Most mobile video-recording devices of today, e.g. cell phones and music players, make use of a rolling shutter camera. A rolling shutter camera captures video by recording every frame line-by-line from top to bottom of the image, leading to image distortions in situations where either the device or the target is moving. Recording video by hand also leads to visible frame-to-frame jitter. In this thesis, methods to decrease distortion caused by the motion of a video-recording device with a rolling shutter camera are presented. The methods are based on estimating the orientation of the camera from gyroscope and accelerometer measurements. The algorithms are implemented on the iPod Touch 4, and the resulting videos are compared to those of competing stabilization software, both commercial and free, in a series of blind experiments. The results from this user study shows that the methods presented in the thesis perform equal to or better than the others. / Mobiltelefoner, mp3-spelare och andra bärbara enheter som kan spela in film har ofta en kamera med rullande slutare. En sådan kamera fångar varje bild rad för rad, från topp till botten. Detta resulterar i distortion i bilden om antingen enheten eller objekt i bilden rör sig. Att filma för hand introducerar också skakighet i filmen. I det här examensarbetet presenteras metoder för att minska den distortion som uppstår till följd av att en enhet med rullande slutare förflyttas under inspelning av en film. Metoderna bygger på estimering av kamerans orientering, utgående från mätdata från gyroskop och accelerometer. Algoritmerna har implementerats på en iPod Touch 4 och de resulterande filmerna har jämförts med de från konkurrerande program i en serie blindtester. Resultaten från denna undersökning visar att metoderna som presenteras i examensarbetet är lika bra eller bättre än de övriga.

Este trabalho apresenta o estudo e a implementação de um sistema de navegação em tempo-real utilizado para estimar a posição, a velocidade e a atitude de um veículo submarino autônomo. O algoritmo investigado é o do Filtro de Kalman Estendido. Este filtro é freqüentemente usado para realizar a fusão de dados obtidos de diferentes sensores, em uma estimativa estatisticamente ótima, quando se respeita algumas condições. Neste trabalho, fez se a fusão entre os seguintes sensores: unidade de navegação inercial do tipo strapdown, sensor acústico de posicionamento, profundímetro, sensor de velocidade de efeito Doppler e uma bússola. Para a aplicação embarcada do Filtro de Kalman, faz-se necessário o seu desenvolvimento em tempo real. Conseqüentemente, este trabalho apresenta o estudo das principais características de um sistema de tempo real. Para desenvolver o código em C utilizou-se de algumas funções do Matlab com a finalidade de se tentar minimizar os erros de implementação do filtro. Além disto, para facilitar a implementação e respeitar os critérios de sistemas de tempo real utilizou-se de um sistema operacional, C/OS-II que possibilita aplicar sistemas com multiprocessos e utilizar semáforos para o gerenciamento do EKF, além disto, foram utilizadas normas de programação, MISRAC, para padronizar o código e aumentar a sua confiabilidade. São apresentadas também a modelagem cinemática, a metodologia e as ferramentas computacionais utilizadas para o filtro. Com base nas simulações e nos ensaios de campo executados on-line, observou-se que os filtros projetados para se estimar a atitude e a posição do veículo obtiveram bons desempenhos, além disto, foi possível verificar a convergência dos EKFs. Para estas simulações e ensaios, foram também estudados casos de situações adversas como, por exemplo, uma falha no sensor de referência de posição, sendo que para esta situação, o EKF de posição e velocidade obteve resultados satisfatórios. / This paper presents the study and implementation of a real-time navigation system used to estimate the position, velocity and attitude of an autonomous underwater vehicle. The Extended Kalman Filter, EKF, was adopted. This filter is often used to perform the data fusion from different sensors, in generating a statistically optimal estimate when some required conditions are fulfilled. The algorithm implements the fusion of the following sensors: an inertial navigation unit sensor (strapdown type), an acoustic positioning, a depth gauge, a Doppler velocity log sensor and a magnetic compass. This work presents the kinematic modelling, the methodology and computational tools used for developing the EKF algorithm. In order to integrate the EKF into an embedded system, it is necessary to develop it in real time. It was adopted the C / OS-II operational system, which allows to implement multithreaded systems and use traffic lights to manage the EKF. Furthermore, programming standards, such as MISRA C, was chosen to standardize the code and increase its reliability. The C code implementation took advantage of some Matlab functions to minimize implementation errors. Based on simulations and field tests carried out online, it was concluded that the filters designed to estimate the attitude and position of the vehicle provided good performances, in addition, it was possible to verify the EKFs convergence. The filters were tested in same adverse situations, e.g., a fault in the position reference sensor, providing satisfactory results as well.

