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.

International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / Obtaining a projectile’s free-flight motion profile and its aerodynamic coefficients is typically accomplished at indoor test ranges using photographic techniques synchronized to timing stations. Since these ranges are relatively short, many discrete tests are necessary to compile a complete understanding of the projectile’s behavior. When Time Space Position Information (TSPI) is requested over long-range flights, it has been gathered with expensive video, laser, and radar trackers. These can be inaccurate at times and are limited to locations where the range equipment is able to track the projectile’s entire flight. With the ever-increasing sophistication of ordnance, such as smart and competent munitions that have multi-stage thrusting and maneuvering capability, it is becoming increasingly difficult to make the necessary measurements using current measurement techniques. Microelectromechanical Systems (MEMS) sensors and other electro-optical and magnetic sensors referenced to the sun and earth allow the projectile’s angular rates (spin, pitch, and yaw) and accelerations (axial and radial) to be measured throughout the flight. These sensors have been packaged into miniaturized telemetry instrumentation systems and placed within empty voids of the munition or in place of the fuze or warhead section. By combining this sensor data with a 6-DOF trajectory code, many of the projectiles aerodynamic coefficients including drag, static moment, and damping moment over a large Mach Number range and over multiple flight paths have been obtained. These techniques decrease the number of test shots required, reduce the complexity of the test setup, and reduce the test costs. Test data from instrumented tank, artillery, and rocket flight tests are presented in this report to show the current capability of making inflight measurements using telemetry-based techniques.

O mecanismo Plataforma de Stewart é um manipulador do tipo paralelo, com seis graus de liberdade, boa relação peso/carga e alta rigidez. Tais características conferem a este tipo de manipulador propriedades superiores de precisão em relação aos manipuladores seriais. Neste trabalho, o controle de um Manipulador Plataforma de Stewart (MPS) acionado por atuadores hidráulicos é estudado com o objetivo de compensação de movimentos para viabilização de transferência de cargas e pessoas em ambiente naval.Visando ao desenvolvimento de um protótipo experimental, o manipulador é estudado considerando a situação em que se encontra sobreposto a um segundo MPS que tem por objetivo simular o movimento da maré, sendo ambos MPS considerados desacoplados dinamicamente. Neste contexto, o estudo envolve a análise cinemática e dinâmica do manipulador incluindo, também, a dinâmica dos cilindros hidráulicos. Além disso, são estudadas unidades de medição inercial (IMU) utilizando-as como instrumento para medição do movimento da base a ser compensado. O projeto do controlador do sistema de atenuação de movimento faz uso da técnica de Torque Computado (TC). A análise de estabilidade, feita separadamente para o sistema mecânico e hidráulico, baseou-se da teoria de Lyapunov. Simulações realizadas considerando trajetórias similares às do movimento de um navio são utilizadas. Para compensação do movimento são utilizados, também, sinais provenientes de uma IMU. Por meio de simulação, comprova-se que o sistema proposto é capaz de compensar adequadamente os movimentos da base estudados. / The Stewart platform mechanism is a parallel manipulator with six degrees of freedom, high load/weight ratio and high stifness. These properties give them a better accuracy when compared to serial manipulators. This work focuses on study of electrohydraucally Stewart Platform Manipulators (MPS) to enable compensation of vessels motions for load and personell transfer in sea. Aimed at developing an experimental prototype, a second MPS is placed underneath the rst MPS to simulate vessels motions and so both manipulators are considered dynamically decoupled. In this sense, the kinematics and dynamics of this manipulator are presented, as well as a mathematical model of the hydraulic actuator. Furthermore, special attention is given to the study of inertial measurement units (IMU) which is used as an instrument for measuring the motion to be compensated. Controller design for the compensation system is developed considering compute torque theory which consider the system separated in two: mechanical and hydraulic. The Lyapunov criteria is used to guarantee closed loop stability for each subsystem. Simulations are performed considering similar vessel motions. Signals provided from a comercial IMU are used for motion compensation. The control compensation performance is veri ed by means of computer simulations.

