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Ranjbar, Gigasari Roza. "Model Predictive Controller for large-scale systems - Application to water networks." Electronic Thesis or Diss., Ecole nationale supérieure Mines-Télécom Lille Douai, 2024. http://www.theses.fr/2024MTLD0002.
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Cette thèse aborde le défi de l’optimisation de la gestion des ressources en eau au sein des canaux. Il s’agit d’une tâche particulièrement complexe en raison de leur échelle étendue et de la nature diverse de leurs composants, mais également de leurs dynamiques complexes caractérisées par des retards importants et parfois des pentes nulles. En ce qui concerne les réseaux de voies navigables, l’objectif principal est de mettre en œuvre des techniques issues de la théorie du Contrôle afin d’assurer la navigabilité du réseau, garantissant le respect des niveaux d’eau pour la navigation. Plus précisément, les niveaux d’eau doivent demeurer dans une plage prédéfinie autour d’un point de consigne. D’autres objectifs visent en la réduction des coûts opérationnels et l’amélioration de la durabilité des équipements. A cet égard, une alternative dans la gestion de tels réseaux est de remplacer les capteurs le long des canaux par un robot mobile qui effectue les mesures requises en se déplaçant, limitant l’ensemble des tâches de déploiement et de maintenance des capteurs et des systèmes de transmission de l’information. Pour parvenir à une gestion efficiente, il est impératif de garantir un contrôle efficace des structures hydrauliques telles que les vannes, les pompes et les écluses tout en limitant leur utilisation. A cette fin, un algorithme de contrôle est introduit, basé sur un modèle existant dérivé des équations de Saint-Venant. Le modèle simplifié offre une facilité d’intégration des informations actuelles et retardées du système dynamique en simplifiant sa complexité originale. L’utilisation de ce modèle nécessite cependant certaines extensions aux outils standards de contrôle et d’estimation d’état standard. Des méthodes de contrôle prédictif, de type MPC, et des méthodes d’estimation de l’état du système, de type MHE, sont adaptées à ce modèle. Elles permettent de considérer les contraintes physiques et opérationnelles des canaux contrôlés. Le MPC centralisé offre une résilience grâce à son couplage avec la technique MHE. Sa nature déterministe limite cependant sa capacité à aborder systématiquement les incertitudes. Pour relever efficacement ces incertitudes, la mise en œuvre du MPC stochastique (SMPC) a ensuite été proposée. Le SMPC intègre des descriptions probabilistes dans la conception du contrôle, offrant une approche tenant compte des incertitudes. Dans ce contexte d’études, le SMPC est interconnecté avec un robot mobile dont l’usage vise à limiter le nombre de capteurs répartis le long du canal. Par conséquent, une partie de cette thèse se concentre sur la conception du SMPC en intégrant un robot mobile. Cette approche a été appliquée à un canal de test ASCE pour en évaluer l’efficacité. Compte tenu de la nature étendu et de la complexité des interactions des canaux avec leur environnement, une conception d’un jumeau numérique a été entreprise avec pour objectifs de répondre aux besoins d’outils d’analyse avancée de leur gestion. En exploitant les capacités des jumeaux numériques, nous avons cherché à améliorer notre compréhension des dynamiques des canaux, en considérant des scénarios passés, mais également à projeter les avantages de nouvelles stratégies de gestion et de contrôle. Cette évaluation vise à combler le fossé entre la théorie et la mise en œuvre pratique, offrant un moyen tangible de rejouer les événements passés, de tester diverses approches de gestion et, finalement, de proposer aux gestionnaires des outils et des critères conduisant à une gestion efficace des réseaux hydrographiques. Les méthodologies présentées dans cette thèse sont appliquées à un cas réel, un canal situé dans la région des Hauts de France, avec l’objectif de tester et de valider leur efficacité dans un contexte réelThis thesis addresses the challenge of optimizing the management of canals, a complex task due to their extensive scale and distinctive attributes, including intricate dynamics, considerable time delays, and minimal bottom slopes. Specifically, the central goal is to ensure the navigability of the network, which involves maintaining safe water levels for vessel travel, through control theory. More precisely, the water levels must remain within a predefined range around a setpoint. Additionally, typical aims encompass reducing operational costs and enhancing the equipment’s life expectancy. In this regard, another objective in the management of such networks is replacing the possible sensors across canals by applying a moving robot to take the required measurements. To accomplish effective management, it becomes imperative to ensure efficient control over hydraulic structures such as gates, pumps, and locks. To this end, a control algorithm is introduced based on an existing model derived from the Saint-Venant equations. The modeling approach simplified the original complex description providing adaptability and facilitating the systematic integration of both current and delayed information. However, the resulting model formulation falls within the category of delayed descriptor systems, necessitating extensions to standard control and state estimation tools. Model predictive control and moving horizon estimation methods can be readily tailored for this formulation, while also adapting physical and operational constraints seamlessly. Given the extensive nature of canals, an evaluation of the digital twin was untaken to address the critical need for advanced tools in the management of such networks. By harnessing the capabilities of digital twins, we aimed to enhance our understanding of canal dynamics, past scenarios, and management strategies. This evaluation sought to bridge the gap between theory and practical implementation, offering a tangible means to playback past events, test diverse management approaches, and ultimately equip decision-makers with robust criteria for informed and effective network management.The methodologies presented above are applied to a practical case study, a canal in the northern region of France. The objective is to validate the efficacy of these approaches in a real-world context.While centralized MPC provides resilience through its receding-horizon approach, its deterministic nature limits its ability to systematically address uncertainties. To effectively tackle these system uncertainties, the implementation of Stochastic MPC (SMPC) has been adopted. SMPC integrates probabilistic descriptions into control design, offering a methodical approach to accommodating uncertainties. In this context, the application of SMPC is interconnected with a mobile robot aimed at replacing existing sensors along the canal to capture measurements. Consequently, a part of this thesis focuses on the design of SMPC in conjunction with a mobile robot. This approach has been applied to an ASCE Test canal to evaluate its effectiveness
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Poquin, Didier. "Estimation de la verticale subjective en tangage : contribution de l'horizon visuel apparent." Grenoble 2, 1998. http://www.theses.fr/1998GRE29016.
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Le point de vue de l'observateur est un facteur essentiel pour estimer l'inclinaison en tangage d'une surface. Dans ce cadre, l'hypothèse selon laquelle la détermination de la verticale subjective en tangage (VST) passe par l'estimation de l'horizon visuel subjectif (HVS) a donc été posée. Pour évaluer la VST, il a été demandé à des sujets d'ajuster dans la direction gravitaire une baguette lumineuse et rectangulaire et pour estimer l'horizon visuel, de placer juste en face de leurs yeux et dans un plan horizontal un petit trait également lumineux. Une première série de résultats a montré que les mécanismes de détermination de la VST font appel aux indices géométriques en rapport avec la forme de la baguette et a l'estimation du niveau des yeux. Ils rendent compte de l'indépendance observée entre le roulis et le tangage dans les ajustements à la verticale gravitaire et de la déviation systématique de la VST, "sommet de la baguette vers l'observateur". La deuxième partie expérimentale a décrit deux mécanismes impliquant l'HVS dans le jugement de la VST. Le premier dit "d'orthogonalisation centrée" conduit à ajuster la surface perpendiculairement à une ligne reliant le centre de la cible et le niveau perçu des yeux. Cette stratégie est mise en place pour de petits décalages de l'HVS. Le deuxième mécanisme, dit de "surcompensation", s'observe quand l'observateur prend conscience du décalage de son HVS et qu'il compense l'écart de ce point de vue subjectif. La conséquence de son utilisation conduit à ajuster la cible en sens oppose à la stratégie précédente. Le mécanisme de surcompensation intervient pour de grands décalages de l'HVS par rapport à l'horizon gravitaire. La dernière section expérimentale a confirmé, en présence d'un cadre perturbateur, l'existence des mécanismes d'orthogonalisation centrée et de surcompensation dans les ajustements d'une baguette à la verticale en tangage en fonction de l'amplitude du décalage de l'HVS. Cette dernière partie à également montré que l'effet d'attraction d'un cadre incliné, classiquement observé en roulis sur la verticale subjective, est observé en tangage sur la VST et sur l'HVS. En conclusion, le niveau apparent des yeux est considèré par un observateur comme le point de vue à partir duquel il perçoit l'orientation des surfaces en tangageThe factors determining spatial orientation in the median plane have been relatively neglected, although this dimension is the preferential plane of human displacements and the alert reaction in case of danger. Concerning pitch orientation, the observers point of view is an essential factor to estimate the surface slant. In this frame, the hypothesis according to pitch visually perceived vertical (pitch VPV) is assessed from visually perceived eye level (VPEL) has been assumed. It has been asked to an observer, seated in a dark room, to assess the subjective vertical by adjusting to the gravity direction a luminous and rectangular surface (the rod), and in other hand to judge the eye level by setting a luminous target in the horizontal plane getting through his eyes. The first part of results shows that the pitch VPV assessments have its own mechanisms whose the main factors are the geometrical cues relative to the form of the rod and the subjective eye level. Those factors could explain the lack of correlation observed between roll and pitch rod adjustments to the gravity direction and the systematic deviation of the pitch VPV, 'top of the rod toward the observer'. The second part of results describes two processes involving the VPEL to estimate the pitch VPV. The first processes, called 'mechanism of cenfered orthogonalisation', leads to adjust the rod perpendicular to an imaginary line getting through the center of the surface to the subjective eye level. This process occurs when VPEL errors are small. The second mechanism, called 'mechanism of surcompensation', is observed when the subject believes that the rod is put up or down relative to his perceived eye level. The consequence is a erroned compensation from this subjective point of view. This mechanism occurs when VPEL errors are large. The last experimental section confirms, with a visual scene, the existence of mechanisms of centered orthogonalisation or surcompensation to adjust a rod to the gravity direction in the median plane. In conclusion, the subjective eye level is considered as the point of view from which an observer calculates the slant orientation of planar surfaces. In other words, the determination of the pitch orientation of an object initially needs the estimation of the observer's localization in the environment
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Patel, Chirag S. "Channel modeling and estimation for mobile-to-mobile OFDM communications." Thesis, Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/13552.
