Dissertations / Theses on the topic 'Inertial data'
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Guner, Dunya Rauf Levent. "Inertial Navigation Sytem Improvement Using Ground Station Data." Phd thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12615036/index.pdf.
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Missile navigation systems rely on hybrid INS/GPS systems to employ lower grade inertial sensors for the sake of cost and availability. Current inertial navigation systems on missiles can perform accurately for a limited time without GPS aiding. However, GPS is the most likely system that is going to be jammed in a crisis or war by low cost jammers by any opposing force. Missiles do not have adequate equipment to maintain accuracy when GPS is jammed completely in the battle area.
In this thesis, a new method is proposed to improve performance of INS systems onboard missiles and autonomous aerial vehicles with EO sensors in a GPS denied environment. Previously laid ground based beacons are used by the missile EO/IIR seeker for bearing-only measurements and position updates are performed by the use of modified artillery survey algorithms based on triangulation techniques which involve angle measurements.
For mission planning, two main problems are identified as deployment problem and path planning problem and a tool for the optimal laying of beacons for a given desired trajectory and optimal path planning for a given network of beacons is developed by using evolutionary algorithms and results for test scenarios are discussed.
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Bertani, Federico. "Reconstruction of vehicle dynamics from inertial and GNSS data." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/16105/.
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The increasingly massive collection of data from various types of sensors installed on vehicles allows the study and reconstruction of their dynamics in real time, as well as their archiving for subsequent analysis.
This Thesis describes the design of a numerical algorithm and its implementation in a program that uses data from inertial and geo-positioning sensors, with applications in industrial contexts and automotive research. The result was made usable through the development of a Python add-on for the Blender graphics program, able to generate a three-dimensional view of the dynamics that can be used by experts and others.
Throughout the Thesis, particular attention was paid to the complex nature of the data processed, introducing adequate systems for filtering, interpolation, integration and analysis, aimed at reducing errors and simultaneously optimizing performances.
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Peixoto, João Carlos Pimentel Fidalgo. "Visual and inertial data integration to assist humanoid balance." Master's thesis, Universidade de Aveiro, 2016. http://hdl.handle.net/10773/17955.
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Mestrado em Engenharia MecânicaEsta dissertação aborda o problema que consiste na medição do movimento da cabeça de um robot humanóide fundindo dados inerciais e visuais, com o objetivo de obter o output que melhor descreve o movimento da cabeça do humanóide. O seu principal objectivo é perceber e desenvolver um algoritmo usando o Filtro de Kalman, que irá fundir ambas as fontes de dados com o propósito de obter uma nova fonte de informação com um maior grau de confiança. Para cumprir os objectivos, um modelo da cabeça do humanóide, juntamente com as câmaras e os sensores inerciais, vão ser movidos na ponta de um braço robótico industrial, que é usado como grupo de controle (ground truth) no que toca a posição angular. Pontos-chave nos frames obtidos através da câmara, são extra dos e usados para calcular a diferença na posição angular que ocorreu entre frames, que vão mais tarde, juntamente com os dados inerciais obtidos de giroscópios, servir de input a um modelo de um Filtro de Kalman. Uma vez que este dissertação assenta em ferramentas como o Filtro de Kalman, que tem como propósito unir dados de origens diferentes, é essencial que se conheçam os tipos de dados e ferramentas que irão ser utilizados. Assim, várias experiências foram desenvolvidas e estudadas com o intuito de desenvolver o conhecimento nessas matérias. Adicionalmente, erros foram acrescentados aos dados, artificialmente, com o objectivo de emular sensores sensíveis a ruído. No entanto, o sistema continua a ter uma performance positiva.
This thesis addresses the problem of measuring a humanoid robot head motion by merging inertial and visual data, in order to obtain an output that will describe the head motion of the robot. Its primary goal is the understanding and development of an algorithm using the Kalman Filter tool, which will merge inertial and visual data, resulting in a more reliable source of information. To accomplish this, a model of a humanoid robot head, including a camera and inertial sensors, are moved on the tip of an industrial robot's arm which is used as ground truth for angular position. Visual features are extracted from the camera images and used to calculate angular displacement and velocity of the camera, which is then merged with angular velocities from a gyroscope and fed into a Kalman Filter, in order to obtain an output. Since this thesis is expected to merge two di erent kinds of data using the Kalman Filter tool, the need to understand both types of data arises, as well as the way the Kalman Filter operates. Therefore, many experiments were developed and studied with the intent of deepening the knowledge on those matters. The results are quite interesting. Additionally, errors are introduced arti cially into the data to emulate noisy sensors, and the system still performs very well.
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FERRARI, ANNA. "Personalization of Human Activity Recognition Methods using Inertial Data." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2021. http://hdl.handle.net/10281/305222.
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Recognizing human activities and monitoring population behavior are fun- damental needs of our society. Population security, crowd surveillance, healthcare support and living assistance, lifestyle and behavior tracking are some of the main applications which require the recognition of activities. Activity recognition involves many phases, i.e. the collection, the elaboration and the analysis of information about human activities and behavior. These tasks can be fulfilled manually or automatically, even though a human-based recognition system is not long-term sustainable and scalable.
Nevertheless, transforming a human-based recognition system to computer- based automatic system is not a simple task because it requires dedicated hardware and a sophisticated engineering computational and statistical techniques for data preprocessing and analysis. Recently, considerable changes in tech- nologies are largely facilitating this transformation. Indeed, new hardwares and softwares have drastically modified the activity recognition systems. For example, Micro-Electro-Mechanical Systems (MEMS) progress has enabled a reduction in the size of the hardware. Consequently, costs have decreased. Size and cost reduction allows to embed sophisticated sensors into simple devices, such as phones, watches, and even into shoes and clothes, also called wearable devices. Furthermore, low costs, lightness, and small size have made wearable devices’ highly pervasive and accelerated their spread among the population. Today, a very small part of the world population doesn’t own a smartphone. According to Digital 2020: Global Digital Overview, more than 5.19 billion people now use mobile phones. Among the western countries, smartphones and smartwatches are gadgets of people everyday life.
The pervasiveness is an undoubted advantage in terms of data generation. Huge amount of data, that is big data, are produced every day. Furthermore, wearable devices together with new advanced software technologies enable data to be sent to servers and instantly analyzed by high performing computers.
The availability of big data and new technology improvements, permitted Artificial Intelligence models to rise. In particular, machine learning and deep learning algorithms are predominant in activity recognition.
Together with technological and algorithm innovations, the Human Ac- tivity recognition (HAR) research field has born. HAR is a field of research which aims at automatically recognizing people’s physical activities. HAR investigates on the selection of the best hardware, e. g. the best devices to be used for a given application, on the choice of the software to be dedicated to a specific task, and on the increasing of the algorithm performances.
HAR has been a very active field of research for years and it is still considered one of the most promising research topic for a large spectrum of ap- plications. In particular, it remains a very challenging research field for many reasons. The selection of devices and sensors, the algorithm’s performances, the collection and the preprocessing of the data, all are requiring further investigation to improve the overall activity recognition system performances.
In this work, two main aspects have been investigated:
• the benefits of personalization on the algorithm performances, when trained on small size datasets: one of the main issue concerning HAR research community is the lack of the availability of public dataset and labelled data. [...]
• a comparison of the performances in HAR obtained both from tradi- tional and personalized machine learning and deep learning techniques.[...]Recognizing human activities and monitoring population behavior are fun- damental needs of our society. Population security, crowd surveillance, healthcare support and living assistance, lifestyle and behavior tracking are some of the main applications which require the recognition of activities. Activity recognition involves many phases, i.e. the collection, the elaboration and the analysis of information about human activities and behavior. These tasks can be fulfilled manually or automatically, even though a human-based recognition system is not long-term sustainable and scalable. Nevertheless, transforming a human-based recognition system to computer- based automatic system is not a simple task because it requires dedicated hardware and a sophisticated engineering computational and statistical techniques for data preprocessing and analysis. Recently, considerable changes in tech- nologies are largely facilitating this transformation. Indeed, new hardwares and softwares have drastically modified the activity recognition systems. For example, Micro-Electro-Mechanical Systems (MEMS) progress has enabled a reduction in the size of the hardware. Consequently, costs have decreased. Size and cost reduction allows to embed sophisticated sensors into simple devices, such as phones, watches, and even into shoes and clothes, also called wearable devices. Furthermore, low costs, lightness, and small size have made wearable devices’ highly pervasive and accelerated their spread among the population. Today, a very small part of the world population doesn’t own a smartphone. According to Digital 2020: Global Digital Overview, more than 5.19 billion people now use mobile phones. Among the western countries, smartphones and smartwatches are gadgets of people everyday life. The pervasiveness is an undoubted advantage in terms of data generation. Huge amount of data, that is big data, are produced every day. Furthermore, wearable devices together with new advanced software technologies enable data to be sent to servers and instantly analyzed by high performing computers. The availability of big data and new technology improvements, permitted Artificial Intelligence models to rise. In particular, machine learning and deep learning algorithms are predominant in activity recognition. Together with technological and algorithm innovations, the Human Ac- tivity recognition (HAR) research field has born. HAR is a field of research which aims at automatically recognizing people’s physical activities. HAR investigates on the selection of the best hardware, e. g. the best devices to be used for a given application, on the choice of the software to be dedicated to a specific task, and on the increasing of the algorithm performances. HAR has been a very active field of research for years and it is still considered one of the most promising research topic for a large spectrum of ap- plications. In particular, it remains a very challenging research field for many reasons. The selection of devices and sensors, the algorithm’s performances, the collection and the preprocessing of the data, all are requiring further investigation to improve the overall activity recognition system performances. In this work, two main aspects have been investigated: • the benefits of personalization on the algorithm performances, when trained on small size datasets: one of the main issue concerning HAR research community is the lack of the availability of public dataset and labelled data. [...] • a comparison of the performances in HAR obtained both from tradi- tional and personalized machine learning and deep learning techniques.[...]