Accurate risk assessment tools and methods are necessary to understand the relationship between occupational exposure to physical risk factors and musculoskeletal disorders. Ergonomists typically consider direct measurement methods to be the most objective and accurate of the available tools. However, direct measurement methods are often not used due to cost, practicality, and worker/workplace disruption. Inertial measurement units (IMUs), a relatively new direct measurement technology used to assess worker kinematics, are attractive to ergonomists due to their small size, low cost, and ability to reliably capture information across full working shifts. IMUs are often touted as a field-capable alternative to optical motion capture systems (OMCs). The error magnitudes of IMUs, however, can vary significantly (>15°) both within and across studies. The overall goals of this thesis were to (i) provide knowledge about the capabilities and limitations of IMUs in order to explain the inconsistencies observed in previous studies that assessed IMU accuracy, and (ii) provide guidance for the ergonomics community to leverage this technology. All three studies in this dissertation systematically evaluated IMUs using a repetitive material transfer task performed by thirteen participants with varying movement speeds (15, 30, 45 cycles/minute) and magnetic disturbance (absent, present). An OMC system was used as the reference device. This first study systematically evaluated the effects of motion speed and magnetic disturbance on the spatial orientation accuracy of an inertial measurement unit (IMU) worn on the hand. Root-mean-square differences (RMSD) exceeded 20° when inclination measurements (pitch and roll) were calculated using the IMU’s accelerometer. A linear Kalman filter and a proprietary, embedded Kalman filter reduced inclination RMSD to < 3° across all movement speeds. The RMSD in the heading direction (i.e., about gravity) increased (from < 5° to 17°) under magnetic disturbance. The linear Kalman filter and the embedded Kalman filter reduced heading RMSD to < 12° and < 7°, respectively. This study indicated that the use of IMUs and Kalman filters can improve inclinometer measurement accuracy. However, magnetic disturbances continue to limit the accuracy of three-dimensional IMU motion capture. The goal of the second study was to understand the capability of IMU inclinometers to improve estimates of angular displacements and velocities of the upper arm. RMSD and peak displacement error exceeded 11° and 28° at the fastest transfer rate (45 cycles/min) when upper arm elevation was calculated using the IMU accelerometer. The implementation of a Kalman filter reduced RMS and peak errors to < 1.5° and < 2.3°, respectively. Similarly, the RMS and peak error for accelerometer-derived velocities exceeded 81°/s and 221.3°/s, respectively, at the fastest transfer rate. The Kalman filter reduced RMS and peak errors to < 9.2°/s and < 25.1°/s, respectively. The third study was conducted to evaluate the relationship between magnetic field strength variation and magnetic heading deviation. In this study, the presence of the metal plate increased magnetic heading deviations from < 12° (90th-10th percentile) to approximately 30°. As expected, the magnetic field strength standard deviation increased from 1.0uT to 2.4uT. While this relationship may differ across other sources of magnetic disturbance, the results reinforce the notion that local magnetic field disturbances should be minimized when using IMUs for human motion capture. Overall, the findings from this thesis contribute to the ergonomics community’s understanding of the current capabilities and limitations of IMUs. These studies suggest that while the touted capabilities of the IMUs (full-body motion capture in workplace settings) may be unattainable based on current sensor technology, these sensors are still significantly more accurate than the accelerometer-based inclinometers commonly used by ergonomists to measure motions of the upper arms.

This thesis proposes a motion sensing system for wheelchairs with the main objective of determining tips, falls and risky situations. The system relies on measurements from an Inertial Measurement Unit, (IMU), consisting of a 3-axis accelerometer and a 2-axis gyroscope as the source of information. The IMU was embedded in a portable device, the "Motion Logger", which collects motion data in a Secure Digital memory card after running a real time preprocessing algorithm. The algorithm was designed to reduce energy consumption and memory usage. Actual signal analysis and attitude estimation is carried out offline. The motion sensing system was developed for determining wheelchair-related falls as part of a major research effort carried out at the research center of the James A Haley VA Hospital Subject Safety Center, Tampa, Florida. The focus of the study concentrated on achieving a thorough understanding of the demographics, nature, consequences and the creation of prediction models for fall events. The main goal of the embedded system was to successfully estimate the motion variables relevant to the occurrence of falls, tips and similar risky situations. Currently, off-line smoothing techniques based on Kalman filter concepts allow for optimal estimation of angles in the longitudinal direction, roll, and in the lateral direction, pitch. Results from both predefined experiments with known outcomes and data collected from actual wheelchair users during pilot and final deployment stages are presented and discussed.

