Ego-motion sensors are commonly used for pose estimation in Simultaneous Localization And Mapping (SLAM) algorithms. Inertial Measurement Units (IMUs) are popular sensors but suffer from integration drift over longer time scales. To remedy the drift they are often used in combination with additional sensors, such as a LiDAR. Pose estimation is used when scans, produced by these additional sensors, are being matched. The matching of scans can be computationally heavy as one scan can contain millions of data points. Methods exist to simplify the problem of finding the relative pose between sensor data, such as the Normal Distribution Transform SLAM algorithm. The algorithm separates the point cloud data into a voxelgrid and represent each voxel as a normal distribution, effectively decreasing the amount of data points. Registration is based on a function which converges to a minimum. Sub-optimal conditions can cause the function to converge at a local minimum. To remedy this problem this thesis explores the benefits of combining IMU sensor data to estimate the pose to be used in the NDT SLAM algorithm.

La localisation automatique est une fonctionnalité importante des systèmes de cartographie mobiles (Mobile Mapping Systems, MMS). La présente thèse présente des solutions complémentaires aux méthodes de localisation utilisées actuellement dans un système MMS terrestre, qui utilise des récepteurs GPS et des centrales à inertie (Inertial Measurement Units, IMU). Un post-traitement, par lissage des données, permet d'améliorer les cartes 3D générées par un MMS. Cette approche est cependant insuffisante pour corriger les erreurs à variations lentes des capteurs. La présente thèse propose une technique de localisation alternative, fondée sur des scanners 2D à lasers. La méthode présentée ici, d'odométrie par laser, utilise des repères plans, qui sont fréquents dans les environnements créés par l'Homme : ces repères fixes permettent de déterminer le déplacement opéré par la plateforme mobile. Contrairement à la technique du SLAM (Simultaneous Localization and Mapping), utilisée pour la navigation des robots à l'intérieur d'un bâtiment, la transformation 3D est calculée sans avoir recours à une carte préétablie, mais en exploitant des propriétés invariantes des caractéristiques extraites de l'environnement. Nous proposons une approche par "division pour régner" (divide and conquer, D&C) qui simplifie les tâches d'association des repères (data association, DA) et de reconstruction du mouvement.

Today's state-of-the-art rate vibratory gyroscopes use a large proof mass that vibrates at a low resonance frequency (3-30 kHz), a condition that creates a performance tradeoff in which the gyroscope can either offer large bandwidth or high resolution, but not both. This tradeoff led to the development of the capacitive bulk acoustic wave (BAW) silicon disk gyroscope, a new class of micromachined rate vibratory gyroscopes operating in the frequency range of 1-10MHz with high device bandwidth and shock/vibration tolerance. By scaling the frequency, BAW gyroscopes can provide low mechanical noise without sacrificing the high bandwidth performance needed for most commercial applications. The drive loop of the BAW gyroscope can also be exploited as a timing device that can be integrated in existing commercial systems to provide competitive clock performance to the state-of-the-art using less area and power. This dissertation discusses the design and implementation of a CMOS ASIC architecture that interfaces with a high-Q, wide-bandwidth BAW gyroscope and the challenges associated with optimizing the noise performance to achieve navigation-grade levels of sensitivity as the frequency is scaled into the MHz regime. Mathematical models are derived to describe the operation of the sensor and are used to generate equivalent electrical circuit models of the gyroscope. A design strategy is then outlined for the ASIC to optimize the drive loop and sense channel for power and noise, and steps toward reducing this noise as the system is pushed to navigation-grade performance are presented that maintain optimum system power consumption. After analyzing the BAW gyroscope and identifying a strategy for developing the drive and sense interface circuitry, a complete fully-differential ASIC is designed in 0.18μm CMOS to interface with a bulk acoustic wave (BAW) disk gyroscope. As an oscillator, the gyroscope provides an uncompensated clock signal at ~9.64 MHz with a temperature sensitivity of -27 ppm/°C and phase noise of -104 dBc at 1 kHz from carrier. When the complete ASIC is interfaced with the gyroscope, the sensor shows a measured rate sensitivity of 1.15 mV/o/s with an open-loop bandwidth of 280 Hz and a bias instability of 0.095 o/s, suitable for the rate-grade performance commonly required for commercial and consumer electronics applications. The system is recorded to have a total power of 1.6 mW and a total area of 0.64 mm2. Following the design of the interface ASIC, this dissertation investigates in further detail the requirements for designing and optimizing charge pumps for capacitive MEMS devices. Basic charge pump design is outlined, followed by an overview of techniques that can be used to generate larger polarization voltages from the ASIC. Lastly, an alternate measurement technique for measuring the rotation rate of the gyroscope is discussed. This technique is based on the phase-shift modulation of the gyroscope output signal when the device is driven with two orthogonal signal inputs and can be easily modified to provide either linear scale factor measurement or a linear calibration curve that can be used to track and adjust the variation of the sensor scale factor over time.