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Alli, Idd Pazi. "Channel estimation in mobile wireless systems." Thesis, KTH, Signalbehandling, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-98754.
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The demands of multimedia services from mobile user equipment (UE) for achieving high data rate, high capacity and reliable communication in modern mobile wireless systems are continually ever-growing. As a consequence, several technologies, such as the Universal Mobile Telecommunications System (UMTS) and the 3rd Generation Partnership Project (3GPP), have been used to meet these challenges. However, due to the channel fading and the Doppler shifts caused by user mobility, a common problem in wireless systems, additional technologies are needed to combat multipath propagation fading and Doppler shifts. Time-variant channel estimation is one such crucial technique used to improve the performance of the modern wireless systems with Doppler spread and multipath spread. One of vital parts of the mobile wireless channel is channel estimation, which is a method used to significantly improve the performance of the system, especially for 4G and Long Term Evolution (LTE) systems. Channel estimation is done by estimating the time-varying channel frequency response for the OFDM symbols. Time-variant channel estimation using Discrete Prolate Spheroidal Sequences (DPSS) technique is a useful channel estimation technique in mobile wireless communication for accurately estimating transmitted information. The main advantage of DPSS or Slepian basis expansion is allowing more accurate representation of high mobility mobile wireless channels with low complexity. Systems such as the fourth generation cellular wireless standards (4G), which was recently introduced in Sweden and other countries together with the Long Term Evolution, can use channel estimation techniques for providing the high data rate in modern mobile wireless communication systems. The main goal of this thesis is to test the recently proposed method, time-variant channel estimation using Discrete Prolate Spheroidal Sequences (DPSS) to model the WINNER phase II channel model. The time-variant sub-carrier coefficients are expanded in terms of orthogonal DPS sequences, referred to as Slepian basis expansions. Both Slepian basis expansions and DPS sequences span the low-dimensional subspace of time-limited and band-limited sequences as Slepian showed. Testing is done by using just two system parameters, the maximum Doppler frequency Dmax v and K, the number of basis functions of length N = 256. The main focus of this thesis is to investigate the Power spectrum and channel gain caused by Doppler spread of the WINNER II channel model together with linear fitting of curves for both the Slepian and Fourier basis expansion models. In addition, it investigates the Mean Square Error (MSE) using the Least Squares (LS) method. The investigation was carried out by simulation in Matlab, which shows that the spectrum of the maximum velocity of the user in mobile wireless channel is upper bounded by the maximum normalized one-sided Doppler frequency. Matlab simulations support the values of the results. The value of maximum Doppler bandwidth vDmax of the WINNER model is exactly the same value as DPS sequences. In addition to the Power spectrum of the WINNER model, the fitting of Slepian basis expansion performs better in the WINNER model than that of the Fourier basis expansion.
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Angladon, Vincent. "Room layout estimation on mobile devices." Phd thesis, Toulouse, INPT, 2018. http://oatao.univ-toulouse.fr/20745/1/ANGLADON_Vincent.pdf.
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Room layout generation is the problem of generating a drawing or a digital model of an existing room from a set of measurements such as laser data or images. The generation of floor plans can find application in the building industry to assess the quality and the correctness of an ongoing construction w.r.t. the initial model, or to quickly sketch the renovation of an apartment. Real estate industry can rely on automatic generation of floor plans to ease the process of checking the livable surface and to propose virtual visits to prospective customers. As for the general public, the room layout can be integrated into mixed reality games to provide a better immersiveness experience, or used in other related augmented reality applications such room redecoration. The goal of this industrial thesis (CIFRE) is to investigate and take advantage of the state-of-the art mobile devices in order to automate the process of generating room layouts. Nowadays, modern mobile devices usually come a wide range of sensors, such as inertial motion unit (IMU), RGB cameras and, more recently, depth cameras. Moreover, tactile touchscreens offer a natural and simple way to interact with the user, thus favoring the development of interactive applications, in which the user can be part of the processing loop. This work aims at exploiting the richness of such devices to address the room layout generation problem. The thesis has three major contributions. We first show how the classic problem of detecting vanishing points in an image can benefit from an a-priori given by the IMU sensor. We propose a simple and effective algorithm for detecting vanishing points relying on the gravity vector estimated by the IMU. A new public dataset containing images and the relevant IMU data is introduced to help assessing vanishing point algorithms and foster further studies in the field. As a second contribution, we explored the state of-the-art of real-time localization and map optimization algorithms for RGB-D sensors. Real-time localization is a fundamental task to enable augmented reality applications, and thus it is a critical component when designing interactive applications. We propose an evaluation of existing algorithms for the common desktop set-up in order to be employed on a mobile device. For each considered method, we assess the accuracy of the localization as well as the computational performances when ported on a mobile device. Finally, we present a proof of concept of application able to generate the room layout relying on a Project Tango tablet equipped with an RGB-D sensor. In particular, we propose an algorithm that incrementally processes and fuses the 3D data provided by the sensor in order to obtain the layout of the room. We show how our algorithm can rely on the user interactions in order to correct the generated 3D model during the acquisition process.
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Kleynhans, Waldo. "On channel estimation for mobile WiMAX." Diss., Pretoria : [s.n.], 2008. http://upetd.up.ac.za/thesis/available/etd-01262009-102433/.
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Kasebzadeh, Parinaz. "Parameter Estimation for Mobile Positioning Applications." Licentiate thesis, Linköpings universitet, Reglerteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-141877.
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The availability and reliability of mobile positioning algorithms depend on both the quality of measurements and the environmental characteristics. The positioning systems based on global navigation satellite systems (GNSS), for example, have typically a few meters accuracy but are unavailable in signal denied conditions and unreliable in multipath environments. Other radio network based positioning algorithms have the same drawbacks. This thesis considers a couple of cases where these drawbacks can be mitigated by model-based sensor fusion techniques. The received signal strength (RSS) is commonly used in cellular radio networks for positioning due to its high availability, but its reliability depends heavily on the environment. We have studied how the directional dependence in the antenna gain in the base stations can be compensated for. We propose a semiempirical model for RSS measurements, composed of an empirical log-distance model of the RSS decay rate, and a deterministic antenna gain model that accounts for non-uniform base station antenna radiation. Evaluations and comparisons presented in this study demonstrate an improvement in estimation performance of the joint model compared to the propagation model alone. Inertial navigation systems (INS ) rely on integrating inertial sensor measurements. INS as a standalone system is known to have a cubic drift in the position error, and it needs supporting sensor information, for instance, position fixes from GNSS whenever available. For pedestrians, special tricks such as parametric gait models and step detections can be used to limit the drift. In general, the more accurate gait parameters, the better position estimation accuracy. An improved pedestrian dead reckoning (PDR) algorithm is developed that learns gait parameters in time intervals when direct position measurements (such as GNSS positions) are available. We present a multi-rate filtering solution that leads to improved estimates of both gait parameters and position. To further extend the algorithm to more realistic scenarios, a joint classifier of the user’s motion and the device’s carrying mode is developed. Classification of motion mode (walking, running, standing still) and device mode (hand-held, in pocket, in backpack) provides information that can assist in the gait learning process and hence improve the position estimation. The algorithms are applied to collected data and promising results are reported. Furthermore, one of the most extensive datasets for personal navigation systems using both rigid body motion trackers and smartphones is presented, and this dataset has also been made publicly available.
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Ning, Yu. "Mobile speed estimation for hierarchical wireless network." Diss., Columbia, Mo. : University of Missouri-Columbia, 2005. http://hdl.handle.net/10355/4298.
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Thesis (M.S.)--University of Missouri-Columbia, 2005.The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (July 14, 2006) Includes bibliographical references.
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Zhou, Bin. "Mobile velocity estimation in multipath fading channels." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0005/MQ42710.pdf.
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Thiagarajan, Arvind. "Probabilistic models for mobile phone trajectory estimation." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/68497.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 157-161).
This dissertation is concerned with the problem of determining the track or trajectory of a mobile device - for example, a sequence of road segments on an outdoor map, or a sequence of rooms visited inside a building - in an energy-efficient and accurate manner. GPS, the dominant positioning technology today, has two major limitations. First, it consumes significant power on mobile phones, making it impractical for continuous monitoring. Second, it does not work indoors. This dissertation develops two ways to address these limitations: (a) subsampling GPS to save energy, and (b) using alternatives to GPS such as WiFi localization, cellular localization, and inertial sensing (with the accelerometer and gyroscope) that consume less energy and work indoors. The key challenge is to match a sequence of infrequent (from sub-sampling) and inaccurate (from WiFi, cellular or inertial sensing) position samples to an accurate output trajectory. This dissertation presents three systems, all using probabilistic models, to accomplish this matching. The first, VTrack, uses Hidden Markov Models to match noisy or sparsely sampled geographic (lat, lon) coordinates to a sequence of road segments on a map. We evaluate VTrack on 800 drive hours of GPS and WiFi localization data collected from 25 taxicabs in Boston. We find that VTrack tolerates significant noise and outages in location estimates, and saves energy, while providing accurate enough trajectories for applications like travel-time aware route planning. CTrack improves on VTrack with a Markov Model that uses "soft" information in the form of raw WiFi or cellular signal strengths, rather than geographic coordinates. It also uses movement and turn "hints" from the accelerometer and compass to improve accuracy. We implement CTrack on Android phones, and evaluate it on cellular signal data from over 126 (1,074 miles) hours of driving data. CTrack can retrieve over 75% of a user's drive accurately on average, even from highly inaccurate (175 metres raw position error) GSM data. iTrack uses a particle filter to combine inertial sensing data from the accelerometer and gyroscope with WiFi signals and accurately track a mobile phone indoors. iTrack has been implemented on the iPhone, and can track a user to within less than a metre when walking with the phone in the hand or pants pocket, over 5 x more accurately than existing WiFi localization approaches. iTrack also requires very little manual effort for training, unlike existing localization systems that require a user to visit hundreds or thousands of locations in a building and mark them on a map.
by Arvind Thiagarajan.