Epidemiological evidence suggests an association between exposure to non-neutral working postures and work-related musculoskeletal disorders (MSDs) of the low back and shoulder. Accurate and precise quantitative estimation of exposure to non-neutral working postures is, therefore, essential for evaluating worker risk, developing and testing ergonomic interventions, and improving worker health and well-being. Current methods used to directly estimate occupational exposure to non-neutral postures may be obtrusive, often lack sufficient portability for field use, and have limited accuracy and precision when used to measure dynamic or complex motions. Inertial measurement units (IMUs) are emerging instrumentation devices that measure and report an object's orientation and motion characteristics using multiple electromechanical sensors (i.e., accelerometers, gyroscopes, and/or magnetometers). They have been observed to accurately monitor body kinematics over periods of relatively short duration in comparison to laboratory-based optical motion capture systems. Limited research, however, has been performed comparing exposure information obtained with IMUs to exposure information obtained with other field-capable direct measurement exposure assessment methods. Furthermore, insufficient information on the repeatability of IMU-based estimates over a substantial time period (e.g., a full work shift) and inadequate knowledge regarding the effects of different IMU sensor configurations and processing methods on the accuracy and repeatability of estimates of exposure obtained with IMU systems contributes to a lack of their use in epidemiological field studies. This thesis was designed to address these issues and expand upon the current scientific literature regarding the use of IMU sensors as direct measurement devices for assessing exposure to non-neutral working postures in the field. Chapter I provides a background and justification for the work. Chapter II presents the findings of a laboratory-based, manual material handling study that was performed to compare estimates of thoracolumbar trunk motion obtained with a commercially available IMU system with estimates of thoracolumbar trunk motion obtained with a field-capable reference system, the Lumbar Motion Monitor (LMM). The effects of alternative sensor configurations and processing methods on the agreement between LMM and IMU-based estimates of trunk motion were also explored. Chapter III presents the results of a study performed to evaluate the accuracy and repeatability of estimates of trunk angular displacement and upper arm elevation obtained with the IMU system examined in Chapter II over the course of an eight-hour work shift in both a laboratory and field-based setting. The effects of alternative sensor configurations and processing methods on the accuracy and repeatability of estimates of trunk angular displacement and upper arm elevation obtained with the IMU system were also studied. Chapter IV presents the results of a randomized, repeated measures intervention that demonstrates the utility of the IMU system examined in Chapters II and III as a direct measurement instrument for comparing "ergonomic" and conventional examination equipment commonly used by ophthalmologists. Finally, Chapter V summarizes the major findings, discusses their practical implications, and provides suggestions for future research.

<p>Hasomed GmbH, a German company in the Field of medicine technology, intends to introduce a gait analysis system on the market. The system includes an inertial sensor which collects data used for generating movement patterns of the feet. This thesis describes the development and evaluation of a new version of the sensor, aimed at minimizing costs, maximizing performance and facilitating production.</p><p>Algorithms used in the gait analysis system are sensitive to noise. Noise sources and precautions taken in order to minimize noise levels are described and discussed. By minimizing the physical size of analogue electronics blocks, static noise and occasional high frequency components were substantially reduced.</p><p>New features including internal temperature sensors, firmware update via serial interface, self-test functions and a wireless link were implemented. Additional improvements are e.g. lower power consumption and an extension of the interface from 2 to 256 (theoretical limit) attached devices. By reducing the number of included components and PCB (Printed Circuit Board) layers, together with use of components that do not require advanced soldering techniques, easier and cheaper production was obtained.</p><p>Research and development presented in this thesis resulted in a sensor with overall good performance and new features.</p>

