Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2007. / Abdel-Khalik, Said, Committee Co-Chair ; Ghiaasiaan, Mostafa, Committee Co-Chair ; Jeter, Sheldon, Committee Member.

Thesis (M. Eng.(Mechanical))-University of Pretoria, 2005. / Includes bibliographical references. Available on the Internet via the World Wide Web.

Inertial measurement units (IMUs) are being recognized as a portable and cost-effective alternative to motion analysis systems and have the potential to be introduced into clinical settings for the assessment of functional movement quality of the spine in patients with low back pain. However, uncertainties regarding sensor accuracy and reliability are limiting the widespread use and acceptance of IMU-based assessments into routine clinical practice. The objective of this work was to assess the performance of inexpensive wearable IMUs (Mbientlab MetaMotionR IMUs; Mbientlab Inc., San Francisco, USA; product specifications available in Appendix C) relative to conventional optical motion capture equipment (Vicon Motion Systems Ltd., Oxford, UK) in: 1) a controlled environment, and 2) an uncontrolled environment. The first study evaluated the performance of 2 IMUs in a controlled environment during simulated repetitive spine motion carried out by means of a motorized gimbal. Root mean square error (RMSE) and mean absolute measurement differences between cycle-to-cycle minimum, maximum, and range of motion values, as well as correlational analyses within IMUs and between IMUs and Vicon, in all movement directions (i.e., simulated flexion-extension (FE), lateral bending (LB), and axial twisting (AT)), were compared. Measurement error was low in all axes during all tests (i.e., ≤ 1.54°); however, low-to-moderate correlational results were found in one non-primary axis, and this axis changed depending on the direction of the movement (i.e., LB during FE-motion (0.244 ≤ R ≤ 0.515), AT during LB-motion (0.594 ≤ R ≤ 0.795), and FE during AT-motion (0.002 ≤ R ≤ 0.255)). The second study was designed to assess the performance of the IMUs in an uncontrolled environment during repetitive spine FE in human participants. Absolute angles and local dynamic stability were compared for individual IMUs (which were placed over T10-T12 spinous processes, and the pelvis) as well as for relative motion between IMUs. Maximum finite-time Lyapunov exponents (λmax) were used to quantify local dynamic stability and were calculated using both FE and the sum of squares (SS) from measured spine kinematics. It was found that the IMUs have acceptable performance in all axes when tracking motion (RMSE ≤ 2.43°); however, low-to-moderate correlational results were found in one non-primary axis (0.987 ≤ RFE ≤ 0.998; 0.746 ≤ RLB ≤ 0.978; 0.343 ≤ RAT ≤ 0.679). In addition, correlations between λmax estimates were high; therefore, local dynamic stability can be accurately estimated using both FE and SS data (0.807 ≤ 〖ICC〗_2,1^FE ≤ 0.919; 0.738 ≤ 〖ICC〗_2,1^SS ≤ 0.868). Correlation between λmax estimates was higher when using FE data for individual sensors/rigid-body marker clusters; however, correlation was higher when using SS data for relative motion. In general, the results of these studies show that the MetaMotionR IMUs have acceptable performance in all axes when considering absolute angle orientation and motion tracking, and measurement of local dynamic stability; however, there is low-to-moderate correlation in one non-primary axis, and that axis changes depending on the direction of motion. Future research will investigate how to optimize performance of the third axis for motion tracking; it will also focus on understanding the significance of the third axis performance when calculating specific outcome measures related to spine movement quality.

abstract: The three-dimensional flow contained in a rapidly rotating circular split cylinder is studied numerically solving the Navier--Stokes equations. The cylinder is completely filled with fluid and is split at the midplane. Three different types of boundary conditions were imposed, leading to a variety of instabilities and complex flow dynamics. The first configuration has a strong background rotation and a small differential rotation between the two halves. The axisymmetric flow was first studied identifying boundary layer instabilities which produce inertial waves under some conditions. Limit cycle states and quasiperiodic states were found, including some period doubling bifurcations. Then, a three-dimensional study was conducted identifying low and high azimuthal wavenumber rotating waves due to G\"ortler and Tollmien–-Schlichting type instabilities. Over most of the parameter space considered, quasiperiodic states were found where both types of instabilities were present. In the second configuration, both cylinder halves are in exact counter-rotation, producing an O(2) symmetry in the system. The basic state flow dynamic is dominated by the shear layer created in the midplane. By changing the speed rotation and the aspect ratio of the cylinder, the flow loses symmetries in a variety of ways creating static waves, rotating waves, direction reversing waves and slow-fast pulsing waves. The bifurcations, including infinite-period bifurcations, were characterized and the flow dynamics was elucidated. Additionally, preliminary experimental results for this case are presented. In the third set up, with oscillatory boundary conditions, inertial wave beams were forced imposing a range of frequencies. These beams emanate from the corner of the cylinder and from the split at the midplane, leading to destructive/constructive interactions which produce peaks in vorticity for some specific frequencies. These frequencies are shown to be associated with the resonant Kelvin modes. Furthermore, a study of the influence of imposing a phase difference between the oscillations of the two halves of the cylinder led to the interesting result that different Kelvin modes can be excited depending on the phase difference. / Dissertation/Thesis / Doctoral Dissertation Applied Mathematics 2017