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Tuul, Viktor. "Online Collaborative Radio-enhanced Visual-inertial SLAM." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254952.
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Simultaneous localization and mapping (SLAM) allows robots and other devices to localize and navigate in environments by using a map which itself generates. SLAM for single agent applications has matured and is showing promising results, thus the interest for collaborative SLAM has increased.This thesis proposes a framework for online collaborative radio-enhanced visual-inertial (VI) SLAM where multiple agents can collaborate by having their individually built maps merged and shared amongst each other. The framework is centralized with the aim to allow multiple agents to be managed by a single machine, also rendering it feasible to use the framework with agents that have limited computational resources, e.g. nano drones. Furthermore, radio technology is implemented in the framework which augments the SLAM solution by fusing ultra-wideband (UWB) anchor information into the built maps. This enables agents to query relevant parts of potentially large maps based on their contemporary radio activity.Four individual experiments are conducted to thoroughly evaluate the proposed solution. The results show that the collaborative SLAM system successfully allow agents to localize on parts of a map that other agents have built, running simultaneously. Moreover, the results also show that fusing UWB information into a visual-inertial map allow agents to perform partial-map queries, restricting the search area for visual matches between camera images and the map, reducing the risk of false re-localizations.Samtidig lokalisering och kartläggning (SLAM) möjliggör för robotar och andra enheter att lokalisera sig och navigera i miljöer genom att nyttja en karta som den själv genererar. SLAM för enskilda agenter har mognat och visar lovande resultat, vilket innebär att intresset för kollaborativ SLAM har ökat.Detta arbete presenterar ett ramverk för kollaborativ radioaugmenterad visuell-inertial (VI) SLAM där flera agenter, exempelvis robotar, kan samverka genom att deras individuellt byggda kartor sammansätts och distributeras mellan varandra. Ramverket är centraliserat i syfte att att flera agenter hanteras av en enda maskin, vilket också möjliggör att ramverket kan användas for agenter med begränsade beräkningsresurser, till exempel nanodrönare. Dessutom så är även radioteknik implementerat i systemet vilket augmenterar SLAM-lösningen genom att inkorporera mottagen information från ultrabandbreddsnoder (UWB) i de byggda kartorna. Detta gör det möjligt för andra agenter att begränsa delar av potentiellt stora kartor for lokalisering baserat på deras innevarande mottagna radiosignaler.Fyra individuella experiment utförs för att grundligt utvärdera den föreslagna lösningen. Resultaten visar att det framtagna ramverket möjliggör för agenter att lokalisera på delar av kartor som andra agenter har byggt, medan de samtidigt körs. Dessutom visar resultaten att implementationen av UWBinformationen i de byggda kartorna medför att agenter kan utföra efterfrågningar på relevanta delar av en global karta. Detta möjliggör begränsningar av sökområdet för visuella träffar mellan kamera och karta och därigenom minska risken för falska omlokaliseringar.
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Bender, Daniel [Verfasser]. "Airborne Navigation by Fusing Inertial and Camera Data / Daniel Bender." Bonn : Universitäts- und Landesbibliothek Bonn, 2018. http://d-nb.info/1160594554/34.
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Huai, Jianzhu. "Collaborative SLAM with Crowdsourced Data." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1483669256597152.
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Jah, Moriba Kemessia. "Mars aerobraking spacecraft state estimation by processing inertial measurement unit data." Diss., Connect to online resource, 2005. http://wwwlib.umi.com/dissertations/fullcit/3178333.
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Fernandes, Claudio dos Santos. "Visual and inertial data fusion for Globally consistent point cloud registration." Universidade Federal de Minas Gerais, 2013. http://hdl.handle.net/1843/ESSA-9D6GLH.
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This work addresses the problem of mapping 3D static environments by using an RGBD sensor, that captures image and depth, and a MARG sensor, composed by inertial sensors and magnetometers. The approached problem is relevant to the robotics field, since its solution will allow mobile robots to autonomously navigate and map unknown environments. Besides, it has impacts on several applications that perform 3D modeling by using scans obtained from depth sensors. Amongst them, one can mention the digital replication of sculptures and art objects, the modeling of characters for games and movies, and the reconstruction of CAD models from old buildings. We have decided to address the problem by performing a rigid registration of point clouds sequentially captured by the depth sensor, posteriorly using the data provided by the inertial sensor as a guide both during the coarse alignment stage and during the global optimization of the estimated map. During the point cloud alignment based on feature matching, the rotation estimated from the MARG sensor is used as an initial estimation of the attitude between point clouds. Thereby, we seek to match keypoints considering only three translational degrees of freedom. The attitude given by the MARG is also used to reduce the search space for loop closures. The fusion of RGB-D and inertial data is still very little explored in the related literature. A similar work already published only uses inertial data to improve the attitude estimation during the pairwise alignment in an ad-hoc fashion, potentially discarding it under specific conditions, and neglecting the global optimization stage. Since we use a MARG sensor, we assume the sensor drift to be negligible for the purposes of our application, which allows us to always use its data, specially during the global optimization stage. In our experiments, we mapped the walls of a rectangular room with dimensions 9.84m x 7.13m and compared the results with a map from the same scene captured by a Zebedee sensor, state of the art in terms of laser-based 3D mapping. We also compared the proposed algorithm against the RGB-D SLAM methodology, which, unlike our methodology, was not capable of detecting the loop closure region.Este trabalho aborda o mapeamento tridimensional de ambientes estáticos utilizando um sensor RGB-D, que captura imagem e profundidade, e um sensor MARG, composto de sensores inerciais e magnetômetros. O problema do mapeamento é relevante ao campo da robótica, uma vez que sua solução permitirá a robôs navegarem e mapearem de forma autônoma ambientes desconhecidos. Além disso, traz impactos em diversas aplicações que realizam modelagem 3D a partir de varreduras obtidas de sensores de profundidade. Dentre elas, estão a replicação digital de esculturas e obras de arte, a modelagem de personagens para jogos e filmes, e a obtenção de modelos CAD de edificações antigas. Decidimos abordar o problema realizando o registro rígido de nuvens de pontos adquiridas sequencialmente pelo sensor de profundidade, usando as informações providas pelo sensor inercial como guia tanto no estágio de alinhamento grosseiro quanto na fase de otimização global do mapa gerado. Durante o alinhamento de nuvens de pontos por casamento de features, a rotação estimada pelo sensor MARG é utilizada como uma estimativa inicial da orientação entre nuvens de pontos. Assim, procuramos casar pontos de interesse considerando apenas três graus de liberdade translacionais. A orientação provida pelo MARG também é utilizada para reduzir o espaço de busca por fechamento de loops. A fusão de dados RGB-D com informações inerciais ainda é pouco explorada na literatura. Um trabalho similar já publicado apenas utiliza dados inerciais para melhorar a estimativa da rotação durante o alinhamento par a par de maneira ad-hoc, potencialmente descartando-os em condições específicas, e negligenciando o estágio de otimização global. Por utilizar um sensor MARG, assumimos que o drift do sensor é negligível em nossa aplicação, o que nos permite sempre utilizar seus dados, especialmente durante a fase de otimização global. Em nossos experimentos, realizamos o mapeamento das paretes de um ambiente retangular de dimensões 9,84m x 7,13m e comparamos os resultados com um mapeamento da mesma cena feito a partir de um sensor Zebedee, estado da arte em mapeamento 3D a laser. Também comparamos o algoritmo proposto com a metodologia RGB-D SLAM, que, ao contrário da nossa metodologia, não foi capaz de detectar a região de fechamento de loop.
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Newlin, Michael Linton Hung John Y. Bevly David M. "Design and development of a GPS intermediate frequency and IMU data acquisition system for advanced integrated architectures." Auburn, Ala., 2006. http://repo.lib.auburn.edu/2006%20Fall/Theses/NEWLIN_MICHAEL_7.pdf.
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Teran, Espinoza Aldo. "Acoustic-Inertial Forward-Scan Sonar Simultaneous Localization and Mapping." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-287368.