Today the area of high-cost and high-performance navigation for vehicles is a well-developed field. The challenge now is to develop high-performance navigation systems using low-cost sensortechnology. This development involves problems spanning from signal processing of the dirty measurements produced by low-costsensors via fusion and synchronization of information produced by a large set of diverse sensors, to reducing the size and energyconsumption of the systems. This thesis examines and proposessolutions to four of these problems. The first problem examined is the time synchronizing of the sensordata in a global positioning system aided inertial navigationsystem in which no hardware clock synchronization is possible. A poor time synchronization results in an increased mean squareerror of the navigation solution and expressions for calculating this mean square error are presented. A method to solve the timesynchronization issue in the data integration software is proposed. The potential of the method is illustrated with tests onreal-world data that are subjected to timing errors. The second problem examined is the achievable clocksynchronization accuracy in a sensor network employing a two-waymessage exchange model. The Cramer-Rao bound for the estimation of the clock parameters is derived and transformed in to a lower bound on the mean square error of the clock offset.Further, an approximate maximum likelihood estimator for the clockparameters is proposed. The estimator is shown to be of low complexity and to have a mean square error in the vicinity of the Cramer-Rao bound. The third problem examined is the detection of the time epochswhen zero-velocity updates can be applied in a foot-mountedpedestrian navigation system. Four general likelihood ratio testsfor detecting when the navigation system is stationary based onthe inertial measurement data are studied. The performance of thefour detectors is evaluated using levelled ground, forward-gaitdata. The results show that the signals from the gyroscopes holdthe most reliable information for the zero-velocity detection. The fourth problem examined is the calibration of a low-costinertial measurement unit. A calibration procedure that relaxesthe accuracy requirements of the orientation angles the inertialmeasurement unit must be placed in during the calibration isstudied. The proposed calibration method is compared with theCramer-Rao bound for the case when the inertial measurementunit is rotated into precisely controlled orientations. Simulationresults show that the mean square error of the estimated sensormodel parameters reaches the Cramer-Rao bound within fewdecibels. Thus, the proposed method may be acceptable for a widerange of low-cost applications. / QC 20100810

Hasomed GmbH, a German company in the Field of medicine technology, intends to introduce a gait analysis system on the market. The system includes an inertial sensor which collects data used for generating movement patterns of the feet. This thesis describes the development and evaluation of a new version of the sensor, aimed at minimizing costs, maximizing performance and facilitating production. Algorithms used in the gait analysis system are sensitive to noise. Noise sources and precautions taken in order to minimize noise levels are described and discussed. By minimizing the physical size of analogue electronics blocks, static noise and occasional high frequency components were substantially reduced. New features including internal temperature sensors, firmware update via serial interface, self-test functions and a wireless link were implemented. Additional improvements are e.g. lower power consumption and an extension of the interface from 2 to 256 (theoretical limit) attached devices. By reducing the number of included components and PCB (Printed Circuit Board) layers, together with use of components that do not require advanced soldering techniques, easier and cheaper production was obtained. Research and development presented in this thesis resulted in a sensor with overall good performance and new features.

Current physiotherapy practice relies on visual observation of the patient for diagnosis and assessment. The assessment process can potentially be automated to improve accuracy and reliability. This thesis proposes a method to recover patient joint angles and automatically extract movement profiles utilizing small and lightweight body-worn sensors. Joint angles are estimated from sensor measurements via the extended Kalman filter (EKF). Constant-acceleration kinematics is employed as the state evolution model. The forward kinematics of the body is utilized as the measurement model. The state and measurement models are used to estimate the position, velocity and acceleration of each joint, updated based on the sensor inputs from inertial measurement units (IMUs). Additional joint limit constraints are imposed to reduce drift, and an automated approach is developed for estimating and adapting the process noise during on-line estimation. Once joint angles are determined, the exercise data is segmented to identify each of the repetitions. This process of identifying when a particular repetition begins and ends allows the physiotherapist to obtain useful metrics such as the number of repetitions performed, or the time required to complete each repetition. A feature-guided hidden Markov model (HMM) based algorithm is developed for performing the segmentation. In a sequence of unlabelled data, motion segment candidates are found by scanning the data for velocity-based features, such as velocity peaks and zero crossings, which match the pre-determined motion templates. These segment potentials are passed into the HMM for template matching. This two-tier approach combines the speed of a velocity feature based approach, which only requires the data to be differentiated, with the accuracy of the more computationally-heavy HMM, allowing for fast and accurate segmentation. The proposed algorithms were verified experimentally on a dataset consisting of 20 healthy subjects performing rehabilitation exercises. The movement data was collected by IMUs strapped onto the hip, thigh and calf. The joint angle estimation system achieves an overall average RMS error of 4.27 cm, when compared against motion capture data. The segmentation algorithm reports 78% accuracy when the template training data comes from the same participant, and 74% for a generic template.