Mobile virtual reality (VR) headsets have been becoming more and more popular. However, the cheapest headsets do not come with any controllers and the ones that do include controllers only uses sensors for rotation, not translational movement. This thesis project aims to develop a prototype of a Bluetooth connected controller for the mobile VR headsets. The controller is based on a MetamotionC board produced by mbientlab Inc., which comes with Bluetooth Low Energy (BLE), an ARM M4 microcontroller, an miniature inertial measurement unit (IMU) sensor (containing a 3-axis accelerometer, a 3-axis gyroscope, and a 3-axis magnetometer and a barometer), a thermometer and other sensors. The only sensors used in this project are the accelerometer, gyroscope, and magnetometer. As a finished prototype, the MetaMotionC is placed on a glove together with five Aruco markers; a 3D model of a hand intended to use as an avatar of the glove was made with Blender and MakeHuman; and a VR room to use the controller with was created in Unity. The 3D hand responds to rotational and translational movements via Bluetooth connection to the IMU sensor on the MetaMotionC. The smartphone camera is used to detect the glove's position with Aruco markers, and the 3D hand is moved to a corresponding location in the VR room. The OpenCV library is used for image processing. The sensor data is filtered with low-pass, median, and thresholding to improve the measurement accuracy. Zero velocity update is used to reset the drift of the integrated accelerations. To reduce the integration error, Romberg's method with a floating window is implemented in Matlab. However, it did not reduce the error enough to make a difference. Thus, the result was unreliable.

Les centrales inertielles (triade de capteurs inertiels dont la fusion des données permet l’estimation de l’orientation d’un corps rigide) sont de plus en plus populaires en biomécanique. Toutefois, les qualités métrologiques des centrales inertielles (CI) sont peu documentées et leur capacité à identifier des incapacités liées à la mobilité, sous-évaluée. Objectifs : (i) Caractériser la validité de la mesure d’orientation issue de CI ; (ii) Optimiser la justesse et la fidélité de ces mesures; et (iii) Proposer des métriques de mobilité basées sur les mesures d’orientation issues de CI. Méthodologie et résultats : La validité de la mesure d’orientation de différents types de CI a d’abord été évaluée en conditions contrôlées, à l’aide d’une table motorisée et d’une mesure étalon. Il a ainsi été démontré que les mesures d’orientation issues de CI ont une justesse acceptable lors de mouvements lents (justesse moyenne ≤ 3.1º), mais que cette justesse se dégrade avec l’augmentation de la vitesse de rotation. Afin d’évaluer l’impact de ces constatations en contexte clinique d’évaluation de la mobilité, 20 participants ont porté un vêtement incorporant 17 CI lors de la réalisation de diverses tâches de mobilité (transferts assis-debout, marche, retournements). La comparaison des mesures des CI avec celles d’un système étalon a permis de dresser un portrait descriptif des variations de justesse selon la tâche exécutée et le segment/l’articulation mesuré. À partir de ces constats, l’optimisation de la mesure d’orientation issue de CI est abordée d’un point de vue utilisateur, démontrant le potentiel d’un réseau de neurones artificiel comme outil de rétroaction autonome de la qualité de la mesure d’orientation (sensibilité et spécificité ≥ 83%). Afin d’améliorer la robustesse des mesures de cinématique articulaire aux variations environnementales, l’ajout d’une photo et d’un algorithme d’estimation de pose tridimensionnelle est proposé. Lors d’essais de marche (n=60), la justesse moyenne de l’orientation à la cheville a ainsi été améliorée de 6.7° à 2.8º. Finalement, la caractérisation de la signature de la cinématique tête-tronc pendant une tâche de retournement (variables : angle maximal tête-tronc, amplitude des commandes neuromusculaires) a démontré un bon pouvoir discriminant auprès de participants âgés sains (n=15) et de patients atteints de Parkinson (PD, n=15). Ces métriques ont également démontré une bonne sensibilité au changement, permettant l’identification des différents états de médication des participants PD. Conclusion : Les mesures d’orientation issues de CI ont leur place pour l’évaluation de la mobilité. Toutefois, la portée clinique réelle de ce type de système ne sera atteinte que lorsqu’il sera intégré et validé à même un outil de mesure clinique. / Abstract : Inertial measurement of motion is emerging as an alternative to 3D motion capture systems in biomechanics. Inertial measurement units (IMUs) are composed of accelerometers, gyroscopes and magnetometers which data are fed into a fusion algorithm to determine the orientation of a rigid body in a global reference frame. Although IMUs offer advantages over traditional methods of motion capture, the value of their orientation measurement for biomechanics is not well documented. Objectives: (i) To characterize the validity of the orientation measurement issued from IMUs; (ii) To optimize the validity and the reliability of these measurements; and (iii) To propose mobility metrics based on the orientation measurement obtained from IMUs. Methods and results: The criterion of validity of multiple types of IMUs was characterized using a controlled bench test and a gold standard. Accuracy of orientation measurement was shown to be acceptable under slow conditions of motion (mean accuracy ≤ 3.1º), but it was also demonstrated that an increase in velocity worsens accuracy. The impact of those findings on clinical mobility evaluation was then assessed in the lab, with 20 participants wearing an inertial suit while performing typical mobility tasks (standing-up, walking, turning). Comparison of the assessed IMUs orientation measurements with those from an optical gold standard allowed to capture a portrait of the variation in accuracy across tasks, segments and joints. The optimization process was then approached from a user perspective, first demonstrating the capability of an artificial neural network to autonomously assess the quality of orientation data sequences (sensitivity and specificity ≥ 83%). The issue of joint orientation accuracy in magnetically perturbed environment was also specifically addressed, demonstrating the ability of a 2D photograph coupled with a 3D pose estimation algorithm to improve mean ankle orientation accuracy from 6.7° to 2.8º when walking (n=60 trials). Finally, characterization of the turn cranio-caudal kinematics signature (variables: maximum head to trunk angle and neuromuscular commands amplitude) has demonstrated a good ability to discriminate between healthy older adults (n=15) and early stages of Parkinson’s disease patients (PD, n=15). Metrics have also shown a good sensitivity to change, enabling to detect changes in PD medication states. Conclusion: IMUs offer a complementary solution for mobility assessment in clinical biomechanics. However, the full potential of this technology will only be reached when IMUs will be integrated and validated within a clinical tool.

