both the tested estimation methods. The causes of that are believed to be the incorrect stimulus of the peripheral vision of the user, the smaller FoV and the smaller immersion sense, as described by the participants of the experiment.

The estimation of the thermodynamic properties of ternary alloys from binary data using the shortest distance composition path

A new composition path, Xi-Xj=constant, is suggested for the semi-empirical calculation of the thermodynamic properties of ternary ‘substitutional’ solutions from binary data, when the binary systems show deviations from the regular solution model. A comparison is made between the results obtained for integral and partial properties using this composition path and those calculated employing other composition paths suggested in literature. It appears that the best estimate of the ternary properties is obtained when binary data at compositions closest to the ternary composition are used.

Estimation of Correlation Distance of Soil Properties by Geostatistics

Random field theory has been used to model the spatial average soil properties, whereas the most widely used, geostatistics, on which also based a common basis (covariance function) has been successfully used to model and estimate natural resource since 1960s. Therefore, geostistics should in principle be an efficient way to model soil spatial variability Based on this, the paper presents an alternative approach to estimate the scale of fluctuation or correlation distance of a soil stratum by geostatistics. The procedure includes four steps calculating experimental variogram from measured data, selecting a suited theoretical variogram model, fitting the theoretical one to the experimental variogram, taking the parameters within the theoretical model obtained from optimization into a simple and finite correlation distance 6 relationship to the range a. The paper also gives eight typical expressions between a and b. Finally, a practical example was presented for showing the methodology.

Extending Distance-based Ranking Models In Estimation of Distribution Algorithms

Recently, probability models on rankings have been proposed in the field of estimation of distribution algorithms in order to solve permutation-based combinatorial optimisation problems. Particularly, distance-based ranking models, such as Mallows and Generalized Mallows under the Kendall’s-t distance, have demonstrated their validity when solving this type of problems. Nevertheless, there are still many trends that deserve further study. In this paper, we extend the use of distance-based ranking models in the framework of EDAs by introducing new distance metrics such as Cayley and Ulam. In order to analyse the performance of the Mallows and Generalized Mallows EDAs under the Kendall, Cayley and Ulam distances, we run them on a benchmark of 120 instances from four well known permutation problems. The conducted experiments showed that there is not just one metric that performs the best in all the problems. However, the statistical test pointed out that Mallows-Ulam EDA is the most stable algorithm among the studied proposals.

Estimation of Gaussian process regression model using probability distance measures

A new class of parameter estimation algorithms is introduced for Gaussian process regression (GPR) models. It is shown that the integration of the GPR model with probability distance measures of (i) the integrated square error and (ii) Kullback–Leibler (K–L) divergence are analytically tractable. An efficient coordinate descent algorithm is proposed to iteratively estimate the kernel width using golden section search which includes a fast gradient descent algorithm as an inner loop to estimate the noise variance. Numerical examples are included to demonstrate the effectiveness of the new identification approaches.

Long-distance photogrammetric trait estimation in free-ranging animals: A new approach

The acquisition of accurate information on the size of traits in animals is fundamental for the study of animal ecology and evolution and their management. We demonstrate how morphological traits of free-ranging animals can reliably be estimated on very large observation distances of several hundred meters by the use of ordinary digital photographic equipment and simple photogrammetric software. In our study, we estimated the length of horn annuli in free-ranging male Alpine ibex (Capra ibex) by taking already measured horn annuli of conspecifics on the same photographs as scaling units. Comparisons with hand-measured horn annuli lengths and repeatability analyses revealed a high accuracy of the photogrammetric estimates. If length estimations of specific horn annuli are based on multiple photographs measurement errors of <5.5 mm can be expected. In the current study the application of the described photogrammetric procedure increased the sample size of animals with known horn annuli length by an additional 104%. The presented photogrammetric procedure is of broad applicability and represents an easy, robust and cost-efficient method for the measuring of individuals in populations where animals are hard to capture or to approach.

Constrained nonparametric estimation of input distance function

This paper proposes a constrained nonparametric method of estimating an input distance function. A regression function is estimated via kernel methods without functional form assumptions. To guarantee that the estimated input distance function satisfies its properties, monotonicity constraints are imposed on the regression surface via the constraint weighted bootstrapping method borrowed from statistics literature. The first, second, and cross partial analytical derivatives of the estimated input distance function are derived, and thus the elasticities measuring input substitutability can be computed from them. The method is then applied to a cross-section of 3,249 Norwegian timber producers.

Robust pose estimation for a car-like vehicle

In this paper, we outline the sensing system used for the visual pose control of our experimental car-like vehicle, the autonomous tractor. The sensing system consists of a magnetic compass, an omnidirectional camera and a low-resolution odometry system. In this work, information from these sensors is fused using complementary filters. Complementary filters provide a means of fusing information from sensors with different characteristics in order to produce a more reliable estimate of the desired variable. Here, the range and bearing of landmarks observed by the vision system are fused with odometry information and a vehicle model, providing a more reliable estimate of these states. We also present a method of combining a compass sensor with odometry and a vehicle model to improve the heading estimate.

Automatic in-bucket volume estimation for dragline operations

This paper presents a method for calculating the in-bucket payload volume on a dragline for the purpose of estimating the material’s bulk density in real-time. Knowledge of the bulk density can provide instant feedback to mine planning and scheduling to improve blasting and in turn provide a more uniform bulk density across the excavation site. Furthermore costs and emissions in dragline operation, maintenance and downstream material processing can be reduced. The main challenge is to determine an accurate position and orientation of the bucket with the constraint of real-time performance. The proposed solution uses a range bearing and tilt sensor to locate and scan the bucket between the lift and dump stages of the dragline cycle. Various scanning strategies are investigated for their benefits in this real-time application. The bucket is segmented from the scene using cluster analysis while the pose of the bucket is calculated using the iterative closest point (ICP) algorithm. Payload points are segmented from the bucket by a fixed distance neighbour clustering method to preserve boundary points and exclude low density clusters introduced by overhead chains and the spreader bar. A height grid is then used to represent the payload from which the volume can be calculated by summing over the grid cells. We show volume calculated on a scaled system with an accuracy of greater than 95 per cent.