This thesis deals with inertial navigation systems issues. It describes basics of reference frames, coordinate systems and matrix calculations for AHRS. There are also basic information about inertial sensors, inertial measurements units and its mistakes. One of the purposes of this paper could be explanation of inertial navigation systems terms. The main object of this thesis is to explore the influence of using multiple sensors of same type to enhance measurements of AHRS systems.

The goal of this diploma thesis is a proposal of autonomous two wheeled balancing robot, differentially driven. This kind of robot is especially suitable in confined space, where it can utilize its maneuver skills. Many criteria as operational conditions, materials, size and weight of the robot, suitable hardware and sensors must to be considered, when designing the robot. Development and implementation of autonomous balancing control system is also part of the thesis.

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.

Si les neurosciences connaissent d’importants progrès dans l’imagerie et le génotypage, le phénotypage repose encore largement sur des échelles visuelles. Le phénotype chez l’homme repose principalement sur son style perceptivo-moteur qui donne une empreinte à la marche, la posture, l’équilibre, l’habilité des membres supérieurs, les mouvements oculaires etc. La marche, fonction complexe et fondamentale de l’être humain, implique l’ensemble du système musculo-squelettique, le système nerveux central et périphérique ainsi que les organes sensoriels. Elle est le produit d’un patron de marche automatique et inconscient modulé par le tronc cérébral, les noyaux gris centraux et par des retours sensitifs (visuels, proprioceptives, vestibulaires et épicritiques). Enfin, la marche est aussi sous contrôle volontaire. Le phénotypage quantitatif de la marche suppose la construction préalable de bases de données de signaux de marche d’un nombre élevé (centaines) de sujets et de patients. Ceci peut être mené à bien grâce à des outils de mesure simples d’utilisation et adaptés à la pratique médicale de routine. Il existe plusieurs moyens pour phénotyper la marche mais le capteur inertiel, en raison de son prix, de sa souplesse d’utilisation et de l’accès aux données brutes est un outil particulièrement adapté pour l’étude de la marche en consultation de routine. Les capteurs inertiels permettent le calcul de nombreux paramètres. L’exercice de marche de 10 m aller/retour à vitesse de confort départ arrêté donne accès aux différentes phases de la marche (initiation, croisière, demi-tour) dans des conditions de consultation de routine. Ainsi, l’objectif de ce travail est d’approcher les mécanismes d’adaptation des personnes à des perturbations à différents niveaux anatomiques des structures impliquées dans la marche. Nous abordons cette question par un phénotypage quantitatif à partir du signal de capteurs inertiels recueilli sur des patients au cours d’un exercice de marche de 10 m aller/retour en consultation clinique de routine. Nous avons étudié successivement la marche de patients atteints d’arthrose du membre inférieur comme modèle d’adaptation de la marche à la douleur, puis la marche dans la maladie de Parkinson comme modèle d’atteinte du système de la mise en place des procédures motrices, enfin, la locomotion des patients hémiparétiques à la suite d’un accident vasculaire cérébral hémisphérique comme modèle d’atteinte de la commande volontaire. Nous montrons que la douleur dans l’arthrose du membre inférieur mène à une rigidification globale de la cinématique corporelle. Cette rigidification est prépondérante sur le membre atteint. Elle traduit la perte des synergies musculaires par la mise en place de boucle-réflexe anti-douleur. Nous démontrons que ces modifications sont corrélées à la sévérité clinique de l’arthrose. Pour analyser la régularité de la marche dans la maladie de Parkinson indépendamment des variabilités inter-individuelles du patron de marche nous avons développé un outil de visualisation de l’exercice de marche. La maladie de Parkinson affecte en particulier la régularité de la marche. Notre travail apporte la preuve que cette irrégularité est corrélée à la sévérité des symptômes chez les patients atteints de la maladie de Parkinson. Nous montrons enfin qu’une lésion du cortex dans l’accident vasculaire hémisphérique provoque un changement de stratégie dans le demi-tour. Comme d’autres, nous faisons l’hypothèse que les stratégies de demi-tours sont en partie stockées dans le cortex frontal et que les hémisphères droit et gauche ne jouent pas un rôle symétrique. Nous montrons que le choix de stratégie de demi-tour est corrélé avec la survenue de chutes à 6 mois et pourrait constituer un nouvel élément pour orienter la rééducation. (...) / In the field of neurosciences, significant improvement has been made in the last decades in imaging and genotyping. However, phenotyping remains stagnant at the state of visual observation or visual grading scales. The human phenotype is made up of locomotion (gait, posture and displacement of daily living), upper-limb fine and rough movements, eye movements, language, cognition and complex social behaviors. Gait is a central function in humans, implying volitional, emotional and automatic processes. It involves the whole musculoskeletal system as well as the central and the peripheral nervous system including sensory organs. Building a gait phenotyping system implies setting up a database of gait signals of many (hundreds) of subjects and patients. This goal can be achieved with user-friendly devices deployed in routine medical practice. For instance, inertial measurement units (IMUs) are a valid tool to measure spatio-temporal gait parameters and are adapted to routine medical use. The 10-meter walking test forward and back at self-selected walking speed is adapted to routine testing at the doctor’s office. It allows for measuring gait initiation, gait cruise, gait termination and a 180° turn. In that context, beyond technical challenges, the aim of this work was to address the question How does the central nervous system adapt to an external alteration on various levels in the command chain of gait? To answer this question, we studied sequentially the IMU signal of gait spatio-temporal kinematics in lower-limb osteoarthritis as a model of gait affected by pain, in Parkinson disease as a model of a lesion of the central nervous system muscle tone regulator and finally, in post-hemispheric stroke as a model of lesions of brain structures responsible for volitional locomotion. Secondary clinical questions were How can the severity of a disease be objectively graded with gait kinematics? and How can locomotion kinematics participate in the fall risk prediction in frail populations? In osteoarthritis, we showed that pain in lower-limb osteoarthritis led to a global stiffness of the body during locomotion. This stiffness was preponderant on the affected limbs and led to the loss of muscular synergies by the establishment of anti-pain reflexes as a reaction to pain. This change was correlated with the severity of lower-limb osteoarthritis. In Parkinson disease, to analyze gait regularity independently from inter-individual gait signature, we constructed a novel gait visualization tool and show that a lesion of the muscle tone regulator in Parkinson disease affects gait regularity. This regularity was associated with disease symptoms. Finally, in stroke, we showed that a lesion in the cortex implied a change in the 180° turning stepping, a volitional task. In line with other authors, we hypothesized that locomotion patterns could be generated in the frontal cortex and that the right and left frontal cortex did not have a symmetric role. We showed specific stepping patterns associated more with risk of fall, which could constitute a new argument to orientate rehabilitation. Altogether then, this work suggests that simple measuring hardware (here IMUs), with appropriate signal processing, allowed for decomposing and quantifying complex behavioral tasks (here locomotion) in daily hospital settings.