Disertační práce je zaměřena na oblast inerciálních navigačních systémů a systémů, které pro odhad polohy používají pouze výpočty. Důležitým faktem v dané problematice je vysoká nepřesnost určení polohy při střednědobém a dlouhodobém využívání takového systému díky kumulativní chybě za předpokladu, že inerciální systém není podpořen žádným dalším přídavným systémem. V disertační práci jsou uvedeny možné přístupy k této problematice a návrh na zvýšení přesnosti určování polohy pouze na základě inerciálních senzorů. Základem inerciální měřicí jednotky je systém s 9 stupni volnosti, který umožňuje snímat celkové zrychlení, rychlost rotace a sílu magnetického pole, jednotlivě ve třech osách. Klíčovou myšlenkou je zařazení umělých neuronových sítí do navigačního systému tak, že jsou schopny rozpoznat charakteristické rysy pohybů, a tím zvýšit přesnost určení polohy. Popis navrhovaných metod zahrnuje analytický postup jejich vývoje a tam, kde je to možné, i analytické hodnocení jejich chování. Neuronové sítě jsou navrhovány v prostředí MATLABTM a jsou používány k určení stavu inerciální jednotky. Díky implementaci neuronových sítí lze určit pozici jednotky s řádově vyšší přesností. Aby byl inerciální polohovací systém s možností využití neuronových sítí demonstrativní, byla vyvinuta aplikace v prostředí Qt. Navržený systém a neuronové sítě byly použity při vyhodnocování reálných dat měřených senzory.