Navigation and mapping in unknown environments is an important building block for increased autonomy of unmanned vehicles, since external positioning systems can be susceptible to interference or simply being inaccessible. Navigation and mapping require signal processing of vehicle sensor data to estimate motion relative to the surrounding environment and to simultaneously estimate various properties of the surrounding environment. Physical models of sensors, vehicle motion and external influences are used in conjunction with statistically motivated methods to solve these problems. This thesis mainly addresses three navigation and mapping problems which are described below. We study how a vessel with known magnetic signature and a sensor network with magnetometers can be used to determine the sensor positions and simultaneously determine the vessel's route in an extended Kalman filter (EKF). This is a so-called simultaneous localisation and mapping (SLAM) problem with a reversed measurement relationship. Previously determined hydrodynamic models for a remotely operated vehicle (ROV) are used together with the vessel's sensors to improve the navigation performance using an EKF. Data from sea trials is used to evaluate the system and the results show that especially the linear velocity relative to the water can be accurately determined. The third problem addressed is SLAM with inertial sensors, accelerometers and gyroscopes, and an optical camera contained in a single sensor unit. This problem spans over three publications. We study how a SLAM estimate, consisting of a point cloud map, the sensor unit's three dimensional trajectory and speed as well as its orientation, can be improved by solving a nonlinear least-squares (NLS) problem. NLS minimisation of the predicted motion error and the predicted point cloud coordinates given all camera measurements is initialised using EKF-SLAM. We show how NLS-SLAM can be initialised as a sequence of almost uncoupled problems with simple and often linear solutions. It also scales much better to larger data sets than EKF-SLAM. The results obtained using NLS-SLAM are significantly better using the proposed initialisation method than if started from arbitrary points. A SLAM formulation using the expectation maximisation (EM) algorithm is proposed. EM splits the original problem into two simpler problems and solves them iteratively. Here the platform motion is one problem and the landmark map is the other. The first problem is solved using an extended Rauch-Tung-Striebel smoother while the second problem is solved with a quasi-Newton method. The results using EM-SLAM are better than NLS-SLAM both in terms of accuracy and complexity. / LINK-SIC

This paper is an extension of various projects that the writer has been associated with at Chance Vought Aircraft, Incorporated.

Magnetic interference in the motion capture environment is caused primarily by ferromagnetic objects and current-carrying devices disturbing the ambient, geomagnetic field. Inertial sensors gather magnetic data to determine and stabilize their global heading estimates, and such magnetic field disturbances alter heading estimates. This decreases orientation accuracy and therefore decreases motion capture accuracy. The often used Kalman Filter approach deals with magnetic interference by ignoring the magnetic data during periods interference is encountered, but this method is only effective when the disturbances are ephemeral, and cannot not retroactively repair data from disturbed time periods. The objective of this research is to develop a method of magnetic interference mitigation for environments where magnetic interference is the norm rather than the exception. To the knowledge of this author, the ability to use inertial and magnetic sensors to capture accurate, global, and drift-free orientation data in magnetically disturbed areas has yet to be developed. Furthermore there are no methods known to this author that are able to use data from undisturbed time periods to retroactively repair data from disturbed time periods. The investigation begins by exploring the use of magnetic shielding, with the reasoning that application of shielding so as to impede disturbed fields from affecting the inertial sensors would increase orientation accuracy. It was concluded that while shielding can mitigate the effect of magnetic interference, its application requires a tedious trial and error testing that was not guaranteed to improve results. Furthermore, shielding works by redirecting magnetic field lines, increasing field complexity, and thus has a high potential to exacerbate magnetic interference. Shielding was determined to be an impractical approach, and development of a magnetic inference mitigation algorithm began. The algorithm was constructed such that magnetic data would be filtered before inclusion in the orientation estimate, with the result that exposure in an undisturbed environment would improve estimation, but exposure to a disturbed environment would have no effect. The algorithm was designed for post-processing, rather than real-time use as Kalman Filters are, which enabled magnetic data gathered before and after a time point could affect estimation. The algorithm was evaluated by comparing it with the Kalman Filter approach of the company XSENS, using the gold standard of optical motion capture as the reference point. Under the tested conditions of stationary periods and smooth planar motion, the developed algorithm was resistant to magnetic interference for the duration of testing, while the Kalman Filter began to degrade after approximately 15 seconds. In a 190 second test, of which 180 were spent in a disturbed environment, the developed algorithm resulted in 0.4 degrees of absolute error, compared to the of the Kalman Filter’s 78.8 degrees. The developed algorithm shows the potential for inertial systems to be used effectively in situations of consistent magnetic interference. As the benefits of inertial motion capture make it a more attractive option than optical motion capture, immunity to magnetic interference significantly expands the usable range of motion capture environments. Such expansion would be beneficial for motion capture studies as a whole, allowing for the cheaper, more practical inertial approach to motion capture to supplant the more expensive and time consuming optimal option.