Ph.D.
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Thomas, Nicholas J. "Techniques for mobile location estimation in UMTS." Thesis, University of Edinburgh, 2001. http://hdl.handle.net/1842/426.
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The subject area of this thesis is the locating of mobile users using the future 3rd generation spread spectrum communication system UMTS. The motivation behind this work is twofold: firstly the United States Federal Communications Commission (FCC) mandated the provision of user location into services in the United States of America due to the increasing number of emergency calls originating from unknown locations. Secondly the user location can enable a number of other potentially profit–making applications and services. These are generally thought to be the important new applications of the third generation mobile networks. The UMTS standard has now made provision for a time difference of arrival based mobile user location system in which the mobile measures time differences of arrival of received signals from surrounding base stations (BS’s). There are two main problems to such a technique: firstly the problem of detecting enough base stations to make a location fix, the so called ‘hearability’ problem. In spread spectrum systems all base stations transmit on the same bandwidth thus non–serving BS’s may not be detectable in normal operation. The second problem is non–line of sight (NLOS) propagation, in which time difference measurements (or any other measurement types) may be corrupted significantly, thus causing significant location error. The thesis of this work is that these two problems can be entirely overcome using spatial filtering of measurements and location estimates. Two constraints that are placed on the filtering algorithms are that the operation should be real time and that the precise distribution of NLOS errors is unknown (though certain key characteristics are exploited). A channel model is first developed, which specifically characterises line of sight and NLOS transitions as well as out of cell radio wave propagation. Several scenarios are then simulated. Slow moving users, low hearability and heavily NLOS conditions pose the biggest challenge. Spatial filtering is achieved by Kalman filters adapted to the problem, as well as simple averaging filters. Results show that improved location accuracy (to within FCC recommendations) is possible in all considered scenarios with spatial filtering as well as improved robustness to low hearability. The detection stage of the receiver is also analysed in detail and methods to improve hearability are presented. The performance of a hybrid location system using angle of arrival measurements of the mobile at the serving BS is also assessed. A fairly pessimistic model for the spread of NLOS errors is used, however significant location improvement is noted in several scenarios. Worst performance occurs in urban scenarios so finally a novel approach to user location is described which is robust to NLOS propagation conditions and also overcomes the hearability problem since only measurements at the serving BS are required. The technique, termed Scatterer Back Tracing (SBT), uses and requires multipaths to calculate the mobile location. Results suggest this SBT can provide extremely high location accuracy but is very sensitive to measurement noise.
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Rovinelli, Marco. "Realtime Monocular Depth Estimation on Mobile Phones." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24159/.
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Depth estimation is a necessary task to understand and navigate the environment around us. Over the years, many active sensors have been developed to measure depth but they are expensive and require additional space to be mounted. A cheaper alternative consists of estimating depth maps using images taken by a mobile phone camera. Since most mobile phones don't have cameras built for stereo depth sensing, it would be ideal to be able to recover depth from a single image using only the computational capability of the mobile phone itself. This can be achieved by training a neural network on ground truth depth maps. This type of data is very expensive to obtain so it's preferred to train the neural network using self-supervision from multiple images. Since the devices where the trained models will be deployed have only one camera, it is ideal to train the network on monocular videos representing the actual data distribution at deployment. Self-supervised training using monocular videos lowers the accuracy of the depth maps and brings the additional challenge of being able to predict depth only up to an unknown scale factor. To this end, additional information, velocity provided by the GPS, and sparse points computed by a monocular SLAM algorithm, are employed to recover scale and improve the accuracy. This study will investigate different neural network architectures and training schemes to achieve depth maps as accurately as possible given the constraints of the computational budget available on modern mobile phones.
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Turbillon, Céline. "Estimation et prévision des processus Moyenne Mobile fonctionnels." Paris 6, 2007. http://www.theses.fr/2007PA066379.
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Cette thèse aborde l’étude des processus à temps continu par des variables aléatoires dans un espace fonctionnel, à représentation moyenne mobile. Elle expose des premiers résultats asymptotiques sur la modélisation moyenne mobile. Ce travail se divise en 5 chapitres. Le chapitre 1 rappelle les notions élémentaires sur le processus moyenne mobile en dimension finie. Celles concernant les processus linéaires à valeurs dans un espace hilbertien sont énoncées dans le chapitre 2. Les 3èmes et 4èmes chapitres proposent des résultats de convergence concernant des estimateurs de l’opérateur moyenne mobile d’un processus moyenne mobile hilbertien d’ordre 1. Enfin, le dernier chapitre consiste à proposer une application à partir d’un électrocardiogramme.
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Azemi, Ghasem. "Mobile velocity estimation using a time-frequency approach." Thesis, Queensland University of Technology, 2003. https://eprints.qut.edu.au/15807/1/Ghasem_Azemi_Thesis.pdf.
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This thesis deals with the problem of estimating the velocity of a mobile station (MS)in a mobile communication system using the instantaneous frequency (IF) of the received signal at the MS antenna. This estimate is essential for satisfactory handover performance, effective dynamic channel assignment, and optimisation of adaptive multiple access wireless receivers. Conventional methods for estimating the MS velocity are based either on the statistics of the envelope or quadrature components of the received signal. In chapter 4 of the thesis, we show that their performance deteriorates in the presence of shadowing. Other velocity estimators have also been proposed which require prior estimation of the channel or the average received power. These are generally difficult to obtain due to the non-stationary nature of the received signal. An appropriate window which depends on the unknown MS velocity must first be applied in order to accurately estimate the required quantities. Using the statistics of the IF of the received signal at the MS antenna given in chapter 3, new velocity estimators are proposed in chapter 4 of this thesis. The proposed estimators are based on the moments, zero-crossing rate, and covariance of the received IF. Since the IF of the received signal is not affected by any amplitude distortion, the proposed IF-based estimators are robust to shadowing and propagation path-loss. The estimators for the MS velocity in a macro- and micro-cellular system are presented separately. A macro-cell system can be considered as a special case of a micro-cell in which there is no line-of-sight component at the receiver antenna. It follows that those estimators which are derived for micro-cells can be used in a macro-cell as well. In chapter 4, we analyse the performance of the proposed velocity estimators in the presence of additive noise, non-isotropic scattering, and shadowing. We also prove analytically that the proposed velocity estimators outperform the existing methods in the presence of shadowing and additive noise. The proposed IF-based estimators need prior estimation of both the IF of the received signal and Ricean K-factor. The IF estimation in a typical wireless environment, can be considered as a special case of a general problem of IF estimation in the presence of multiplicative and additive noise. In chapter 5, we show that current time-frequency approaches to this problem which are based on the peak of a time-frequency distribution (TFD) of the signal, fail because of the special shape of the power spectral density of the multiplicative noise in a wireless environment. To overcome this drawback, the use of the first-order moment of a TFD is studied in chapter 5. Theoretical analysis and simulations show that the IF estimator based on the first-order moment of a TFD exhibits negligible bias when the signal-to-additive noise ratio is more than 10 dB. The Ricean K-factor is not only necessary for velocity estimation in micro-cells, but also is a measure of the severity of fading and a good indicator of the channel quality. Two new methods for estimating the Ricean K-factor based on the first two moments of the envelope of the received signal, are proposed in chapter 6. Performance analysis presented in chapter 6, prove that the proposed K estimators are robust to non-isotropic scattering. Theoretical analysis and simulations which are presented in chapters 4 and 7 of this thesis, prove that the proposed velocity and K estimators outperform existing estimators in the presence of shadowing and additive noise.
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Azemi, Ghasem. "Mobile Velocity Estimation Using a Time-Frequency Approach." Queensland University of Technology, 2003. http://eprints.qut.edu.au/15807/.