Because of climate change renewable energy field is becoming more and more relevant. Renewable energy can be gained from the sun, from wind but also from ocean waves. To support the research and development in this field reliably measured wave data is collected through a measurement system that shows the exact position of a buoy. The project consists of the design, development and implementation of such a measurement system. It is divided into three subtasks: The power supply based on a solar panel and a battery The measurement part including a sensor and its implementation to the circuit The deployment of a module for data transmission and communication between the measurement system and the on-shore computer The power supply is capable to power the system and to maintain the battery voltage. A suggested stronger power supply will be used in a later state of the project to increase the reliability. The results of the charging test are good. The power supply system is connected to the circuit and the battery charges. For the measurement system the altitude and heading reference system (AHRS) “Ellipse2-D” from SBG Systems has been selected and connected to an Arduino Mega 2560. The AHRS provides raw data and values processed by a Kalman filter. Both data sets are picked up by the microcontroller. The raw data is backed up on a secure digital memory card (SD-card). For the evaluation of the sensor unit, static and dynamic tests are applied to the sensor. In the end it can be seen that the measurement series are aligned with each other. The information from the Kalman model of the AHRS is transmitted with the Adeunis ARF868 ultra-long range (ULR) modem. The transmitter is linked to the Arduino Mega 2560 and the sensor data is transmitted to the receiver. The first field test already shows the reliability of the system for a range of about 3 km. The results of the tests are as expected and in the future this system will be implemented on a buoy.

This thesis presents an activity mode intent recognition approach for safe, robust and reliable control of powered backbone exoskeleton. The thesis presents the background and a concept for a powered backbone exoskeleton that would work in parallel with a user. The necessary prerequisites for the thesis are presented, including the collection and processing of surface electromyography signals and inertial sensor data to recognize the user’s activity. The development of activity mode intent recognizer was described based on decision tree classification in order to leverage its computational efficiency. The intent recognizer is a high-level supervisory controller that belongs to a three-level control structure for a powered backbone exoskeleton. The recognizer uses surface electromyography and inertial signals as the input and CART (classification and regression tree) as the classifier. The experimental results indicate that the recognizer can extract the user’s intent with minimal delay. The approach achieves a low recognition error rate and a user-unperceived latency by using sliding overlapped analysis window. The approach shows great potential for future implementation on a prototype backbone exoskeleton.

For over a decade, Brigham Young University's Microwave Earth Remote Sensing (MERS) team has been developing SAR systems and SAR processing algorithms. In order to create the most accurate image reconstruction algorithms, detailed aircraft motion data is essential. In 2008, the MERS team purchased a costly inertial measurement unit (IMU) coupled with a high precision global positioning system (GPS) from NovAtel, Inc. In order to lower the cost of obtaining detailed motion measurements, the MERS group decided to build a system that mimics the capability the NovAtel system as closely as possible for a much lower cost. As a first step, the same sensors and a simplified set of flight dynamics are used. This thesis presents a standalone motion sensor recording system (MOTRON), and outlines a method of utilizing the square-root Unscented Kalman filter (SR-UKF) to estimate aircraft flight dynamics, based on recorded flight data, as an alternative to the extended Kalman filter. While the results of the SR-UKF are not as precise as the NovAtel results, they approach the accuracy of the NovAtel system despite the simplified dynamics model.

Spatial haptic interfaces have existed for more than 20 years but have not been widespread despite promising applications. The few devices found in the market as of today are either considered costly, of higher quality and produced in smaller series or mass-produced and cheap, but of lower quality. This thesis aims to develop a new serially-linked everyday haptic desktop product under the project name Polhem. It aims to be based on the previous efforts of WoodenHaptics and AluHaptics, developed by Forsslund et al. The electronics and control software is shared between the WoodenHaptics, the AluHaptics as well as the Polhem designed and manufactured in this project. Polhem is capable of delivering forces in 3 DOF and its manipulandum is trackable in 6 DOF. Polhem is designed so as to eliminate problems related to angular tracking technologies currently used in some higher-end haptic devices. / Spatiala haptiska gränssnitt har existerat i mer än 20 år men har trots sina lovande applikationer inte varit tillgänglig i någon större utsträckning. De få enheter som finns på marknaden i dagsläget anses antingen vara dyra, av högre kvalitet och produceras i mindre serier eller massproducerade och billiga, men av lägre kvalitet. Denna avhandling syftar till att utveckla en ny serielänkad haptisk produkt under projektnamnet Polhem. Polhem syftar till att baseras på de föregående enheterna WoodenHaptics och AluHaptics, som utvecklats av Forsslund et al. Elektroniken och reglermjukvaran delas mellan WoodenHaptics, AluHaptics och Polhem. Polhem kan leverera krafter i 3 frihetsgrader och dess manipulandum kan spåras i 6 frihetsgrader. Polhem är utformad så att den eliminerar problem relaterade till äldre vinkelspårningsteknologi som för närvarande används i många högpresterande haptiska enheter