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The increasing accessibility and versatility of forward-scan (FS) imaging sonars (also known as forward looking sonars or FLS) has spurred the interest of the robotics community seeking to solve the difficult problem of robotic perception in low-visibility underwater scenarios. Processing the incoming data from an imaging sonar is challenging, since it captures an acoustic 2D image of the 3D scene instead of providing straightforward range measurements like other sonar technologies do (e.g. multibeam sonar). Hence, complex postprocessing and sensor fusion techniques are required to extract useful information out of the sonar image. The present report details development, validation and implementation of an acoustic-inertial localization and mapping algorithm that processes sonar images captured by an FS sonar and inertial measurements to solve the simultaneous localization and mapping (SLAM) problem with an underwater sensor suite. A sonar odometry pose constraint is computed by detecting and matching features from two consecutive sonar images on a degeneracy-aware two-view bundle adjustment. The sonar odometry measurements are fused with preintegrated inertial measurements in a minimal pose-graph representation. The state-of-the-art iSAM2 (Incremental Smoothing and Mapping) solver is used to allow for real-time localization. A Python simulator was developed to evaluate the performance of the two-view bundle adjustment algorithm. Results are presented and discussed from both computer simulations in Gazebo using the Robot Operating System (ROS) and from real-world tests in a controlled environment with an in-house developed sensor suite. Sonar image degeneracies, sensor drift, and computation complexity, proved to be hard to tackle, reducing the performance and robustness of the current implementation of the SLAM solution. However, the current work will serve as a stepping stone for for future work and collaboration in underwater localization and mapping using FS sonars.Den ökande tillgängligheten och mångsidigheten för framåtriktade (FS) bildåtergivande ekolod (även känd som framåtriktade ekolod eller FLS) har gett upphov till robotgemenskapens intresse som försöker lösa det svåra problemet med robotuppfattning i undervattensscenarier med låg synlighet. Att bearbeta inkommande data från ett bildbildsekolod är utmanande, eftersom den tar en akustisk 2D-bild av 3D-scenen istället för att ge enkla räckviddsmätningar som andra ekolodstekniker gör (t.ex. multibeam-ekolod). Därför krävs komplexa efterbearbetnings- och sensorfusionsmetoder för att extrahera användbar information ur ekolodsbilden. Denna rapport beskriver utvecklingen, valideringen och implementeringen av en akustisk-tröghetslokaliserings- och kartläggningsalgoritm som bearbetar ekolodsbilder som fångats av ett FS-ekolod och tröghetsmätningar för att lösa samtidig lokalisering och kartläggning (SLAM) med en undervattenssensor. En begränsning för ekolodsmätning utgörs av att detektera och matcha funktioner från två på varandra följande ekolodsbilder på en degenerationsmedveten tvåvisningsbuntjustering. Mätningarna av ekolodsmätningen smälter samman med förintegrerade tröghetsmätningar i en minimal framställning av graf. Den senaste iSAM2- lösaren (Incremental Smoothing and Mapping) används för att möjliggöra lokalisering i realtid. En Python-simulator utvecklades för att utvärdera prestanda för algoritmen för tvåvisningsbuntjustering. Resultaten presenteras och diskuteras från både datorsimuleringar i Gazebo med hjälp av Robot Operating System (ROS) och från verkliga tester i en kontrollerad miljö med en egenutvecklad sensorsvit. Sonarbildsgenerationer, sensordrift och beräkningskomplexitet visade sig vara svåra att hantera, vilket minskade prestanda och robusthet i den nuvarande implementeringen av SLAM-lösningen. Emellertid kommer det nuvarande arbetet att fungera som en språngbräda för framtida arbete och samarbete inom lokalisering och kartläggning under vattnet med hjälp av FS-ekolod.
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Beaufils, Bertrand. "Topological Data Analysis and Statistical Learning for measuring pedestrian activities from inertial sensors." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASS107.
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Cette thèse s’intéresse à la détection de mouvements spécifiques à partir du dispositif ActiMyo développé par la société Sysnav, système de capteurs inertiels miniatures bascoût pouvant se porté à la cheville et au poignet. En particulier, une approche d’apprentissage statistique supervisé vise à détecter les foulées dans les enregistrements cheville. Ce premier travail, combiné avec un algorithme breveté par l’entreprise Sysnav, permet de reconstruire la trajectoire du piéton. Cette trajectoire est ensuite utilisée dans une nouvelle méthode d’apprentissage supervisé pour la reconnaissance d’activité qui est une précieuse information notamment dans un contexte médical. Ces deux algorithmes proposent une approche innovante basée sur l’alignement des signaux inertiels et l’extraction d’intervalles candidats qui sont ensuite classés par l’algorithme de Gradient Boosting Trees. Le manuscrit présente également une architecture de réseaux de neurones combinant des channels de convolution et d’analyse topologique des données pour la détection de mouvements caractéristiques de la maladie de Parkinson tels que les tremblements et crises de dyskinésieThis thesis focuses on the detection of specific movements using ActiMyo, a device developed by the company Sysnav. This system is composed by low-cost miniature inertial sensors that can be worn on the ankle and wrist. In particular, a supervised statistical learning approach aims to detect strides in ankle recordings. This first work, combined with an algorithm patented by Sysnav, allows to compute the trajectory of the pedestrian. This trajectory is then used in a new supervised learning method for the activity recognition, which is valuable information, especially in a medical context. These two algorithms offer an innovative approach based on the alignment of inertial signals and the extraction of candidate intervals which are then classified by the Gradient Boosting Trees algorithm. This thesis also presents a neural network architecture combining convolutional channels and topological data analysis for the detection of movements representative of Parkinson’s disease such as tremors and dyskinesia crises
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Gwatiringa, Tinashe G. "Sea state estimation from inertial platform data for real-time ocean wave prediction." Master's thesis, University of Cape Town, 2018. http://hdl.handle.net/11427/29496.
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Ocean observation is vital in understanding how the oceans contribute toward climate change and other effects. This is one of many undertakings requiring a persistent presence in the oceans. These maritime activities are mainly carried out on large research vessels chartered for weeks at a time, which can be extremely costly. In addition, the data obtained when using these vessels are only short snapshots of the continual processes that occur. Recently, there has been a drive toward using Unmanned Surface Vehicles (USVs) and Unmanned Underwater Vehicles (UUVs), which can be deployed at a fraction of the cost, and provide greatly improved spatio-temporal data. The wave glider (WG) is one such autonomous marine robot used for persistent ocean research and other maritime activities, and forms the focus of this study. The WG is a low power USV/UUV hybrid that harnesses wave energy for propulsion, and has a small solar- and battery-powered thruster, and a rudder for steering. Due to effects of waves, currents, and other disturbances, the platform tends to veer off its desired path. Additionally, local sea state information is not taken into consideration while manoeuvring, hence energy extraction from ocean waves is not optimal. More sophisticated navigation algorithms operating on a per-wave strategy may improve accuracy along a specified path and maximise the energy uptake from the waves. To realise these improvements requires prediction of local wave behaviour. If one can predict what the wave field will be a short time in the future, then possible control action can be taken to efficiently navigate in the environment. Inertial measurements and wave modelling have been used to improve localisation of the WG platform directly, and predict the platform’s velocity. However there is limited work in the context of WG navigation. Hence the problem this dissertation aims to solve is the estimation and subsequent prediction of local wave behaviour. This work proposes a novel approach to estimate the sea state and hence predict short-term, local wave behaviour from inertial measurements on a slow-moving marine platform such as the WG. A Kalman filtering strategy consisting of a phase-locked loop and filter based sea state estimator is used to generate local height and angle of arrival estimates. This method offers an improvement over existing Fast Fourier Transform methods as it does not require long time series data to produce results, and enables the prediction of wave behaviour a short time into the future. The ideas are tested in simulation by generating wind waves using ocean wave models such as the Pierson Moskowitz model, and dynamic a dynamic model of the WG platform. In addition, a small scale lab experiment is carried out to verify the performance of the sea-state estimator developed. Preliminary results obtained indicate that relative wave height can be estimated on-board a marine platform, using only inertial sensors.
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Ashraf, Pouya. "Improving Spatial Sound Capturing on Mobile Devices Through Fusion of Inertial Measurement Data." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-372151.
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Through the use of sensor arrays it is possible to extract spatial information about signals present in the environment. For instance position, velocity, distance, etc. In this thesis we focus on the use of microphone arrays with the aim of accurately determining, and over time track, the Direction of Arrival (DoA) of nearby sound signals impinging on the array. As modern mobile devices like smartphones and tablets are commonly equipped with two or more microphones, these constitute a simple microphone array. This gives us the opportunity of attaining the above aim. However, in the scenario that the microphone array is not stationary, a number of problems arise. In this thesis we implement an algorithm to estimate the microphone array's orientation in three-dimensional space, with the aim of using these estimates to cancel the effect of the array's orientation on the DoA estimates. The cancellation is done with a dynamical model, which we use in a modified Kalman Filter (KF) capable of tracking an arbitrary number of sound sources over time. Additionally, we estimate the computational cost of the mentioned algorithms. The simulation results show satisfactory performance in the modified KF with respect to handling crossing trajectories and noise in the measurements. The chosen algorithm for orientation estimation proves susceptible to magnetic disturbances to the extent that usage in the context of mobile devices is undesirable. Due to this, the orientation estimates are provided by a proprietary algorithm. Experiments where the DoA of the sound sources are computed using actual sound, together with orientation estimates, confirm the correctness of the proposed model.
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A, Al-Jameel H., and Hannawi Ali Hussein. "Fusion of visual tracking and inertial measurement units for movement analysis." Thesis, Boston, USA, 2020. http://openarchive.nure.ua/handle/document/11839.
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The study analyzed the possibility of combining visual tracking and data inertial measurement units (IMU). The block diagram of a motion registration system based on a combination of visual tracking data and IMU data is proposed. Optical data from cameras (at least two) are used to calculate the position. In parallel, IMU data is also used to calculate the position. All this information is combined in the appropriate block. Specialized probability filters should be used to fuse dissimilar data. After analyzing the available mathematical methods, the most optimal is the use of an extended Kalman filter
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Holm, Malin, Christoffer Roepstorff, and Martin Svedberg. "Validering av Inertial Measurment Units som insamlare av data för drivande av OpenSim-modell." Thesis, Uppsala universitet, Institutionen för teknikvetenskaper, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-175937.
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The purpose of this paper is to investigate the possibility of replacing data from highspeed filming (Qualisys motion capture) with data from Inertial Measurement Units (X-io technologies), when used to run a model of torso and pelvis in OpenSim. Qualisys motion capture data is used as the golden standard to validate the result visually and with Bland-Altman plots. In order to obtain comparable data experiments are conducted where both methods of collecting data are used simultaneously. Data from the IMU's then need to be processed in Matlab before it can be used to run the OpenSim modell. Several Matlab programs rotate the IMU data to a static reference frame, filter and integrate it, then create viritual markers that correspond to Qualisys' optical markers. The conclusion is that using IMU as a method for collecting data can replace Qualisys in some applications, but not in ones that require high precision. However, this paper only begins the examination of IMU's and there are most likely improvements to be made.
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Simone, Matthew James. "A Novel Method to Locate Targets Using Active Vision and Robotic Inertial Navigation Data." Thesis, Virginia Tech, 2006. http://hdl.handle.net/10919/32751.