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This thesis deals with the problem of estimating the velocity of a mobile station (MS)in a mobile communication system using the instantaneous frequency (IF) of the received signal at the MS antenna. This estimate is essential for satisfactory handover performance, effective dynamic channel assignment, and optimisation of adaptive multiple access wireless receivers. Conventional methods for estimating the MS velocity are based either on the statistics of the envelope or quadrature components of the received signal. In chapter 4 of the thesis, we show that their performance deteriorates in the presence of shadowing. Other velocity estimators have also been proposed which require prior estimation of the channel or the average received power. These are generally difficult to obtain due to the non-stationary nature of the received signal. An appropriate window which depends on the unknown MS velocity must first be applied in order to accurately estimate the required quantities. Using the statistics of the IF of the received signal at the MS antenna given in chapter 3, new velocity estimators are proposed in chapter 4 of this thesis. The proposed estimators are based on the moments, zero-crossing rate, and covariance of the received IF. Since the IF of the received signal is not affected by any amplitude distortion, the proposed IF-based estimators are robust to shadowing and propagation path-loss. The estimators for the MS velocity in a macro- and micro-cellular system are presented separately. A macro-cell system can be considered as a special case of a micro-cell in which there is no line-of-sight component at the receiver antenna. It follows that those estimators which are derived for micro-cells can be used in a macro-cell as well. In chapter 4, we analyse the performance of the proposed velocity estimators in the presence of additive noise, non-isotropic scattering, and shadowing. We also prove analytically that the proposed velocity estimators outperform the existing methods in the presence of shadowing and additive noise. The proposed IF-based estimators need prior estimation of both the IF of the received signal and Ricean K-factor. The IF estimation in a typical wireless environment, can be considered as a special case of a general problem of IF estimation in the presence of multiplicative and additive noise. In chapter 5, we show that current time-frequency approaches to this problem which are based on the peak of a time-frequency distribution (TFD) of the signal, fail because of the special shape of the power spectral density of the multiplicative noise in a wireless environment. To overcome this drawback, the use of the first-order moment of a TFD is studied in chapter 5. Theoretical analysis and simulations show that the IF estimator based on the first-order moment of a TFD exhibits negligible bias when the signal-to-additive noise ratio is more than 10 dB. The Ricean K-factor is not only necessary for velocity estimation in micro-cells, but also is a measure of the severity of fading and a good indicator of the channel quality. Two new methods for estimating the Ricean K-factor based on the first two moments of the envelope of the received signal, are proposed in chapter 6. Performance analysis presented in chapter 6, prove that the proposed K estimators are robust to non-isotropic scattering. Theoretical analysis and simulations which are presented in chapters 4 and 7 of this thesis, prove that the proposed velocity and K estimators outperform existing estimators in the presence of shadowing and additive noise.
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Chan, Ka Chun. "A dual channel location estimation system for mobile computing." HKBU Institutional Repository, 2003. http://repository.hkbu.edu.hk/etd_ra/445.
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Ward, Christopher Charles. "Terrain sensing and estimation for dynamic outdoor mobile robots." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/42419.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.Includes bibliographical references (p. 120-125).
In many applications, mobile robots are required to travel on outdoor terrain at high speed. Compared to traditional low-speed, laboratory-based robots, outdoor scenarios pose increased perception and mobility challenges which must be considered to achieve high performance. Additionally, high-speed driving produces dynamic robot-terrain interactions which are normally negligible in low speed driving. This thesis presents algorithms for estimating wheel slip and detecting robot immobilization on outdoor terrain, and for estimating traversed terrain profile and classifying terrain type. Both sets of algorithms utilize common onboard sensors. Two methods are presented for robot immobilization detection. The first method utilizes a dynamic vehicle model to estimate robot velocity and explicitly estimate longitudinal wheel slip. The vehicle model utilizes a novel simplified tire traction/braking force model in addition to estimating external resistive disturbance forces acting on the robot. The dynamic model is combined with sensor measurements in an extended Kalman filter framework. A preliminary algorithm for adapting the tire model parameters is presented. The second, model-free method takes a signal recognition-based approach to analyze inertial measurements to detect robot immobilization. Both approaches are experimentally validated on a robotic platform traveling on a variety of outdoor terrains. Two detector fusion techniques are proposed and experimentally validated which combine multiple detectors to increase detection speed and accuracy. An algorithm is presented to classify outdoor terrain for high-speed mobile robots using a suspension mounted accelerometer. The algorithm utilizes a dynamic vehicle model to estimate the terrain profile and classifies the terrain based on spatial frequency components of the estimated profile. The classification algorithm is validated using experimental results collected with a commercial automobile driving in real-world conditions.
by Christopher Charles Ward.
S.M.
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Kang, Shinwoo 1976. "Terrain parameter estimation and traversability assessment for mobile robots." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/42830.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2003.Includes bibliographical references (leaves 65-68).
The estimation of terrain characteristics is an important missions of Martian exploration rovers. Since only limited resources and human supervision are available, efficient and autonomous method of estimation are required. In this thesis, an on-line estimation method of two important terrain parameters, cohesion and internal friction angle, is developed. The method uses onboard rover sensors and is computationally efficient. Terrain parameter estimation is of scientific interest, and can also be useful in predicting rover mobility on rough-terrain. A method to estimate traversability of a rover on deformable terrain using on-board sensors is presented. Simulation and experimental results show that the proposed methods can accurately and efficiently estimate traversability of deformable terrain.
by Shinwoo Kang.
S.M.
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Nordlander, Rickard. "Pose Estimation in an Outdoors Augmented Reality Mobile Application." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-70653.
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This thesis proposes a solution to the pose estimation problem for mobile devices in an outdoors environment. The proposed solution is intended for usage within an augmented reality application to visualize large objects such as buildings. As such, the system needs to provide both accurate and stable pose estimations with real-time requirements. The proposed solution combines inertial navigation for orientation estimation with a vision-based support component to reduce noise from the inertial orientation estimation. A GNSS-based component provides the system with an absolute reference of position. The orientation and position estimation were tested in two separate experiments. The orientation estimate was tested with the camera in a static position and orientation and was able to attain an estimate that is accurate and stable down to a few fractions of a degree. The position estimation was able to achieve centimeter-level stability during optimal conditions. Once the position had converged to a location, it was stable down to a couple of centimeters, which is sufficient for outdoors augmented reality applications.
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Molitor, Torsten, and Hilding Wollbo. "Estimation of Statistical Properties in a Mobile MIMO System." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-239375.
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Several measures to evaluate the stationarity of a MIMO radio channel are proposed and implemented. The analysis is performed on a Kronecker model implementation of the channel matrix covariance, which describes the statistical characteristics and transmission properties of the radio channel. The analysis involves calculating the Path Gain, Eigen Quotient and Correlation Matrix Distance. A novel measure, Time of Stationarity, is introduced based on the CMD and is seen to correlate with changes in the Eigen Quotient.
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Patel, Chirag S. "Wireless channel modeling, simulation, and estimation." Diss., Available online, Georgia Institute of Technology, 2006, 2006. http://etd.gatech.edu/theses/available/etd-03282006-200818/.
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Thesis (Ph. D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2006.Andrew, Alfred, Committee Member ; Durgin, Gregory, Committee Member ; Li, Geoffrey, Committee Member ; Ingram, Mary Ann, Committee Member ; Stuber, Gordon, Committee Chair.
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Saur, Stephan. "Channel estimation for mobile wideband code division multiple access (WCDMA)." Aachen Shaker, 2008. http://d-nb.info/989680819/04.
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Johansson, Oscar. "Weight Estimation and Evaluation of User Suggestions in Mobile Browsing." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-154647.
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This study investigates the suggestion system of a mobile browser. The goal of a suggestion system is to assist the user by presenting relevant suggestions in an ordered list. By weighting the different types of suggestions presented to the user, such as history, bookmarks etc., it is investigated how this affects the performance of the suggestion sys- tem. The performance is measured using the position, error and Mean Reciprocal Rank of the chosen suggestion as well as the number of written characters. It is also measured if the user chose to not use the suggestion system, by searching or entering the entire URL. The weights were estimated using a Genetic Algorithm. The evaluation was done by performing an A/B test, were the control group used an unweighted system and the test group used the weights estimated by the genetic algorithm. The results from the A/B test were statistically analyzed using BEST and Bootstrap. The results showed an improvement of position, number of written characters, MMR and the error. There was no change in how much the user used the suggestion system. The thesis concluded that there is a correlation between the position of the desired suggestion and when the user stops typing, and that weighting types is a way to improve said position. The thesis also concludes that there is a need for future work in regards to evaluation of the optimization algorithm and error measurement.
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Kumar, Sumeet Ph D. Massachusetts Institute of Technology. "Mobile sensor systems for field estimation and "hot spot" identification." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/87977.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 155-166).
Robust, low-cost mobile sensing enables effective monitoring and management of urban environment and infrastructure which contributes towards a sustainable future. While mobile sensor systems have attracted significant attention in recent years, a large scale deployment for urban infrastructure monitoring poses many research challenges. One fundamental challenge is dealing with noisy and uncontrolled samples stemming from both noisy sensor measurements and locations, and lack of control on sensor deployment. Such conditions pose difficulties in field estimation and "hot spot" identification from sensor data. My thesis contributions aim to bridge this gap. In this thesis, I designed and developed a mobile sensor system for urban light infrastructure monitoring and studied two problems on field estimation in the presence of noisy and uncontrolled samples with general implications on mobile sensing. As an example system, I designed and successfully tested a city-wide street light scanning mobile sensor platform. Currently, street light maintenance uses labor-intensive, poorly scalable manual inspection techniques. My system automatically maps street illumination levels and lamp infrastructure. The collected data presents challenges in identifying lamp "hot spots" from false positives and using sensor data from noisy sensor locations for estimating luminosity maps. I present an algorithm for identifying various light sources from video streams and combining that data with location information to geotag lamps. To identity the light sources, I developed a supervised classifier for lamp classification and later extended it to develop a method for estimating the height of the street lamps. As accurate car location information is critical for successful luminosity mapping, I discuss how I improved car location estimates by integrating multiple independent data streams such as vehicle speed data obtained via on-board diagnostic systems and GPS. Towards such field deployments, one must address fundamental challenges related to both hardware implementation and data analytics. In this thesis, I addressed two problems related to mobile sensor based sampling and signal estimation: nonuniform sampling and errors in sample location. Uniform grid sampling is often impractical in the context of mobile spatial sampling. As an alternative, I studied [delta]-dense sensor arrangements as a realistic scheme for non-uniform flexible sampling. To assess its utility, I derived sufficient conditions for estimating a signal represented in a finite-dimensional basis set and present simulation results on the numerical stability of signal estimation under [delta]-dense sampling. Furthermore, I present the use of proper orthogonal decomposition as a technique to obtain basis sets for signals that are solutions to a parametric differential equation. Finally, I studied how errors in the location measurements of mobile nodes affect the overall signal estimation problem. To address such signal estimation problems, I developed a computationally efficient iterative linear estimator and compared my approach to the state of the art expectation-maximization technique. I present simulation studies on the performance of the estimator and discuss results on its numerical stability. My approach offers several orders of magnitude reduction in computational time while achieving comparable mean squared estimation error to other techniques making it an appealing candidate for real-time embedded mobile sensing applications.
by Sumeet Kumar.