This dissertation presents a novel approach to develop a system for real-time tracking of the position and orientation of the human hand in three-dimensional space, using MEMS inertial measurement units (IMUs) and infrared cameras. This research focuses on the study and implementation of an algorithm to correct the gyroscope drift, which is a major problem in orientation tracking using commercial-grade IMUs. An algorithm to improve the orientation estimation is proposed. It consists of: 1.) Prediction of the bias offset error while the sensor is static, 2.) Estimation of a quaternion orientation from the unbiased angular velocity, 3.) Correction of the orientation quaternion utilizing the gravity vector and the magnetic North vector, and 4.) Adaptive quaternion interpolation, which determines the final quaternion estimate based upon the current conditions of the sensor. The results verified that the implementation of the orientation correction algorithm using the gravity vector and the magnetic North vector is able to reduce the amount of drift in orientation tracking and is compatible with position tracking using infrared cameras for real-time human hand motion tracking. Thirty human subjects participated in an experiment to validate the performance of the hand motion tracking system. The statistical analysis shows that the error of position tracking is, on average, 1.7 cm in the x-axis, 1.0 cm in the y-axis, and 3.5 cm in the z-axis. The Kruskal-Wallis tests show that the orientation correction algorithm using gravity vector and magnetic North vector can significantly reduce the errors in orientation tracking in comparison to fixed offset compensation. Statistical analyses show that the orientation correction algorithm using gravity vector and magnetic North vector and the on-board Kalman-based orientation filtering produced orientation errors that were not significantly different in the Euler angles, Phi, Theta and Psi, with the p-values of 0.632, 0.262 and 0.728, respectively. The proposed orientation correction algorithm represents a contribution to the emerging approaches to obtain reliable orientation estimates from MEMS IMUs. The development of a hand motion tracking system using IMUs and infrared cameras in this dissertation enables future improvements in natural human-computer interactions within a 3D virtual environment.

No description available.

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.