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Unmanned vehicles are increasingly being used for mobile sensing missions. These missions can range from target acquisition to chemical and biological sensing. The reason why these vehicles are increasingly being used is because they can carry many different types of sensors and can function as a cheap platform for carrying these sensors. The sensing that will be explained in this thesis is target acquisition. Target acquisition is the act of locating the exact position of an â area of interest.â Currently this task can be completed with different types of complex range sensors. This thesis presents a type of target acquisition scheme for unmanned vehicles that will use a combination of cheap, simple vision sensors and robot inertial navigation data in order to accurately measure the location of a target in real world coordinates. This thesis will first develop an accurate waypoint driving algorithm that will either use dead reckoning or GPS/ compass sensors. We will then develop a robust target extraction algorithm that will be able to pick out a target in an image. After this is completed we will develop an algorithm that will be used to find the distance to the target from the robot. This algorithm will be based on a type of active vision system. Finally we will integrate all of these algorithms together in order to develop a target extraction technique that will be able to accurately find the distance to the target. With the distance we can then find the real world location of the target.Master of Science
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Lu, Fei, Kevin K. Lin, and Alexandre J. Chorin. "Data-based stochastic model reduction for the Kuramoto–Sivashinsky equation." ELSEVIER SCI LTD, 2017. http://hdl.handle.net/10150/622792.
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The problem of constructing data-based, predictive, reduced models for the Kuramoto–Sivashinsky equation is considered, under circumstances where one has observation data only for a small subset of the dynamical variables. Accurate prediction is achieved by developing a discrete-time stochastic reduced system, based on a NARMAX (Nonlinear Autoregressive Moving Average with eXogenous input) representation. The practical issue, with the NARMAX representation as with any other, is to identify an efficient structure, i.e., one with a small number of terms and coefficients. This is accomplished here by estimating coefficients for an approximate inertial form. The broader significance of the results is discussed.
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Tao, Yaqin. "Fusing visual and inertial data for human upper limb motion tracking in home-based rehabilitation." Thesis, University of Essex, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.486196.
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Human motion tracking and analysis is currently one of the most active topics in research community. It is driven by a wide range of application domains, such as motion capture for animation, human-computer interaction, security surveillance, and diagnostics for orthopaedic patients. This thesis aims to develop a motion tracking system to track and analyze the upper limb motion of patients who sustain a stroke, to allow rehabilitation exercise in a home environment without the need for the presence of physiotherapists. The first part of this work is focused on developing visual tracking methods for human motion, which should be accurate, cheap, fast and suitable for home based rehabilitation. A proposed method is colour belt based tracking, which makes use of the advantages of both marker and markerless tracking systems. 2D and 3D arm motion are tracked using monocular and stereo views respectively. Tracking performance is promising. The proposed visual tracking methods serve as fundamental units in the second part of this thesis.In the second part of this work, visual and inertial sensors are integrated into a motion tracking system to track human upper limb motion. By combining different sensors into a single system, this compe.nsates for any of their individual shortcomings, thereby improving the system performance. An Extended Kalman Filter (EKF) and. Particle Filter (PF) are used to fuse different data modalities from inertial and visual sensors. Their performances are compared and validated with a further comparison with the ground truth.
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Mahmoud, Mahmoud A. "The Monitoring of Linear Profiles and the Inertial Properties of Control Charts." Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/29544.
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The Phase I analysis of data when the quality of a process or product is characterized by a linear function is studied in this dissertation. It is assumed that each sample collected over time in the historical data set consists of several bivariate observations for which a simple linear regression model is appropriate, a situation common in calibration applications. Using a simulation study, the researcher compares the performance of some of the recommended approaches used to assess the stability of the process. Also in this dissertation, a method based on using indicator variables in a multiple regression model is proposed.
This dissertation also proposes a change point approach based on the segmented regression technique for testing the constancy of the regression parameters in a linear profile data set. The performance of the proposed change point method is compared to that of the most effective Phase I linear profile control chart approaches using a simulation study. The advantage of the proposed change point method over the existing methods is greatly improved detection of sustained step changes in the process parameters.
Any control chart that combines sample information over time, e.g., the cumulative sum (CUSUM) chart and the exponentially weighted moving average (EWMA) chart, has an ability to detect process changes that varies over time depending on the past data observed. The chart statistics can take values such that some shifts in the parameters of the underlying probability distribution of the quality characteristic are more difficult to detect. This is referred to as the "inertia problem" in the literature. This dissertation shows under realistic assumptions that the worst-case run length performance of control charts becomes as informative as the steady-state performance. Also this study proposes a simple new measure of the inertial properties of control charts, namely the signal resistance. The conclusions of this study support the recommendation that Shewhart limits should be used with EWMA charts, especially when the smoothing parameter is small. This study also shows that some charts proposed by Pignatiello and Runger (1990) and Domangue and Patch (1991) have serious disadvantages with respect to inertial properties.Ph. D.
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Bergeron, Alexandre. "Design and Development of a Marine Data Acquisition System for Inertial Measurement in Wind Powered Yachts." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23116.
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This thesis presents the design of an inertial measurement data acquisition system intended for use in sailboats. The variables of interest are 3-axis acceleration, 3-axis rotation, GPS position/velocity, magnetic compass bearing and wind speed/direction. The design focus is on low-cost micro-electromechanical systems (MEMS) based technology and demonstrating the validity of these technologies in a scientific application. A prototype is constructed and submitted to a series of tests to demonstrate functionality and soundness of the design. These tests range from bench tests to full scale application. Contributions of this thesis include the novel application of inertial measurement unit (IMU) technology to a sailboat racing application, the integration of all instrumentation, creative ruggedised packaging and emphasising the use of low-cost commercial off-the-shelf (COTS) technology.
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Spina, Davide. "Multi-sensor Data Fusion for Robotics Applications." Doctoral thesis, Università di Catania, 2015. http://hdl.handle.net/10761/1671.
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Thanks to faster and better integrated processing units, as well as increasingly miniaturized and precise sensors, Robotics is experiencing a period of significant development.
New technology is making robots increasingly more autonomous. Data from different sensors can be fused and processed in real time by on-board processing units in order to make the robot perform either more or less complicated tasks.
Unmanned Ground Vehicles (UGV) and Unmanned Aerial Vehicles (UAV) equipped with sensors and microprocessors/microcontrollers can be remotely piloted. They can also move autonomously with the help of different navigation and localization methods.
Power electronics is contributing to a transformation in many fields such as robotics, automotive and consumer devices.
Some new applications of power electronics are discussed in the first chapter of this thesis. One of these describes how new power electronics devices allow the use of distributed instead of centralized control in industrial robotics.
Multi-sensor data fusion theory is presented in the second chapter; the Kalman Filter and Particle Filter are described.
Inertial sensors and magnetometers are introduced in the third chapter with the description of a calibration procedure for each sensor.
Two new methods of multi-sensor data fusion, based on low-cost Micro Electro-Mechanical Systems (MEMS) Inertial Sensors, to estimate joint angles of industrial manipulators are described in the fourth chapter. The results of two experimental tests are also presented to evaluate and to compare the performances of the two methods.
A method to estimate the attitude and heading of an UAV is described in the fifth chapter. In order to check the performance of the developed method, at the end of the fifth chapter, a comparison test with a high accuracy system is presented.
A localization algorithm for a wheeled UGV equipped with a GPS and an inertial platform is described in the sixth chapter. Simulation tests and experimental results are also presented at the end of the sixth chapter.
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Malik, Zohaib Mansoor. "Design and implementation of temporal filtering and other data fusion algorithms to enhance the accuracy of a real time radio location tracking system." Thesis, Högskolan i Gävle, Avdelningen för elektronik, matematik och naturvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-13261.
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A general automotive navigation system is a satellite navigation system designed for use inautomobiles. It typically uses GPS to acquire position data to locate the user on a road in the unit's map database. However, due to recent improvements in the performance of small and lightweight micro-machined electromechanical systems (MEMS) inertial sensors have made the application of inertial techniques to such problems, possible. This has resulted in an increased interest in the topic of inertial navigation. In location tracking system, sensors are used either individually or in conjunction like in data fusion. However, still they remain noisy, and so there is a need to measure maximum data and then make an efficient system that can remove the noise from data and provide a better estimate. The task of this thesis work was to take data from two sensors, and use an estimation technique toprovide an accurate estimate of the true location. The proposed sensors were an accelerometer and a GPS device. This thesis however deals with using accelerometer sensor and using estimation scheme, Kalman filter. The thesis report presents an insight to both the proposed sensors and different estimation techniques. Within the scope of the work, the task was performed using simulation software Matlab. Kalman filter’s efficiency was examined using different noise levels.
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Rickenbach, Mark Douglas. "Correction of inertial navigation system drift errors for an autonomous land vehicle using optical radar terrain data." Thesis, Monterey, Calif. : Naval Postgraduate School, 1987. http://hdl.handle.net/10945/22225.
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Josses, Roxane. "Data Fusion between Inertial and Optical Sensors for Earth Observation Satellite Line of Sight Estimation and Stabilization." Thesis, KTH, Rymdteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299359.