Ph. D.
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Hughes, Lloyd Haydn. "Enhancing mobile camera pose estimation through the inclusion of sensors." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/95917.
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Thesis (MSc)--Stellenbosch University, 2014.ENGLISH ABSTRACT: Monocular structure from motion (SfM) is a widely researched problem, however many of the existing approaches prove to be too computationally expensive for use on mobile devices. In this thesis we investigate how inertial sensors can be used to increase the performance of SfM algorithms on mobile devices. Making use of the low cost inertial sensors found on most mobile devices we design and implement an extended Kalman filter (EKF) to exploit their complementary nature, in order to produce an accurate estimate of the attitude of the device. We make use of a quaternion based system model in order to linearise the measurement stage of the EKF, thus reducing its computational complexity. We use this attitude estimate to enhance the feature tracking and camera localisation stages in our SfM pipeline. In order to perform feature tracking we implement a hybrid tracking algorithm which makes use of Harris corners and an approximate nearest neighbour search to reduce the search space for possible correspondences. We increase the robustness of this approach by using inertial information to compensate for inter-frame camera rotation. We further develop an efficient bundle adjustment algorithm which only optimises the pose of the previous three key frames and the 3D map points common between at least two of these frames. We implement an optimisation based localisation algorithm which makes use of our EKF attitude estimate and the tracked features, in order to estimate the pose of the device relative to the 3D map points. This optimisation is performed in two steps, the first of which optimises only the translation and the second optimises the full pose. We integrate the aforementioned three sub-systems into an inertial assisted pose estimation pipeline. We evaluate our algorithms with the use of datasets captured on the iPhone 5 in the presence of a Vicon motion capture system for ground truth data. We find that our EKF can estimate the device’s attitude with an average dynamic accuracy of ±5°. Furthermore, we find that the inclusion of sensors into the visual pose estimation pipeline can lead to improvements in terms of robustness and computational efficiency of the algorithms and are unlikely to negatively affect the accuracy of such a system. Even though we managed to reduce execution time dramatically, compared to typical existing techniques, our full system is found to still be too computationally expensive for real-time performance and currently runs at 3 frames per second, however the ever improving computational power of mobile devices and our described future work will lead to improved performance. From this study we conclude that inertial sensors make a valuable addition into a visual pose estimation pipeline implemented on a mobile device.
AFRIKAANSE OPSOMMING: Enkel-kamera struktuur-vanaf-beweging (structure from motion, SfM) is ’n bekende navorsingsprobleem, maar baie van die bestaande benaderings is te berekeningsintensief vir gebruik op mobiele toestelle. In hierdie tesis ondersoek ons hoe traagheidsensors gebruik kan word om die prestasie van SfM algoritmes op mobiele toestelle te verbeter. Om van die lae-koste traagheidsensors wat op meeste mobiele toestelle gevind word gebruik te maak, ontwerp en implementeer ons ’n uitgebreide Kalman filter (extended Kalman filter, EKF) om hul komplementêre geaardhede te ontgin, en sodoende ’n akkurate skatting van die toestel se postuur te verkry. Ons maak van ’n kwaternioon-gebaseerde stelselmodel gebruik om die meetstadium van die EKF te lineariseer, en so die berekeningskompleksiteit te verminder. Hierdie afskatting van die toestel se postuur word gebruik om die fases van kenmerkvolging en kameralokalisering in ons SfM proses te verbeter. Vir kenmerkvolging implementeer ons ’n hibriede volgingsalgoritme wat gebruik maak van Harris-hoekpunte en ’n benaderde naaste-buurpunt-soektog om die soekruimte vir moontlike ooreenstemmings te verklein. Ons verhoog die robuustheid van hierdie benadering, deur traagheidsinligting te gebruik om vir kamerarotasies tussen raampies te kompenseer. Verder ontwikkel ons ’n doeltreffende bondelaanpassingsalgoritme wat slegs optimeer oor die vorige drie sleutelraampies, en die 3D punte gemeenskaplik tussen minstens twee van hierdie raampies. Ons implementeer ’n optimeringsgebaseerde lokaliseringsalgoritme, wat gebruik maak van ons EKF se postuurafskatting en die gevolgde kenmerke, om die posisie en oriëntasie van die toestel relatief tot die 3D punte in die kaart af te skat. Die optimering word in twee stappe uitgevoer: eerstens net oor die kamera se translasie, en tweedens oor beide die translasie en rotasie. Ons integreer die bogenoemde drie sub-stelsels in ’n pyplyn vir postuurafskatting met behulp van traagheidsensors. Ons evalueer ons algoritmes met die gebruik van datastelle wat met ’n iPhone 5 opgeneem is, terwyl dit in die teenwoordigheid van ’n Vicon bewegingsvasleggingstelsel was (vir die gelyktydige opneming van korrekte postuurdata). Ons vind dat die EKF die toestel se postuur kan afskat met ’n gemiddelde dinamiese akkuraatheid van ±5°. Verder vind ons dat die insluiting van sensors in die visuele postuurafskattingspyplyn kan lei tot verbeterings in terme van die robuustheid en berekeningsdoeltreffendheid van die algoritmes, en dat dit waarskynlik nie die akkuraatheid van so ’n stelsel negatief beïnvloed nie. Al het ons die uitvoertyd drasties verminder (in vergelyking met tipiese bestaande tegnieke) is ons volledige stelsel steeds te berekeningsintensief vir intydse verwerking op ’n mobiele toestel en hardloop tans teen 3 raampies per sekonde. Die voortdurende verbetering van mobiele toestelle se berekeningskrag en die toekomstige werk wat ons beskryf sal egter lei tot ’n verbetering in prestasie. Uit hierdie studie kan ons aflei dat traagheidsensors ’n waardevolle toevoeging tot ’n visuele postuurafskattingspyplyn kan maak.
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Lu, Bowen. "Bayesian estimation of environmental fields using mobile wireless sensor networks." Thesis, University of Essex, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.635987.
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Environmental fields widely exist around us in our daily life and some of them are so important that cannot be ignored. For instance, temperature distribution, environment contamination and nuclear leaking can all be categorised as envirornmental fields. Some of the fields are invisible, some are dynamic changing and some are harmful to human. Therefore, deploying a mobile wireless sensor network (WSN) will be a better solution than manually sampling and estimating an environmental field. Bayesian framework is an elegant mathematical model that interprets the recognition procedures of human being and is widely used for iterative learning processes. Based on two regression methods in this platform, a complete field estimation solution for mobile WSNs is proposed. First, two distributed platforms are provided based on support vector regression (SVR), and centroidal Voronoi tessellation (CVT) is employed to optimise the sensor deployment. Second, to overcome the defects existed in the solution of SVR-CVT, Gaussian process regression (GPR) is being investigated due to its additional estimation accuracy information. To further improve the performance of this GPR based solution. A data selection strategy for GPR and a hybrid criterion for CVT are investigated.
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Sebastian, Bijo. "Traversability Estimation Techniques for Improved Navigation of Tracked Mobile Robots." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/94629.
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The focus of this dissertation is to improve autonomous navigation in unstructured terrain conditions, with specific application to unmanned casualty extraction in disaster scenarios. Robotic systems are being widely employed for search and rescue applications, especially in disaster scenarios. But a majority of these are focused solely on the search aspect of the problem. This dissertation proposes a conceptual design of a Semi-Autonomous Victim Extraction Robot (SAVER) capable of safe and effective unmanned casualty extraction, thereby reducing the risk to the lives of first responders. In addition, the proposed design addresses the limitations of existing state-of-the-art rescue robots specifically in the aspect of head and neck stabilization as well as fast and safe evacuation.
One of the primary capabilities needed for effective casualty extraction is reliable navigation in unstructured terrain conditions. Autonomous navigation in unstructured terrain, particularly for systems with tracked locomotion mode involves unique challenges in path planning and trajectory tracking. The dynamics of robot-terrain interaction, along with additional factors such as slip experienced by the vehicle, slope of the terrain, and actuator limitations of the robotic system, need to be taken into consideration. To realize these capabilities, this dissertation proposes a hybrid navigation architecture that employs a physics engine to perform fast and accurate state expansion inside a graph-based planner.
Tracked skid-steer systems experience significant slip, especially while turning. This greatly affects the trajectory tracking accuracy of the robot. In order to enable efficient trajectory tracking in varying terrain conditions, this dissertation proposes the use of an active disturbance rejection controller. The proposed controller is capable of estimating and counter acting the effects of slip in real-time to improve trajectory tracking. As an extension of the above application, this dissertation also proposes the use of support vector machine architecture to perform terrain identification, solely based on the estimated slip parameters.