När tiden för utveckling av nya produkter kortas ner måste testning och verifiering utföras i ett tidigare utvecklingsstadie. Genom simulering av systemet kan tester utföras utan tillgång till det faktiska systemet och därmed kan utvecklingsprocessen accelereras. I BAE Systems Hägglunds stridsvagnar används en tröghetsnavigator som kan beräkna stridsvagnens position utan externa referenser. Test och verifiering av navigation med denna enhet i testbänk är ej fullt möjligt. Syftet med detta arbete är att kunna genomföra verklighetstrogna tester, i testbänk i utvecklingsfasen, genom att simulera navigatorns funktioner. Eftersom kommunikation med fordonssystemet ska ske i realtid samtidigt som navigationsdata läses från ett externt program, så ställs krav på att modellen har tillräcklig prestanda för att ge en verklighetstrogen simulering. Den övergripande frågeställningen i detta examensarbete är om en modell realiserad på en mikrokontroller (MCU) har tillräcklig prestanda för att användas vid simulering av en tröghetsnavigator. För att besvara frågeställningen har hårdvara för anpassning av gränssnittet mellan fordonssystem, MCU och externt program samt mjukvara för att simulera en tröghetsnavigator skapats. Därefter har modellen verifierats genom att mäta tiden för utvalda processer. Alla funktioner hos navigatorn har inte implementerats i simuleringsmodellen men resultaten visar att modellen kan användas för verklighetstrogna tester i testbänk. / When time for development of new products is shortened, testing and verification must be performed at an earlier stage of development. By simulating the system, tests can be performed without access to the actual system and thus the development process can be accelerated.  BAE Systems Hägglunds manufacture combat vehicles and use an Inertial Navigation System (INS) to calculate the combat vehicle’s position without external references. Testing and verification of navigation with this unit in the test bench is not entirely possible.  The aim of this thesis is to enable realistic tests, in a test bench in the development phase, by simulating the navigator’s functions. Since communication with the Vehicle Control System (VCS) must take place in real time at the same time as navigation data must be read from external program, the model is required to have sufficient performance to provide a realistic simulation.  The overall question in this thesis is whether a model realized on a microcontroller (MCU) has sufficient performance to be used for simulation of an INS. To answer the question at issue, hardware for adapting the interface between the VCS, MCU and external program as well as software for simulating an INS have been created. Thereafter, the model has been verified by measuring the time for selected processes.  Not all functions of the navigator have been implemented in the simulation model, but the results show that the model can be used for realistic tests in the test bench.

Inertial measurement units (IMUs) are devices that sense accelerations and angular rates in 3D so that vehicles and other devices can estimate their orientations, positions, and velocities. While traditionally large, heavy, and costly, using mechanical gyroscopes and stabilized platforms, the recent development of micro-electromechanical sensor (MEMS) IMUs that are small, light, and inexpensive has led to their adoption in many everyday systems such as cell phones, video game controllers, and commercial drones. MEMS IMUs, despite their advantages, have major drawbacks when it comes to accuracy and reliability. The idea of using more than one of these sensors in an array, instead of using only one, and fusing their outputs to generate an improved solution is explored in this thesis.

A detailed analysis and design of a navigation algorithm for a spacecraft to achieve precision lunar descent and landing is presented. The Inertial Navigation System (INS) was employed as the primary navigation system. To increase the accuracy and precision of the navigation system, the INS was integrated with aiding sensors - a star camera, an altimeter and a terrain camera. An unscented Kalman filter was developed to integrate the aiding sensor measurements with the INS measurements, and to estimate the current position, velocity and attitude of the spacecraft. The errors associated with the accelerometer and gyro measurements are also estimated as part of the navigation filter. An STK scenario was utilized to simulate the truth data for the navigation system. The navigation filter developed was tested and simulated, and from the results obtained, the position, velocity and attitude of the spacecraft were observed to be well estimated.