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The line-of-sight (LoS) pointing and stability requirements of Earth observation satellites are becoming increasingly stringent. The microvibrations that disturb the LoS are therefore no longer negligible, and many studies are focusing on the estimation of these microvibrations and on mitigation strategies, on platform and payload levels. Disturbances of the LoS can be seen by image processing algorithms that provide high-frequency information. In this paper, a novel method is proposed to fuse these optical data with inertial data using a Kalman filter to obtain the best LoS estimation. To demonstrate the performances of this fusion, a simulation tool is developed on Matlab/Simulink and three estimators, corresponding to three image processing techniques (fixed scene, scrolling scene and scene tracking) are tested. The stabilization of the LoS is performed by adding a fast-steering mirror in the optic path of the telescope. Results indicate that the fusion with optical data enables to include in the LoS estimation the instrument motion, which can differ from the platform motion at high frequencies. Using this estimation, stabilization results are approaching the challenging pointing requirements.Siktlinjens (LoS) peknoggrannhet och stabilitetskrav för jordobservationssatelliter blir allt striktare. Mikrovibrationerna som stör LoS är därför inte längre försumbara, och många studier fokuserar på uppskattningen av dessa mikrovibrationer samt på strategier för att minska dessa, både plattforms- och nyttolastnivåerna. Störningar i LoS kan ses av bildbehandlingsalgoritmer som ger högfrekvent information. I detta arbete föreslås en ny metod för att slå samman optiska data med tröghetsdata med hjälp av ett Kalman-filter för att uppnå bästa LoS-uppskattning. För att visa prestandan för denna datasammanslagning utvecklades ett simuleringsverktyg i Matlab/Simulink och tre uppskattningsalgoritmer, motsvarande tre bildbehandlingstekniker (fast scen, rullningsbild och scenspårning), testades. Stabiliseringen av LoS utförs genom att lägga till en snabbspegel i teleskopets optiska väg. Resultaten visar att sammanslagningen med optisk data gör det möjligt att inkludera instrumentets rörelse i LoS-uppskattningen, som kan skilja sig från plattformens rörelse vid höga frekvenser. Med hjälp av denna uppskattning närmar sig stabiliseringsresultaten de utmanande pekkraven.
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Berlin, Eugen [Verfasser], Kristof Van [Akademischer Betreuer] Laerhoven, and Oliver [Akademischer Betreuer] Amft. "Early Abstraction of Inertial Sensor Data for Long-Term Deployments / Eugen Berlin. Betreuer: Kristof Van Laerhoven ; Oliver Amft." Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2014. http://d-nb.info/1110979444/34.
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Kautz, Thomas [Verfasser], Bjoern [Gutachter] Eskofier, and Peter [Gutachter] Husar. "Acquisition, Filtering and Analysis of Positional and Inertial Data in Sports / Thomas Kautz ; Gutachter: Bjoern Eskofier, Peter Husar." Erlangen : FAU University Press, 2017. http://d-nb.info/1144619084/34.
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Kautz, Thomas [Verfasser], Bjoern Gutachter] Eskofier, and Peter [Gutachter] [Husar. "Acquisition, Filtering and Analysis of Positional and Inertial Data in Sports / Thomas Kautz ; Gutachter: Bjoern Eskofier, Peter Husar." Erlangen : FAU University Press, 2017. http://nbn-resolving.de/urn:nbn:de:bvb:29-opus4-89527.
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Jarrell, Jason A. "Employ sensor fusion techniques for determining aircraft attitude and position information." Morgantown, W. Va. : [West Virginia University Libraries], 2008. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=5894.
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Thesis (M.S.)--West Virginia University, 2008.Title from document title page. Document formatted into pages; contains xii, 108, [9] p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 104-108).
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Kurebayashi, Shinya 1976. "Using Nuclear data and Monte-Carlo techniques to study areal density and mix in D² inertial confinement fusion implosions." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/29369.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Physics, 2004.Includes bibliographical references.
Measurements from three classes of direct-drive implosions at the OMEGA laser system [T. R. Boehly et al., Opt. Commun. 133, 495 (1997)] were combined with Monte-Carlo simulations to investigate models for determining hot-fuel areal density ([rho]Rhot) in compressed, D2-filled capsules, and to assess the impact of mix and other factors on the determination of pRhot. The results of the Monte-Carlo calculations were compared to predictions of commonly used models that use ratios of either secondary D3He proton yields or secondary DT neutron yields to primary DD neutron yields to provide estimates [rho]Rhot or [rho]Rhot,n, respectively, for pRhot. For the first class of implosions, where [rho]Rhot is low (=/< 3 mg/cm2), [rho]Rhot,p and [rho]Rhot,n often agree with each other and are often good estimates of the actual [rho]Rhot. For the second class of implosions, where [rho]Rhot is of order 10 mg/cm2, pRhot,p often underestimates the actual value due to secondary proton yield saturation. In addition, fuel-shell mix causes pRhot,p to further underestimate, and [Rho]Rhot,n to overestimate, [rho]Rhot. As a result, values of [Rho]Rhot,p and [Rho]Rhot,n can be interpreted as lower and upper limits, respectively. For the third class of implosions, involving cryogenic capsules, secondary protons and neutrons are produced mainly in the hot and cold fuel regions, respectively, and the effects of the mixing of hot and cold fuel must be taken into account when interpreting the values of [rho]Rhot,p and pRhot,n. From these data sets, we conclude that accurate inference of [rho]Rhot requires comprehensive measurements in combination with detailed modeling.
by Shinya Kurebayashi.
S.M.
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Sammon, Ryan. "Data Collection, Analysis, and Classification for the Development of a Sailing Performance Evaluation System." Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/25481.
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The work described in this thesis contributes to the development of a system to evaluate sailing performance. This work was motivated by the lack of tools available to evaluate sailing performance. The goal of the work presented is to detect and classify the turns of a sailing yacht. Data was collected using a BlackBerry PlayBook affixed to a J/24 sailing yacht. This data was manually annotated with three types of turn: tack, gybe, and mark rounding. This manually annotated data was used to train classification methods. Classification methods tested were multi-layer perceptrons (MLPs) of two sizes in various committees and nearest- neighbour search. Pre-processing algorithms tested were Kalman filtering, categorization using quantiles, and residual normalization. The best solution was found to be an averaged answer committee of small MLPs, with Kalman filtering and residual normalization performed on the input as pre-processing.
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Lugo, Rafael Andres. "Statistical Entry, Descent, and Landing Flight Reconstruction with Flush Air Data System Observations using Inertial Navigation and Monte Carlo Techniques." Thesis, North Carolina State University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3584008.
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A method is introduced to consider flush air data system (FADS) pressures using a technique based on inertial navigation to reconstruct the trajectory of an atmospheric entry vehicle. The approach augments the recently-developed Inertial Navigation Statistical Trajectory and Atmosphere Reconstruction (INSTAR), which is an extension of inertial navigation that provides statistical uncertainties by utilizing Monte Carlo dispersion techniques and is an alternative to traditional statistical approaches to entry, descent, and landing trajectory and atmosphere reconstruction.
The method is demonstrated using flight data from the Mars Science Laboratory (MSL) entry vehicle, which contained an inertial measurement unit and a flush air data system called the Mars Entry Atmospheric Data System (MEADS). An MSL trajectory and atmosphere solution that was updated using landing site location in INSTAR is first presented. This solution and corresponding uncertainties, which were obtained from Monte Carlo dispersions, are then used in a minimum variance algorithm to obtain aerodynamic estimates and uncertainties from the MEADS observations. MEADS-derived axial force coefficient and freestream density estimates and uncertainties are also derived from the minimum variance solutions independent of the axial force coefficients derived from computation fluid dynamics (CFD), which have relatively high a priori uncertainty. Results from probabilistic analyses of the solutions are also presented.
This dissertation also introduces a method to consider correlated CFD uncertainties in INSTAR. From a priori CFD uncertainties, CFD force and pressure coefficients are dispersed in a Monte Carlo sense and carried over into the reconstructions. An analysis of the subsequent effects on the trajectory, atmosphere, and aerodynamic estimates and statistics is presented.
Trajectory, atmospheric, and aerodynamic estimates compare favorably to extended Kalman filter solutions obtained by the MSL reconstruction team at NASA Langley Research Center. The uncertainties obtained through the methods from this work are generally smaller in magnitude because of assumptions made regarding sources of error in the MEADS pressure transducer uncertainties. Using data-derived uncertainties in the pressure measurement noise covariance results in aerodynamic parameter estimate uncertainties that are in better agreement with the uncertainties derived from the Monte Carlo dispersions. CFD database errors dominate the uncertainties of parameters derived from aerodatabase axial force coefficients.
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Shollenberger, Tara Krystyna. "Statistical Entry, Descent, and Landing Flight Reconstruction with Flush Air Data System Observations using Inertial Navigation and Monte Carlo Techniques." Thesis, North Carolina State University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3584009.
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Research suggests what leaders should do or the qualities or characteristics they should have to be ethical leaders (Brown & Treviño, 2006). The ethical decision-making process that leaders should follow to avoid scandals and unethical behavior are overlooked. Few studies focused on ethical decision-making within higher education. Yet, educational leaders have an ethical responsibility that may be even more complex than those of other leaders due in part to increasingly diverse student populations enrolled in higher education that is having an impact on the growth of educational institutions on a global basis (Shapiro & Stekfovich, 2011). Further, ethical scandals are no longer contained by national borders. The rapid growth of technology coupled with changes in political and societal landscapes has advanced ethical scandals to global prominence. A more collective need to understand ethical values and ethical decision-making practices on a global level has emerged. To be globally effective, leaders must be aware of the similarities and differences across and within cultures that could influence business practices (Resick, Hanges, Dickson, & Mitchelson, 2006). However, cross-cultural research has not yet addressed the topic of ethical decision-making. In this study, the ethical decision-making process of higher education was not only examined in the United Stated but also in Poland. This exploratory study used the Delphi research technique to identify an ethical decision-making definition that higher administration leaders in both the United States and Poland use to make ethical decisions and identify the environmental factors that influence their decisions. Findings showed that the United States and Polish expert panels were different and showed very little in common in the identification of a definition and environmental factors. Lastly, both sets of experts identified a new process for ethical decision-making, each constructing a different ethical decision-making process model. This research on ethical decision-making provided evidence that the Polish and United States cultures are not as similar as identified in previous studies in terms of how they identify ethical decision-making and the factors they identify with influencing ethical decision-making. Using this information will create a better understanding of the practices and approaches to ethics that leaders use because of the huge influence they have and exert on people within their own organization and society around them.
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Dill, Evan T. "Integration of 3D and 2D Imaging Data for Assured Navigation in Unknown Environments." Ohio University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1299616166.