Combining all of the above techniques, an overall architecture is proposed to assist and inform tele-operation of tracked robotic systems in unstructured terrain conditions. All of the above proposed techniques have been validated through simulations and experiments in indoor and simple outdoor terrain conditions.Doctor of Philosophy
This dissertation explores ways to improve autonomous navigation in unstructured terrain conditions, with specific applications to unmanned casualty extraction in disaster scenarios. Search and rescue applications often put the lives of first responders at risk. Using robotic systems for human rescue in disaster scenarios can keep first responders out of danger. To enable safe robotic casualty extraction, this dissertation proposes a novel rescue robot design concept named SAVER. The proposed design concept consists of several subsystems including a declining stretcher bed, head and neck support system, and robotic arms that conceptually enable safe casualty manipulation and extraction based on high-level commands issued by a remote operator. In order to enable autonomous navigation of the proposed conceptual system in challenging outdoor terrain conditions, this dissertation proposes improvements in planning, trajectory tracking control and terrain estimation. The proposed techniques are able to take into account the dynamic effects of robot-terrain interaction including slip experienced by the vehicle, slope of the terrain and actuator limitations. The proposed techniques have been validated through simulations and experiments in indoor and simple outdoor terrain conditions. The applicability of the above techniques in improving tele-operation of rescue robotic systems in unstructured terrain is also discussed at the end of this dissertation.
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Wong, Hak Lim. "Signal strength-based location estimation in two different mobile networks." HKBU Institutional Repository, 2006. http://repository.hkbu.edu.hk/etd_ra/700.
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Kan, Ka Ho. "Location estimation system based on the GSM network." HKBU Institutional Repository, 2004. http://repository.hkbu.edu.hk/etd_ra/524.
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Chaplin, Bruce Alan. "Motion estimation from stereo image sequences for a mobile mapping system." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0020/MQ48058.pdf.
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Afgani, Mostafa Z. "Exploitation of signal information for mobile speed estimation and anomaly detection." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/4890.
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Although the primary purpose of the signal received by amobile handset or smartphone is to enable wireless communication, the information extracted can be reused to provide a number of additional services. Two such services discussed in this thesis are: mobile speed estimation and signal anomaly detection. The proposed algorithms exploit the propagation environment specific information that is already imprinted on the received signal and therefore do not incur any additional signalling overhead. Speed estimation is useful for providing navigation and location based services in areas where global navigation satellite systems (GNSS) based devices are unusable while the proposed anomaly detection algorithms can be used to locate signal faults and aid spectrum sensing in cognitive radio systems. The speed estimation algorithms described within this thesis require a receiver with at least two antenna elements and a wideband radio frequency (RF) signal source. The channel transfer function observed at the antenna elements are compared to yield an estimate of the device speed. The basic algorithm is a one-dimensional and unidirectional two-antenna solution. The speed of the mobile receiver is estimated from a knowledge of the fixed inter-antenna distance and the time it takes for the trailing antenna to sense similar channel conditions previously observed at the leading antenna. A by-product of the algorithm is an environment specific spatial correlation function which may be combined with theoretical models of spatial correlation to extend and improve the accuracy of the algorithm. Results obtained via computer simulations are provided. The anomaly detection algorithms proposed in this thesis highlight unusual signal features while ignoring events that are nominal. When the test signal possesses a periodic frame structure, Kullback-Leibler divergence (KLD) analysis is employed to statistically compare successive signal frames. A method of automatically extracting the required frame period information from the signal is also provided. When the signal under test lacks a periodic frame structure, information content analysis of signal events can be used instead. Clean training data is required by this algorithm to initialise the reference event probabilities. In addition to the results obtained from extensive computer simulations, an architecture for field-programmable gate array (FPGA) based hardware implementations of the KLD based algorithm is provided. Results showing the performance of the algorithms against real test signals captured over the air are also presented. Both sets of algorithms are simple, effective and have low computational complexity – implying that real-time implementations on platforms with limited processing power and energy are feasible. This is an important quality since location based services are expected to be an integral part of next generation cognitive radio handsets.
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Ahmadzadeh, Amir Masoud. "Capacity and Cell-Range Estimation for Multitraffic Users in Mobile WiMAX." Thesis, Högskolan i Borås, Institutionen Ingenjörshögskolan, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-19122.
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The fundamentals for continued growth of broadband wireless remain sound. According to the Ericsson’s official forecasts, the addressable global market of wireless internet broadband connectivity reaches to 320 million users by the end of 2010. The opportunity for BWA/WiMAX to serve those who want to switch to broadband service is huge in many parts of the world where wireline technologies may not be feasible.The current document (Capacity and Cell-range Estimation for Multitraffic Users in Mobile WiMAX) is prepared as a master’s program final thesis to peruse the service provision capabilities of Mobile WiMAX innovate technology in more details. An elaborate excerpt of the technical subjects of IEEE-802.16e-2005 standard is gathered in the first chapter to provide the reader with a practical concept of Mobile WiMAX technology. The following chapter is aimed to collect the required knowledge for WiMAX planning problem. An innovate methodology to calculate the system’s actual throughput and a traffic model for mixed application users are proposed with a step by step description to derive an algorithm to determine the maximum number of subscribers that each specific Mobile WiMAX sector may support. The report also contains a Matlab code –enclose in the appendix– that tries to implement the entire algorithm for different system parameter and traffic cases to ease the Mobile WiMAX planning problem. The last chapter introduces the mostly used propagation models that suit the WiMAX applications.The presented methodology would help those operators that plan to implement a wide coverage network in a city. Using the introduced methodology, service providers will be able to estimate the number of base stations and hence the network investment and profitability.Uppsatsnivå: D
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Li, Wei. "Intelligent joint channel parameter estimation techniques for mobile wireless positioning applications." Thesis, Brunel University, 2010. http://bura.brunel.ac.uk/handle/2438/7764.
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Mobile wireless positioning has recently received great attention. For mobile wireless communication networks, an inherently suitable approach is to obtain the parameters that are used for positioning estimates from the radio signal measurements between a mobile device and one or more xed base stations. However, obtaining accurate estimates of these location-dependent channel parameters is a challenging task. The focus of this thesis is on the estimation of these channel parameters for mobile wireless positioning applications. In particular, we investigate novel estimators that jointly estimate more than one type of channel parameters. We rst perform a comprehensive critical review on the most recent and popular joint channel parameter estimation techniques. Secondly, we improve a state-of-the-art technique, namely the Space Alternating Generalised Expectation maximisation (SAGE) algorithm by employing adaptive interference cancellation to improve the estimation accuracy of weaker paths. Thirdly, a novel intelligent channel parameter estimation technique using Evolution Strategy (ES) is proposed to overcome the drawbacks of the existing iterative maximum likelihood methods. Furthermore, given that in reality it is di cult to obtain the number of multipath in advance, we propose a two tier Hierarchically Organised ES to jointly estimate the number of multipath as well as the channel parameters. Finally, we extend the proposed ES method to further estimate the Doppler shift in mobile environments. Our proposed intelligent joint channel estimation techniques are shown to exhibit excellent performance even with low Signal to Noise Ratio (SNR) channel conditions as well as robust against uncertainties in initialisations.
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Krumbein, Marc. "Heading Estimation of a Mobile Robot Using Multiple UWB Position Sensors." Case Western Reserve University School of Graduate Studies / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1555001007552678.
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Håkansson, Dennis, and Johan Lövberg. "Development of algorithm for a mobile-based estimation of heart rate." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43561.
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To perform a physical performance test is a good way to keep track of one’s health and can be beneficial to find evidence of deviations in the body. This thesis focuses on the development of a mobile-based heart rate algorithm that can be used with the Queens College Step Test, on the behalf of Mobistudy. Mobistudy wants to include such a test in their mobile application which aims to become a tool for researchers to use to gather data. The algorithm uses the mobile device’s camera to collect data from the user’s finger and uses that data to calculate the heart rate. The algorithm was first tested with data collected during the development and the results has an average error of less than 5% and a standard deviation of less than 3%. Two participants between the age of 20-25 performed three sets each of the Queens College Step Test and the results showed that the algorithm was accurate in its estimation of the heart rate after the test.Genom att utföra ett test av ens fysiska prestanda kan man utvärdera ens hälsostatus och upptäcka indikationer på avvikelser i kroppen. Syftet med detta arbete är att utveckla en mobilbaserad algoritm som kan beräkna och uppskatta ens puls när man utför the Queens College Step Test på begäran av Mobistudy. Mobistudy vill inkludera detta test i deras mobilapplikation som fokuserar på att kunna användas som ett verktyg inom forskning för att samla in data. Algoritmen använder sig av mobilens kamera för att samla in data från användarens finger och använder den insamlade data för att beräkna pulsen. Algoritmen testades först gentemot data som samlades in vid utvecklingsstadiet och resultatet visade på att genomsnittliga felet var under 5% samt att standardavvikelsen var under 3%. Två deltagare mellan åldern 20 och 25 utförde tre tester var utav the Queens College Step Test och resultatet visade att algoritmen var tillräckligt noggrann i sin uppskattning av pulsen efter ett utfört test.
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Hsu, Pei-Lun. "Machine Learning-Based Data-Driven Traffic Flow Estimation from Mobile Data." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-300712.