The breakthrough in mobile technology and the development of smartphones, supplied with sensing devices such as Inertial Measurement Units (IMUs), has made it possible to obtain accurate and reliable data on the angular velocity for different objects. The available technical sensors for wrist movements, such as electrogoniometers, are costly, time-consuming, and need a particular computer program to be analyzed. Therefore, there is a need to develop user-friendly risk assessment methods for wrist angular velocity measurements. This master thesis aimed to validate the accuracy of a newly developed iPhone application (App), "ErgoHandMeter," for wrist velocity in actual work tasks, by comparing the “ErgoHandMeter” to standard electrogoniometers. The project study was performed with four participants, two females and two males, from three jobs performing actual work tasks. The total angular velocity obtained by the mobile application was compared with the angular velocity data from the standard electrogoniometer. The total angular velocities obtained from the smartphone and the goniometer were computed at the 10th, 50th and 90th percentile for the four subjects. The 50th percentile of goniometer-flexion velocity (G-flex) was 7.4 ± 5.4°/s, for the goniometer-total (G-tot) 8.7 ± 6.5)°/s and for App 7.2 ± 4.9°/s. The correlation coefficient for the 50th percentile of goniometer-flexion (G-flex) parameter and smartphone application was 0.994. For the goniometer-total (G-tot) and the application, it was 0.993. In a Bland-Altman plot the mean difference between G-flex and App for the 50th percentile was -0.18 °/s and for G-tot and App was -1.54 °/s, i.e. the App was lower in average. The limit of the agreement between G-Flex and App, and G-tot and App stayed within two standard deviations. For G-Flex and App (mean+1.96SD) was 1.34 °/s, (mean-1.96SD) was -1.71 °/s, while for G-tot and App (mean+1.96SD) was 1.89 °/s, (mean-1.96SD) was -4.96 °/s, indicating an adequate agreement between the two methods. A limitation was that the included occupations were all relatively low velocity. However, in conclusion, the results indicate that the two methods agree adequately and can be used interchangeably. / Genombrottet inom mobiltekniken och utvecklingen av smarttelefoner med sensorer som t.ex. tröghetsmätningsenheter (IMU) har gjort det möjligt att få exakta och tillförlitliga uppgifter om vinkelhastigheten för olika objekt. De tillgängliga tekniska sensorerna för handledsrörelser, t.ex. elektrogoniometrar, är dyra, tidskrävande och de samplade signalerna kräver ett särskilt datorprogram för att analyseras. Det finns därför ett behov av att utveckla användarvänliga riskbedömningsmetoder för mätningar av handledens vinkelhastighet. Syftet med detta examensarbete var att validera noggrannheten hos en nyutvecklad iPhone-applikation (App), "ErgoHandMeter", för handledshastighet i verkliga arbetsuppgifter, genom att jämföra "ErgoHandMeter" med vanliga elektrogoniometrar. Projektstudien genomfördes med fyra deltagare, två kvinnor och två män, från tre yrken som utförde verkliga arbetsuppgifter. Den totala vinkelhastigheten som erhölls av mobilapplikationen jämfördes med vinkelhastighetsdata från standardelektrogoniometern. De totala vinkelhastigheterna som erhållits från smarttelefonen och goniometern beräknades vid den 10:e, 50:e och 90:e percentilen för de fyra försökspersonerna. Den 50:e percentilen för goniometer-flexionshastigheten (G-flex) var i genomsnitt 7,4°/s och för goniometertotalen (G-tot) 8,7°/s. Korrelationskoefficienten (r) för den 50:e percentilen för goniometer-flexionsparametern (G-flex) och smartphone-applikationen var 0,994. För goniometer-total (G-tot) och applikationen var r 0,993. I en Bland-Altman-plot var den genomsnittliga skillnaden mellan G-flex och appen för den 50:e percentilen -0,18°/s och för G-tot och appen -1,54°/s (App var lägre än Gon). Medelvärdet för differensen mellan G-Flex och App och G-tot och App ligger inom två standardavvikelser. För G-Flex och App (medelvärde+1,96SD) var 1,34 °/s, (medelvärde-1,96SD) var -1,71 °/s, medan för G-tot och App (medelvärde+1,96SD) var 1,89 °/s, (medelvärde-1,96SD) var -4,96 °/s. Vilket tyder på en tillräcklig överensstämmelse mellan de två metoderna. En begränsning var att de inkluderade yrkena alla hade relativt låg hastighet. Sammanfattningsvis visar dock resultaten att de två metoderna stämmer väl överens och kan användas på ett utbytbart sätt.