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Rågmark, Johan. "Calibration and Evaluation of Inertial Navigation with Zero Velocity Update for Industrial Fastening Tools." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-298025.
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Indoor Positional Navigation (IPN) systems can be used to track the position of tools in factories which is crucial for quality assurance in many manufacturing industries. Inertial navigation is rarely used on its own because of the noisy Inertial Measurement Unit (IMU) sensors which contribute to large drift. Current IPN systems usually involve the installation and calibration of cameras or antennas, so achieving sufficient accuracy with inertial navigation based IPN would be very desirable. This project aims to evaluate an inertial navigation algorithm, based on Zero Velocity Update (ZUPT), for bolt level positioning by repeatability tests using an industrial robot. The ZUPT algorithm, developed at Atlas Copco, manages to effectively reduce drift and achieve moderate accuracy in position for simpler movements. The gravity tracking Kalman filter dictates the systematic errors in position that grow large with increased degree and dimension of rotation. When keeping rotations within 45◦ for a linear movement the absolute error in position is under 10%. Frequent stops are important when moving in a more complex trajectory to be able to negate drift, consequently detecting the start and stop of motion is crucial. The results show that increased frequency will improve accuracy. It is shown that averaging IMU samples before calculations can increase both truthfulness and precision by 10−25%, if sampling the IMU faster than the calculations. The ZUPT approach of inertial navigation will never yield positional results in real time, and the evaluated algorithm only performs well within certain limitations, mainly frequent stops and simple movements. Despite these limitations there is potential in using the algorithm for quality assurance purposes in hand held industrial fasteners.Kvalitetssäkring är en central fråga för många tillverkningsindustrier, så som flygplans- och bilindustrin, där det är avgörande att varje förband har dragits åt på rätt sätt för att garantera säkerheten i produkten. Moderna fabriker har centrala styrsystem som kommunicerar med maskiner och verktyg, och ifall något blir fel är det vanligt att fabrikslinan stannar vilket blir kostsamt. Inomhuspositionering (IPS) av hög noggrannhet kan spåra vilken åtdragning som blivit fel, vilket dokumenteras och åtgärdas om möjligt senare, utan att stanna fabrikslinan. Dagens noggranna IPS system för kvalitetssäkring kräver installation och kalibrering av kameror och/eller antenner. Tröghetsnavigering kräver i grunden bara billiga sensorer installerade på verktyget men metoden är mycket opålitlig på grund av sensorernas opålitlighet och brus. I detta projekt har en metod för tröghetsnavigering, användandes Zero Velocity Update (ZUPT), evaluerats för kvalitetssäkring av handhållna verktyg genom repetabilitetstester. Tröghetsnavigeringsalgoritmen som tidigare utvecklats på Atlas Copco lyckas på effektivt sätt reducera drift och uppnår rimlig noggranhet för enklare rörelser. För linjära rörelser med rotationer under 45◦ så erhålls ett absolut positionsfel inom 10%. För att fungera väl även för mer komplexa rörelser krävs frekventa stop, och noggrann rörelsedetektion är central. Denna ZUPT-metod kommer aldrig att kunna generera position i realtid och algoritmen presterar väl endast inom vissa begränsningar. Trots detta så finns god potential för metoden inom kvalitetssäkring för handhållna industriverktyg.
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Hult, Axel, and Chang Daniel Munguia. "Smartphone Acquisition and Online Visualization of IMU and EMG Sensor Data for Assessment of Wrist Load." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231304.
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Work-related musculoskeletal disorders constitutes a substantial burden for society, generating individual suffering and financial costs. Quantifying the musculoskeletal stress and establishing exposure-response relationships is an important step in facing this problem. Observational methods for assessing exposure in the field of ergonomics have shown poor results, and the technical measurement methods that exists are often complicated to use which limits their scope to scientific purposes. This work describes the development of a prototype measurement system aimed to simplify ambulatory measurements of musculoskeletal load, specifically aimed at the wrist and hand. Wearable sensors including Inertial Measurement Units (IMU:s) and Electromyography (EMG) were connected to a smartphone and used for measuring wrist movement and forearm muscle activity. Data sampled in the smartphone was stored online in a cloud database, and a webapplication was developed to visualize work-load exposure. Testing under controlled conditions indicated that muscular rest can be measured and classified according to suggested risk thresholds. Accurate angular measurements were difficult to implement because of lacking inter-sensor alignment in the horizontal plane, as well as uncertainties in the Bluetooth protocol. Future work should focus on the IMU:s and look to further develop a method of correcting the relative angle error, as well as investigating accurate time synchronization of the two sensors.Alternatively, deriving angular velocities directly from the IMU gyroscopes could be investigated.
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Gray, Robert A. "Inflight detection of errors for enhanced aircraft flight safety and vertical accuracy improvement using digital terrain elevation data with an inertial navigation system, global positioning system and radar altimeter." Ohio University / OhioLINK, 1999. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1181161513.
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Souček, Václav. "Geografické informační systémy v dopravě." Doctoral thesis, Vysoké učení technické v Brně. Fakulta stavební, 2014. http://www.nusl.cz/ntk/nusl-233824.
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The work is focused on the issues associated with the use of geographical information systems in transport. Of the various types of transport was chosen railway transport for its great potential particularly in the field of freight transport, but also because it is a relatively environmentally friendly. This fact is also well known to the leaders of the European Union, who are engaged in the field of transportation. The European Commission in its documents (green and white papers) gives accent on the development of railway transportation and combined transportation, because this is the path to secure the sustainable development of transport. In the course of this study the current state of information systems several problems were discovered. One problem is the fragmentation of the partial information systems and the associated strong administrative burden. This situation stems both from the incomplete legislative framework, but also from the lack of the concept and awareness of the managerial positions. This work deals with other selected issues. The first is the area of designing the data model topology track that satisfies the requirements set out in legislation, both European and national level. The data model was designed with regard to a sufficient degree of variability. The work contains a section dedicated to the implementation of the data model and solution design of problems associated with visualization arcs. Another area is the collection of geographic data. Data collection is one of the key tasks in the implementation and maintenance of the information system. The acquisition of the geographical data can be lengthy and costly. We therefore suggest how to use inertial measurement in acquisition of topological data. This method could speed up the entire process of data capturing with sufficient precision and reduce the costs to the acceptable range.
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Roberts, Iris P., and Thomas P. Hancock. "GPS TEST RANGE MISSION PLANNING." International Foundation for Telemetering, 1990. http://hdl.handle.net/10150/613801.
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International Telemetering Conference Proceedings / October 29-November 02, 1990 / Riviera Hotel and Convention Center, Las Vegas, NevadaTASC is currently developing for the GPS Range Applications Joint Program Office (RAJPO) the mission planner which will be used by test ranges procuring RAJPOdeveloped GPS test range instrumentation. Test Range User Mission Planner (TRUMP) is a user-friendly, PC-resident tool which aids in deploying and utilizing GPS-based test range assets. In addition to providing satellite/jammer visibility (for a Digital Terrain Elevation Data (DTED) range map) and dilution-of-precision (DOP) information, TRUMP features: C Time history plots of time-space-position information (TSPI) C Performance based on a dynamic GPS/inertial system simulation C Time history plots of TSPI data link connectivity C DTED maps with user-defined cultural features C Two-dimensional coverage plots of ground-based test range assets. This paper will discuss TRUMP’s role on the test ranges and its current features. In addition, the functionality to be added during the next development phase will be presented.
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McIntyre, David S. "GPS effective data rate optimization with applications to integrated GPS/INS attitude and heading determination." Ohio : Ohio University, 1989. http://www.ohiolink.edu/etd/view.cgi?ohiou1182445154.
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Simón, Colomar David, John-Olof Nilsson, and Peter Händel. "Smoothing for ZUPT-aided INSs." KTH, Signalbehandling, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-107414.
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Due to the recursive and integrative nature of zero-velocity-update-aided (ZUPT-aided) inertial navigation systems (INSs), the error covariance increases throughout each ZUPT-less period followed by a drastic decrease and large state estimate corrections as soon as ZUPTs are applied. For dead-reckoning with foot-mounted inertial sensors, this gives undesirable discontinuities in the estimated trajectory at the end of each step. However, for many applications, some degree of lag can be tolerated and the information provided by the ZUPTs at the end of a step can be made available throughout the step, eliminating the discontinuities. For this purpose, we propose a smoothing algorithm for ZUPT-aided INSs. For near real-time applications, smoothing is applied to the data in a step-wise manner requiring a suggested varying-lag segmentation rule. For complete off-line processing, full data set smoothing is examined. Finally, the consequences and impact of smoothing are analyzed and quantified based on real-data.QC 20130114
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Bruno, Carlo. "Developing methods and algorithms of sensor fusion by IMUs applied to service robotics." Doctoral thesis, Università di Catania, 2012. http://hdl.handle.net/10761/1076.
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The importance of research in Inertial Navigation Systems (INS) has been growing in recent years. Usually the IMU is used in inertial navigation, such as UAV, AGV, AUV, but it is also used in games, human movement reconstruction (the use of sensors in the studies of human movement is now quickly gaining importance as a promising alternative to video capture systems laboratories), entertainment, etc. Often IMU is used in association with GPS or other sensors to estimate trajectory or for navigation as well as localization. In literature, there are many examples using Kalman Filter or EKF for this aim. It can also be considered to use the implementation of an algorithm in the use of the robot. Moreover, when speaking about an inertial platform there is also a Kalman Filter as a good algorithm providing good results.
The work described concerned the development of systems and algorithms, or new approaches to existing systems to bring robotics to everyday life and to lower costs of implementation of certain devices in industrial processes, or to review some progresses in the light of improvement of technology.