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Comprehensive information on traffic flow is essential for vehicular emission monitoring and traffic control. However, such information is not observable everywhere and anytime on the road because of high installation costs and malfunctions of stationary sensors. In order to compensate for stationary sensors’ weakness, this thesis analyses an approach for inferring traffic flows from mobile data provided by INRIX, a commercial crowd-sourced traffic dataset with wide spatial coverage and high quality. The idea is to develop Artificial Neural Network (ANN)-based models to automatically extract relations between traffic flow and INRIX measurements, e.g., speed and travel time, from historical data considering temporal and spatial dependencies. We conducted experiments using four weeks of data from INRIX and stationary sensors on two adjacent road segments on the E4 highway in Stockholm. Models are validated via traffic flow estimation based on one week of INRIX data. Compared with the traditional approach that fits the stationary flow-speed relationship based on the multi-regime model, the new approach greatly improves the estimation accuracy. Moreover, the results indicate that the new approach’s models have better resistance to the drift of input variables and can decrease the deterioration of estimation accuracy on the road segment without a stationary sensor. Hence, the new approach may be more appropriate for estimating traffic flows on the nearby road segments of a stationary sensor. The approach provides a highly automated means to build models adaptive to datasets and improves estimation and imputation accuracy. It can also easily integrate new data sources to improve the models. Therefore, it is very suitable to be applied to Intelligent Transport Systems (ITS) for traffic monitor and control in the context of the Internet of Things (IoT) and Big Data.Information om trafikflödet är nödvändig för övervakning av fordonsutsläpp och trafikstyrning. Trafikflöden kan dock inte observeras överallt och när som helst på vägen på grund av höga installationskostnader och t.ex. funktionsstörningar hos stationära sensorer. För att kompensera för stationära sensorers svagheter analyseras i detta arbete ett tillvägagångssätt för att estimera trafikflöden från mobila data som tillhandahålls av INRIX. Detta kommersiella dataset innehåller restider som kommer från användare av bl.a. färdnavigatorer i fordon och som har en bred rumslig täckning och hög kvalitet. Idén är att utveckla modeller baserade på artificiellt neuronnät för att automatiskt extrahera samband mellan trafikflödesdata och restidsdata från INRIX-mätningarna baserat på historiska data och med hänsyn till tidsmässiga och rumsliga beroenden. Vi utförde experiment med fyra veckors data från INRIX och från stationära sensorer på två intilliggande vägsegment på E4:an i Stockholm. Modellerna valideras med hjälp av estimering av trafikflöde baserat på en veckas INRIX- data. Jämfört med det traditionella tillvägagångssättet som anpassar stationära samband mellan trafikflöde och hastighet baserat på fundamentaldiagram, förbättrar det nya tillvägagångssättet noggrannheten avsevärt. Dessutom visar resultaten att modellerna i den nya metoden bättre hanterar avvikelser i ingående variabler och kan öka noggrannheten på estimatet för vägsegmentet utan stationär sensor. Den nya metoden kan därför vara lämplig för att uppskatta trafikflöden på vägsegment närliggande en stationär sensor. Metodiken ger ett automatiserat sätt att bygga modeller som är anpassade till datamängderna och som förbättrar noggrannheten vid estimering av trafikflöden. Den kan också enkelt integrera nya datakällor. Metodiken är lämplig att tillämpa på tillämpningar inom intelligenta transportsystem för trafikövervakning och trafikstyrning.
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Chu, Man Kin. "A hybrid approach for mobile location estimation in cellular radio networks." HKBU Institutional Repository, 2006. http://repository.hkbu.edu.hk/etd_ra/672.
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Jayasinghe, Sankissa G. "Techniques of detection, estimation and coding for fading channels." Thesis, Loughborough University, 1989. https://dspace.lboro.ac.uk/2134/7282.
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The thesis describes techniques of detection, coding and estimation, for use in high speed serial modems operating over fading channels such as HF radio and land mobile radio links. The performance of the various systems that employ the above techniques are obtained via computer simulation tests. A review of the characteristics of HF radio channels is first presented, leading to the development of an appropriate channel model which imposes Rayleigh fading on the transmitted signal. Detection processes for a 4.8 kbit/s HF radio modem are then discussed, the emphasis, here, being on variants of the maximum likelihood detector that is implemented by the Viterbi algorithm. The performance of these detectors are compared with that of a nonlinear equalizer operating under the same conditions, and the detector which offers the best compromise between performance and complexity is chosen for further tests. Forward error correction, in the form of trellis coded modulation, is next introduced. An appropriate 8-PSK coded modulation scheme is discussed, and its operation over the above mentioned HF radio modem is evaluated. Performance comparisons are made of the coded and uncoded systems. Channel estimation techniques for fast fading channels akin to cellular land mobile radio links, are next discussed. A suitable model for a fast fading channel is developed, and some novel estimators are tested over this channel. Computer simulation tests are also used to study the feasibility of the simultaneous transmission of two 4-level QAM signals occupying the same frequency band, when each of these signals are transmitted at 24 kbit/s over two independently fading channels, to a single receiver. A novel combined detector/estimator is developed for this purpose. Finally, the performance of the complete 4.8 kbit/s HF radio modem is obtained, when all the functions of detection, estimation and prefiltering are present, where the prefilter and associated processor use a recently developed technique for the adjustment of its tap gains and for the estimation of the minimum phase sampled impulse response.
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Filliat, David. "Cartographie et estimation globale de la position pour un robot mobile autonome." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2001. http://tel.archives-ouvertes.fr/tel-00655469.
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La gestion des déplacements dans l'espace pour un robot mobile autonome est un problème qui a été abordé dès les premiers essais d'intégration de l'intelligence artificielle et de la robotique, mais qui reste difficile et auquel peu de solutions générales ont été apportées. Parmi toutes les stratégies de navigation existantes, nous nous intéressons à celles qui utilisent une carte représentant la structure spatiale de l'environnement et qui permettent de planifi er les déplacements jusqu'à un but lointain. La construction d'une carte et l'estimation de la position du robot sont deux sous-problèmes de navigation qui ont reçu isolément des solutions e fficaces. Toutefois, leur résolution simultanée reste une tâche complexe. Le problème de l'estimation de la position, pris isolément, peut notamment être résolu de manière très e fficace par des modèles probabilistes utilisant des Processus de Décision Markoviens Partiellement Observables. Toutefois, ces modèles ne peuvent en général pas être utilisés pour construire "en-ligne" la carte qu'ils utilisent. Nous avons élaboré un modèle de navigation qui s'inspire de ces méthodes mais qui, à partir de capteurs relativement imprécis, permet la construction "en-ligne" de la carte. La capacité d'intégration des informations qu'o ffre cette méthode de localisation permet de compenser la faiblesse des perceptions. Nous utilisons de plus des procédures de perception active qui permettent, en fonction du contexte, d'utiliser les capteurs de manière e fficace. Notre modèle permet ainsi, en faisant peu d'hypothèses sur l'environnement, une estimation robuste de la position et une construction simultanée de la carte. Ses capacités ont été démontrées à la fois en simulation et sur un robot réel. En particulier, nous avons montré qu'il permettait au robot de se localiser correctement dès son introduction dans un environnement nouveau, de se relocaliser rapidement lorsqu'il est transporté passivement d'un endroit à un autre et de plani fier une trajectoire permettant de rejoindre de manière robuste un but donné.
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Sun, Xusheng. "Optimal distributed detection and estimation in static and mobile wireless sensor networks." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44825.
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This dissertation develops optimal algorithms for distributed detection and estimation
in static and mobile sensor networks. In distributed detection or estimation scenarios
in clustered wireless sensor networks, sensor motes observe their local environment,
make decisions or quantize these observations into local estimates of finite length, and
send/relay them to a Cluster-Head (CH). For event detection tasks that are subject to
both measurement errors and communication errors, we develop an algorithm that
combines a Maximum a Posteriori (MAP) approach for local and global decisions with
low-complexity channel codes and processing algorithms. For event estimation tasks that
are subject to measurement errors, quantization errors and communication errors, we
develop an algorithm that uses dithered quantization and channel compensation to ensure
that each mote's local estimate received by the CH is unbiased and then lets the CH fuse
these estimates into a global one using a Best Linear Unbiased Estimator (BLUE). We then
determine both the minimum energy required for the network to produce an estimate
with a prescribed error variance and show how this energy must be allocated amongst the
motes in the network.
In mobile wireless sensor networks, the mobility model governing each node will affect the
detection accuracy at the CH and the energy consumption to achieve this level of accuracy.
Correlated Random Walks (CRWs) have been proposed as mobility models that
accounts for time dependency, geographical restrictions and nonzero drift. Hence, the
solution to the continuous-time, 1-D, finite state space CRW is provided and its statistical
behavior is studied both analytically and numerically. The impact of the motion of sensor
on the network's performance is also studied.
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Devaraj, Sreekalyan. "Estimation of path duration in mobile ad-hoc networks: A theoretical study." Thesis, Wichita State University, 2009. http://hdl.handle.net/10057/2529.
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Mobile ad hoc networks (MANETs) are widely deployed for different purposes.
Some of these areas are for the military, emergency rescue operations, etc. These
networks are established "on the fly" and, therefore, play a decisive role in such
applications. From a network point of view, MANETs are self configuring and
dynamically changing networks. Since the topology changes dynamically, each node in
the network must keep track of other nodes' movements and maintain connectivity. The
most popular MANET routing protocols use response time or number of hops to decide
the feasible routes. Estimation of path duration can enhance the efficiency of routing
protocols in MANETs. One such area in reactive routing can be the assignment of route
expiry time. This thesis attempts to develop a mathematical model to compute the path
duration. The mathematical model is based on the concept of least remaining distance
(LRD). LRD is similar to the shortest path forwarding, where the path is selected based
on the least number of hops. In this technique, the path is selected by the least path
duration. An analytical expression of path duration for an n-hop network is derived. The
accuracy of the model is validated with the experimental results available in the
literature.Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science
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von, dem Knesebeck Matthias. "Fast motion estimation methods for H.264 video coding on mobile devices." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/28761.
Full textAbstract:
Digital video is becoming an increasingly widespread application on a multitude of devices ranging from mobile devices to digital cinema. Technological advancements in processing speed and available bandwidth along with substantial improvements in compression techniques enable completely new applications and services for digital video content.
The most demanding task in video encoding is the motion estimation process which aims to identify similarities to previously transmitted video frames. Up to 90% of the processing requirements are attributable to this element.