We used the IMUs (Inertial Measurement Unit) and MEMS devices such as accelerometers, gyroscopes, but also temperature and pressure sensors for localization and navigation. Through the use of more accurate sensors and to the growing potential of the new microcontrollers, we have been able to implement algorithms to process and filter data the more quickly and with fewer steps and in some cases to be able to find good solutions at the expense of precision, but in the interest of processing speed.
These sensors have been designed as an aid to existing sensors or for new applications such as three-dimensional localization in a building using the pressure or for safety, in industry, eg for the monitoring of movements of a robotic arm.
Finally, since usually the inertial navigation uses GPS data to correct inertial data, this excludes the GPS spoofing; in other words that someone deliberately alters the signal in such a way that it provides the same values specifically wrong to hack satellite systems installed in the cars.
The IMU used in this work is the iNEMO board, an inertial measurement unit developed by STMicroelectronics. It runs a sophisticated sensor fusion algorithm (attitude heading reference system) to provide static and dynamic orientation and inertial measurements. This 10-DOF inertial system integrates five different sensors and has a size of 4x4 cm.
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Waqar, Adnan. "Enhancing the capabilities of electronic performance tracking system for applications in sports." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2022. https://ro.ecu.edu.au/theses/2562.
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The success of electronic technologies has sparked interest in sports amongst coaches, athletes and sports scientists. Consequently, the sporting world has witnessed a rapid rise in sports technologies in recent years. In sports, technologies can assist in a variety of ways, ranging from winner selection to athlete injury prevention. In recent years, wearable technologies have become popular in sports. Wearable microtechnology devices, commonly known as electronic performance tracking system (EPTS) in sports, can be used to monitor and improve an athlete's performance. EPTSs can also play an important role in injury prevention. This thesis investigates the performance of wearable EPTSs and presents solutions to improve the accuracy of EPTSs in sports.
For an EPTS to capture and accurately quantify important athlete-related parameters, such as speed, distance covered, number and intensity of sprints, change of direction (COD), and positioning and movement, data is of vital importance. Whilst satellite-based positioning systems require a relatively short setup time, their accuracy and reliability are often low. Wearable inertial sensors may be able to track an athlete's movements, but they can also be noisy and their error accumulates over time. Consequently, designing an accurate and wearable EPTS is a complex task and requires critical investigation. This featured as the key motivation for this research, whose findings are presented in this thesis.
In this thesis, a new ultra-wide band (UWB)-based positioning system is proposed to increase the accuracy of an EPTS in indoor sports. A close analysis of real-world experiments is presented, and limitations associated with the UWB-based positioning systems are highlighted. In forming an economical hardware solution, geometric and machine learning algorithms are introduced. The accuracy of the developed solution is compared against conventional positioning systems. To mitigate errors in UWB-based indoor positioning systems, a range error reduction technique is introduced. The optimal hardware setup and complexity for implementing the proposed positioning solution are also discussed.
In order to track an athlete's movements using real-world data, a multi-sensor data fusion approach is introduced for measuring/tracking athletes' change of direction (COD) detection and quantification. This COD data is then used to reduce divergence errors incurred in state estimation-based particle filter algorithms. The developed solution achieves significant improvements as compared to existing techniques. Overall, the proposed EPTS solution offers higher accuracy in tracking an athlete's position and movement data. Further, the proposed solution enables the use of EPTS in indoor environments.
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Taia, Alaoui Fadoua. "Navigation des personnes aux moyens des technologies des smartphones et des données d’environnements cartographiés." Thesis, Ecole centrale de Nantes, 2018. http://www.theses.fr/2018ECDN0051/document.
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La navigation inertielle grâce aux capteurs intégrés dans les smartphones permet d’assurer une géolocalisation continue même en absence de signal GNSS. Ces capteurs bas coût délivrent néanmoins des mesures bruitées qui engendrent une dérive de la trajectoire. La technique PDR qui est une technique de navigation inertielle par détection de pas souffre de deux limites principales. La première est l’estimation de la longueur de pas car cette dernière dépend des caractéristiques physiques de chaque utilisateur, et la seconde est le résultat d’une dérive angulaire combinée avec un biais lié au portage du capteur à la main. Dans le contexte du projet HAPPYHAND, ce travail s’intéresse à l’exploitation de la carte pour corriger ces différentes erreurs. Un réseau de navigation topologique est exploité pour corriger à la fois les erreurs angulaires et calibrer le modèle de longueur de pas. Ce modèle est ensuite augmenté par un processus de mise à jour de position par détection de points d’intérêtSmartphone navigation using the low-cost embedded sensors in off the shelf smartphones can provide a continuous solution in GNSS-denied environments. The most widely adopted approach is Pedestrian Dead Reckoning (PDR) that uses acceleration and angular velocity to estimate the user’s position. Yet, consumer grade sensors deliver noisy measurements that may result into a drift in the estimated trajectory. One major challenge is to estimate accurately step length information since it depends on physiological features that are specific to each user. In addition, angular biases are more likely to be introduced in the orientation estimation process with handheld devices. This is mainly due to the high degree of freedom of hand motion. In the context of a national project called HAPPYHAND, the main goal of this work is to exploit map information as far as possible in order to mitigate the previous inherent limitations to the PDR approach. First, a topological network extracted from the map is proposed in order to correct the angular errors and calibrate the step length model. Second, context awareness is adopted in order to provide regular and frequent position updates thanks to a point of interest online detection scheme
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Broman, Simon, and André Franzén. "Analys av accelerometerdata för identifiering av träffpunkt och mätning av resulterande vibrationer i padelrack." Thesis, KTH, Hälsoinformatik och logistik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-296609.
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Syftet med att mäta vibrationer och rekyler i ett padelrack i detta arbete är att utveckla en prototyp som kan användas som träningsredskap för att minska risken för skador. En vanlig skada som drabbar padelspelare är tennisarmbåge, som enligt studier tros uppkomma genom upprepad exponering av mikrotrauman som vibrationer och rekyler. Genom att utföra en litteraturstudie i ämnet har systemkrav för ett sensorbaserat system definierats. Systemet som mäter vibrationer och rekyler har monterats i handtaget på padelracket. Två olika testmiljöer har utvecklats för att möjliggöra kontrollerade tester. För att identifiera och analysera slag använder systemet frekvensanalyser, korrelationstester och positionsförändring. Vid utveckling av metoden för identifiering av träffpunkt delades racket upp i fem olika zoner. Resultatet indikerar att träffar i två av zonerna ger upphov till mindre mängd vibrationer jämfört med de övriga zonerna. Resultatet för identifiering av träffzon varierar mellan testmiljöerna och enbart identifiering av en zon kan anses vara fungerande i båda fallen. Systemet identifierade träffzonen korrekt i 18 av 25 slag i den ena testmiljön och 9 av 25 i den andra. För att förbättra identifieringen av träffzon behövs flera analyser och korrelationtester utformas. En slutsats för det här examensarbetet är att det här arbetet kan användas som grund för vidare utveckling av ett sensorbaserat system för att identifiera träffzonen och kvantifiera vibrationer i ett padelrack.The purpose of measuring vibrations and recoils in a padel racket in this thesis is to develop a prototype that can be used as a training equipment to reduce the risk of injury. A common injury for padel players is tennis elbow, studies show that the cause of this injury are microtraumas from vibrations and recoils. Through a literature study in the subject, system demands for a sensor-based system have been defined. The system that has been used to measure vibrations and recoils have been attached to the bottom of the handle on the padel racket. To achieve controlled tests two different test environments have been developed. To identify and analyze impacts the system utilizes frequency analysis, correlation tests and displacement tracking. For identification of the impact area the racket was divided into five zones. The result indicates, that two of the impact zones generate less vibrations than the others. The result also shows that identification of impact zone varies between the test environments and that only the sweet spot can be identified in both cases. The system identified the impact zone correctly in 18 out of 25 strokes in one test environment and 9 out of 25 in the other. To further improve the methods for identification of the impact zone more analyses and correlations tests are required. One conclusion for this thesis is that it can be used as a platform for further development of a sensor-based system that can correctly identify impacts in all zones and quantify the resulting vibrations.
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Rehbinder, Henrik. "State Estimation and Limited Communication Control for Nonlinear Robotic Systems." Doctoral thesis, KTH, Mathematics, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3250.
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Pálenská, Markéta. "Návrh algoritmu pro fúzi dat navigačních systémů GPS a INS." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2013. http://www.nusl.cz/ntk/nusl-230495.
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Diplomová práce se zabývá návrhem algoritmu rozšířeného Kalmanova filtru, který integruje data z inerciálního navigačního systému (INS) a globálního polohovacího systému (GPS). Součástí algoritmu je i samotná mechanizace INS, určující na základě dat z akcelerometrů a gyroskopů údaje o rychlosti, zeměpisné pozici a polohových úhlech letadla. Vzhledem k rychlému nárůstu chybovosti INS je výstup korigován hodnotami rychlosti a pozice získané z GPS. Výsledný algoritmus je implementován v prostředí Simulink. Součástí práce je odvození jednotlivých stavových matic rozšířeného Kalmanova filtru.
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Harshe, Mandar. "Analyse et conception d'un système de rééducation de membres inférieurs reposant sur un robot parallèle à câbles." Phd thesis, Ecole Nationale Supérieure des Mines de Paris, 2012. http://pastel.archives-ouvertes.fr/pastel-00933732.