In this thesis, we present three methods for encoding new and transcoding existing video content with significantly reduced computational complexity while maintaining both quality and bitrate.
The first method reduces the number of steps required to perform motion estimation by adaptively adjusting the search accuracy needed in distortion measurement.
The second method addresses the topic of mode decision in video encoding and provides an algorithm that allows an early decision about the most probable modes without the need to evaluate all 259 different combinations of block sizes.
The third method provides a multi-dimensional measure that facilitates evaluating only the most likely modes for efficiently transcoding existing pre-encoded content to lower resolutions with an arbitrary downscaling ratio. This is an important factor for the ever-growing number of devices and application scenarios that access existing pre-encoded content. Our method supplements existing fast transcoding schemes that primarily focus on efficiently determining motion vectors in transcoding.
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Yiin, Lihbor. "Sequence estimation receivers for trellis-coded continuous phase modulation on mobile channels." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/14818.
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Saur, Stephan [Verfasser]. "Channel Estimation for Mobile Wideband Code Division Multiple Access (WCDMA) / Stephan Saur." Aachen : Shaker, 2008. http://d-nb.info/1162793139/34.
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Sheen, Wern-Ho. "Performance analysis of sequence estimation techniques for intersymbol interference channels." Diss., Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/13089.
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Coulton, Paul. "Novel synchronisation and channel estimation techniques using auxiliary decoding information." Thesis, Lancaster University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266675.
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Miao, H. (Honglei). "Channel estimation and positioning for multiple antenna systems." Doctoral thesis, University of Oulu, 2007. http://urn.fi/urn:isbn:9789514284113.
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Abstract
The multiple–input multiple–output (MIMO) technique, applying several transmit and receive antennas in wireless communications, has emerged as one of the most prominent technical breakthroughs of the last decade. Wideband MIMO parameter estimation and its applications to the MIMO orthogonal frequency division multiplexing (MIMO–OFDM) channel estimation and mobile positioning are studied in this thesis.
Two practical MIMO channel models, i.e., correlated-receive independent-transmit channel and correlated-transmit-receive channel, and associated space-time parameter estimation algorithms are considered. Thanks to the specified structure of the proposed training signals for multiple transmit antennas, the iterative quadrature maximum likelihood (IQML) algorithm is applied to estimate the time delay and spatial signature for the correlated-receive independent-transmit MIMO channels. For the correlated-transmit-receive MIMO channels, the spatial signature matrix corresponding to a time delay can be further decomposed in such a way that the angle of arrival (AOA) and the angle of departure (AOD) can be estimated simultaneously by the 2-D unitary ESPRIT algorithm. Therefore, the combination of the IQML algorithm and the 2-D unitary ESPRIT algorithm provides a novel solution to jointly estimate the time delay, the AOA and the AOD for the correlated-transmit-receive MIMO channels. It is demonstrated from the numerical examples that the proposed algorithms can obtain good performance at a reasonable cost.
Considering the correlated-receive independent-transmit MIMO channels, channel coefficient estimation for the MIMO–OFDM system is studied. Based on the parameters of the correlated-receive independent-transmit MIMO channels, the channel statistics in terms of the correlation matrix are developed. By virtue of the derived channel statistics, a joint spatial-temporal (JST) filtering based MMSE channel estimator is proposed which takes full advantage of the channel correlation properties. The mean square error (MSE) of the proposed channel estimator is analyzed, and its performance is also demonstrated by Monte Carlo computer simulations. It is shown that the proposed JST minimum mean square error (MMSE) channel estimator outperforms the more conventional temporal MMSE channel estimator in terms of the MSE when the signals in the receive antenna array elements are significantly correlated. The closed form bit error probability of the space-time block coded OFDM system with correlation at the receiver is also developed by taking the channel estimation errors and channel statistics, i.e., correlation at the receiver, into account.
Mobile positioning in the non-line of sight (NLOS) scenarios is studied. With the knowledge of the time delay, the AOA and the AOD associated with each NLOS propagation path, a novel geometric approach is proposed to calculate the MS's position by only exploiting two NLOS paths. On top of this, the least squares and the maximum likelihood (ML) algorithms are developed to utilize multiple NLOS paths to improve the positioning accuracy. Moreover, the ML algorithm is able to estimate the scatterers' positions as well as those of the MSs. The Cramer-Rao lower bound related to the position estimation in the NLOS scenarios is derived. It is shown both analytically and through computer simulations that the proposed algorithms are able to estimate the mobile position only by employing the NLOS paths.
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Mashali, Mustafa. "Kinematic Control of Redundant Mobile Manipulators." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5989.
Full textAbstract:
A mobile manipulator is a robotic arm mounted on a robotic mobile platform. In such a system, the degrees of freedom of the mobile platform are combined with that of the manipulator. As a result, the workspace of the manipulator is substantially extended. A mobile manipulator has two trajectories: the end-effector trajectory and the mobile platform trajectory. Typically, the mobile platform trajectory is not defined and is determined through inverse kinematics. But in some applications it is important to follow a specified mobile platform trajectory. The main focus of this work is to determine the inverse kinematics of a mobile manipulator to follow the specified end-effector and mobile platform trajectories, especially when both trajectories cannot be exactly followed simultaneously due to physical limitations. Two new control algorithms are developed to solve this problem.
In the first control algorithm, three joint-dependent control variables (spherical coordinates D, α and β) are introduced to define the mobile platform trajectory in relation to the end-effector trajectory and vice versa. This allows direct control of the mobile platform motion relative to the end-effector. Singularity-robust and task-priority inverse kinematics with gradient projection method is used to find best possible least-square solutions for the dual-trajectory tracking while maximizing the whole system manipulability. MATLAB Simulated Planar Mobile Manipulation is used to test and optimize the proposed control system. The results demonstrate the effectiveness of the control system in following the two trajectories as much as possible while optimizing the whole system manipulability measure.
The second new inverse kinematics algorithm is introduced when the mobile platform motion is restricted to stay on a specified virtual or physical track. The control scheme allows xii the mobile manipulator to follow the desired end-effector trajectory while keeping the mobile platform on a specified track. The mobile platform is moved along a track to position the arm at a pose that facilitates the end-effector task. The translation of the redundant mobile manipulator over the mobile platform track is determined by combining the mobility of the platform and the manipulation of the redundant arm in a single control system. The mobile platform is allowed to move forward and backward with different velocities along its track to enable the end-effector in following its trajectory. MATLAB simulated 5 DoF redundant planar mobile manipulator is used to implement and test the proposed control algorithm. The results demonstrate the effectiveness of the control system in adjusting the mobile platform translations along its track to allow the arm to follow its own trajectory with high manipulability. Both control algorithms are implemented on MATLAB simulated wheelchair mounted robotic arm system (WMRA-II). These control algorithms are also implemented on real the WMRA-II hardware.
In order to facilitate mobile manipulation, a control motion scheme is proposed to detect and correct the mobile platform pose estimation error using computer vision algorithm. The Iterative Closest Point (ICP) algorithm is used to register two consecutive Microsoft Kinect camera views. Two local transformation matrices i. e., Encoder and ICP transformation matrices, are fused using Extended Kalman Filter (EKF) to filter the encoder pose estimation error. VICON motion analysis system is used to capture the ground truth of the mobile platform. Real time implementation results show significant improvement in platform pose estimation. A real time application involving obstacle avoidance is used to test the proposed updated motion control system.
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Lenardi, Massimiliano. "Advanced mobile receivers and downlink channel estimation for 3G UMTS-FDD WCDMA systems /." [S.l.] : [s.n.], 2002. http://library.epfl.ch/theses/?nr=2574.
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Sadeghi, Parastoo School of Electrical Engineering And Telecommunications UNSW. "Modelling, information capacity, and estimation of time-varying channels in mobile communication systems." Awarded by:University of New South Wales. School of Electrical Engineering And Telecommunications, 2006. http://handle.unsw.edu.au/1959.4/32310.
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In the first part of this thesis, the information capacity of time-varying fading channels is analysed using finite-state Markov channel (FSMC) models. Both fading channel amplitude and fading channel phase are modelled as finite-state Markov processes. The effect of the number of fading channel gain partitions on the capacity is studied (from 2 to 128 partitions). It is observed that the FSMC capacity is saturated when the number of fading channel gain partitions is larger than 4 to 8 times the number of channel input levels. The rapid FSMC capacity saturation with a small number of fading channel gain partitions can be used for the design of computationally simple receivers, with a negligible loss in the capacity. Furthermore, the effect of fading channel memory order on the capacity is studied (from first- to fourth-order). It is observed that low-order FSMC models can provide higher capacity estimates for fading channels than high-order FSMC models, especially when channel states are poorly observable in the presence of channel noise. To explain the effect of memory order on the FSMC capacity, the capacities of high-order and low-order FSMC models are analytically compared. It is shown that the capacity difference is caused by two factors: 1) the channel entropy difference, and 2) the channel observability difference between the high-order and low-order FSMC models. Due to the existence of the second factor, the capacity of high-order FSMC models can be lower than the capacity of low-order FSMC models. Two sufficient conditions are proven to predict when the low-order FSMC capacity is higher or lower than the high-order FSMC capacity. In the second part of this thesis, a new implicit (blind) channel estimation method in time- varying fading channels is proposed. The information source emits bits ???0??? and ???1??? with unequal probabilities. The unbalanced source distribution is used as a priori known signal structure at the receiver for channel estimation. Compared to pilot-symbol-assisted channel estimation, the proposed channel estimation technique can achieve a superior receiver bit error rate performance, especially at low signal to noise ratio conditions.