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L'analyse de la marche et la mesure du déplacements des articulations humaines ont été largement étudiées. Les artefacts de tissus "mous" sont une source fréquente d'erreur pour la plupart des méthodes de mesure utilisées. La procédure standard en analyse de la marche consiste à utiliser une combinaison de mesures pour l'estimation efficace des angles articulaires et de la position des segments du corps humain. Ce travail propose le développement d'un système d'analyse de la marche reposant sur un robot parallèle à câbles équipé de plusieurs capteurs mesurant spécifiquement les déplacements du genou. Nous considérons le cas général pour lequel les articulations humaines se comportent comme des joints à 6 degrés de liberté reliant deux segments du corps. Afin de déterminer la position et l'orientation de ces segments, 14 câbles y sont attachés, ce qui permet de considérer ces segments comme les organes effecteurs de robots parallèles. Leur position peut alors être calculée à partir de la mesure de la longueur des câbles. Cependant, ces mesures sont entachées de bruit à cause des artefacts de tissus "mous". Afin d'améliorer la précision des résultats, le système propose aussi l'utilisation d'autres capteurs de nature différente : plusieurs capteurs inertiels (avec accéléromètres et gyroscopes), un système de motion capture, des capteurs de pression plantaire, des capteurs de distance (IR et résistance variable) et des capteurs de force pour mesurer la contraction musculaire. Plusieurs approches globales sont disponibles pour l'analyse du genou lors de la marche. Les choix technologiques effectués impactent directement sur la conception de notre système et imposent le développement de matériel spécifique pour mener à bien les mesures, tel que le collier flexible utilisé d'une part pour permettre l'attache des câbles sur les segments du patient et d'autres part pour supporter les capteurs supplémentaires. Nous traitons le collier comme une chaîne cinématique sérielle et nous proposons une méthode d'étalonnage qui ne nécessite pas d'utiliser les mesures angulaires des articulations contrairement aux méthodes existantes. Nous décrivons le protocole expérimental ainsi que les méthodes utilisées pour synchroniser les données issues de plusieurs ordinateurs. Les données sont ensuite fusionnées pour obtenir la pose du collier et donc celle des segments du patient. Enfin, ce travail permet d'identifier les modifications à apporter au système pour une meilleure analyse de la marche, ce qui pourra servir de base à un système de rééducation complet.
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Leite, José Roberto Bairão. "Oscilações inerciais sobre a plataforma continental Sudeste do Brasil." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/21/21135/tde-26112014-165554/.
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Variações temporais na tensão de cisalhamento do vento, na Plataforma Continental Sudeste do Brasil (PCSE), perturbam o equilíbrio geostrófico gerando movimentos com frequências próximas à inercial local. Estas perturbações se propagam horizontalmente e verticalmente, interagindo com o fluxo médio e alterando as características hidrográficas e hidrodinâmicas. Foram analisados dados observacionais de corrente, registrados por correntógrafos fundeados às isóbatas de 50 m e 100 m, ao largo de Arraial do Cabo (RJ) e Ubatuba (SP), de vento registrados por bóias meteorológicas e de salinidade e temperatura perfilados em função da profundidade em estações hidrográficas, obtidos no âmbito do Projeto DEPROAS (Dinâmica do Ecossistema de Plataforma da Região Oeste do Atlântico Sul), entre 2001 e 2002. Os resultados das análises indicaram que a média de duração dos eventos de oscilações inerciais é 7,5 dias com desvio padrão de 3,8 dias, sendo 6,8 o número médio de oscilações em cada evento (desvio padrão de 3,3 oscilações). O período inercial efetivo médio foi calculado em 26,5 h com deslocamento médio da frequência inercial em 12,2%, devido ao desvio Doppler causado pelas interações com a vorticidade relativa do fluxo básico. As correntes inerciais horizontais, filtradas a partir das séries correntográficas, apresentaram valores entre 3 e 10 cm/s. Foi observada propagação vertical das oscilações inerciais e calculado o valor da velocidade de grupo vertical em -2,59 .10-2 cm.s-1. A partir desse resultado, foi obtido o valor de 28,3 m de profundidade para o valor máximo de velocidade vertical das partículas de água na onda interna inercial forçada pela oscilação das isotermas, em acordo com resultados observados de máxima corrente inercial logo abaixo da camada de mistura. O valor calculado para a amplitude da oscilação vertical das isotermas foi 17,2 m, próximo aos 19 m registrado com os resultados observacionais em períodos de mudança do campo de ventos. O modelo numérico hidrodinâmico ROMS (Regional Ocean Modelling System) comprovou resultados observacionais em relação à capacidade de mudanças na tensão de cisalhamento do vento, em períodos menores que o inercial local, gerarem oscilações inerciais. Os resultados numéricos com o ROMS permitiram analisar a interação das oscilações inerciais com o fluxo médio em diferentes regiões da PCSE, através de diferentes condições de estratificação da coluna de água e, a partir da trajetória de pseudoderivadores, estimar os raios das trajetórias com ordem 10 km.Temporal variations in the wind stress, on the South Brazil Bight, disturb the geostrophic equilibrium and generate motion with near inertial frequencies. The disturbances propagate horizontally and vertically, interacting with the basic motions and altering the hydrodynamics and hydrographic characteristics. Observational data of currents, collected by currentmeters deployed in the 50 m and 100 m isobaths, offshore Arraial do Cabo (RJ) and Ubatuba (SP), of winds collected in meteorological buoys and of salinity and temperature vertically profiled in hydrographic stations, during the project DEPROAS (Dinâmica do Ecossistema de Plataforma da Região Oeste do Atlântico Sul), in the years of 2001 and 2002, have been analyzed. Results showed that the mean duration of the inertial oscillations events is 7.5 days, with standard deviation of 3.8 days, being 6.8 the mean number of oscillations in each event (standard deviation of 3.3 oscillations). The calculated mean effective inertial period is 26.5 h, with a mean difference of the local inertial frequency of 12.2% due to the Doppler shift caused by interactions with the relative vorticity of the basic flow. The horizontal inertial currents, filtered from the current time series, presented values between 3 and 10 cm/s. Vertical propagation of the inertial oscillations were observed and the calculated value for the vertical group velocity was -2.59 . 10-2 cm/s. From these results, the calculated value for the depth of maximum water vertical velocity was 28.3 m for the internal inertial wave forced by the isotherms oscillations, in accordance with results observed of maximum vertical velocities occurring below the mixing layer. The calculated value for the amplitude of vertical oscillations of isotherms was 17.2 m, approximately equal to the 19 m observed in the data set during periods of wind shift. The numerical hydrodynamical model ROMS (Regional Ocean Modeling System) confirmed the observational results that changes in the wind field with periods smaller than the local inertial period generate inertial oscillations. The numerical results with ROMS allowed to analyze the interaction between the inertial oscillations and the basic flow in different regions of the South Brazil Bight, due to vertical different stratification characteristics of the sea water, and from the trajectories of pseudo-drifters it was possible to estimate the radius of the trajectories as having order of magnitude of 10 km.
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Bommakanti, Hemanth Ram Kartik. "Impact of Time Synchronization Accuracy in Integrated Navigation Systems." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-260239.
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Global Navigation Satellite System/Inertial Measurement Unit (GNSS/IMU) Integrated Navigation Systems (INS) integrate the positive features of GNSS and IMU for optimal navigation guidance in high accuracy outdoor navigation systems, for example using Extended Kalman Filter (EKF) techniques. Time synchronization of IMU data with precise GNSS based time is necessary to accurately synchronize the two systems. This must be done in real-time for time sensitive navigation applications such as autonomous vehicles. The research is done in two parts. The first part is the simulation of inaccurate time-stamping in a single axis of nonlinear input data in a gyroscope and an accelerometer, to obtain the timing error value that is tolerable by a high accuracy GNSS/INS system. The second part is the creation of a real-time algorithm using an STM32 embedded system enabled with FreeRTOS real-time kernel for a GNSS receiver and antenna, along with an IMU sensor. A comparative analysis of the time synchronized system and an unsynchronized system is done based on the errors produced using gyroscope and accelerometer readings along a single axis from the IMU sensor, by conducting static and rotational tests on a revolving chair.The simulation concludes that a high accuracy GNSS/INS system can tolerate a timing error of up to 1 millisecond. The real-time solution provides IMU data paired with updated GNSS based time-stamps every 5 milliseconds. The timing jitter is reduced to a range of ±1 millisecond. Analysis of final angular rotation error and final position error from gyroscope and accelerometer readings respectively, indicate that the real-time algorithm produces a reduction in errors when the system is static, but there is no statistical evidence showing the reduction of errors from the results of the rotational tests.GNSS / IMU integrerade navigationssystem kombinerar de positiva egenskaperna hos GNSS och IMU för optimal prestanda i noggranna navigationssystem. Detta görs med hjälp av sensorfusion, till exempel EKF. Tidssynkronisering av IMU-data med exakt GNSS-baserad tid är nödvändigt för att noggrant synkronisera de två systemen. Detta måste göras i realtid för tidskänsliga navigationsapplikationer såsom autonoma fordon. Forskningen görs i två delar. Den första delen är simulering av icke-linjär rörelse i en axel med felaktig tidsstämpling hos ett gyroskop och en accelerometer. Detta görs för att erhålla det högsta tidsfel som är acceptabelt hos ett GNSS / INS-system med hög noggrannhet. Den andra delen är skapandet av en realtidsalgoritm med ett inbyggt STM32-system med FreeRTOS som realtidskärna för en GNSSmottagare och antenn, tillsammans med en IMU-sensor. En jämförande analys av det tidssynkroniserade systemet mot ett osynkroniserat system görs baserat på de positionsfel längs en axel som produceras av gyroskopoch accelerometermätningar. Detta görs genom att utföra statiska och roterande tester med hjälp av en roterande stol.Simuleringen visar att ett noggrant GNSS / INS-system tolererar ett tidsfel på upp till 1 millisekund. Realtidslösningen ger IMU-data med tidsstämplar synkroniserade med GNSS-tid var femte millisekund. Tidsjittret reduceras till ett intervall mellan ± 1 millisekund. Analysen av det slutliga vinkelrotationsfelet och positionsfelet från gyroskopoch accelerometermätningar indikerar att realtidsalgoritmen ger ett lägre fel när systemet är statiskt. Det finns dock inga statistiska bevis för förbättringen från resultaten av rotationstesterna.