A study was undertaken to identify the effect of head flexion/extension on singing voice quality. The amplitude of the fundamental frequency (F0), and the singing power ratio (SPR), an indirect measure of singer’s formant activity, were measured. F0 and SPR scores at four experimental head positions were compared with the subjects’ scores at their habitual positions. Three vowels and three pitch levels were tested. F0 amplitudes and low frequency partials in general were greater with more extended head positions, while SPR increased with neck flexion. No effect of pitch or vowel was found. Gains in SPR appear to be the result of damping low frequency partials rather than amplifying those in the singer’s formant region. Raising the amplitude of F0 is an important resonance tool for female voices in the high range, and may be of benefit to other voice types in resonance, loudness, and laryngeal function.

This masters theses deal with computer control of the vertically rotative arm. The actuator of this arm is a direct current motor for its numeric control is used a programmable logic controller. The produce is several alternatives of a resolution varying in available quality at first. In this graduation theses is solved a user interface in the form of touch screen.

This thesis applies the methods of previous work in aerial magnetic field mapping and use in state estimation to the Virginia Tech Swing Space motion capture indoor facility. State estimation with magnetic field data acquired from a quadrotor is comparatively performed with Gaussian process regression, a multiplicative extended Kalman filter, and a particle filter to estimate the position and attitude of an uncrewed aircraft system (UAS) at any point in the motion capture testing environment. Motion capture truth data is used in the analysis. The first experimental method utilized in this thesis is Gaussian process regression. This machine learning tool allows us to create three-dimensional magnetic field maps of the indoor test space by collecting magnetic field vector data with a small UAS. Here, the maps illustrate the 3D magnetic field strengths and directions in the Virginia Tech Swing Space motion capture lab. Also, the magnetic field spatial variation of the test space is analyzed, yielding higher magnetic field gradient at lower heights above the ground. Next, the multiplicative extended Kalman filter is used with our Gaussian process regression magnetic field maps to estimate the attitude of the quadrotor. The results indicate an increase in attitude estimation accuracy when magnetic field mapping is utilized compared to when it is not. Here, results show that the addition of aerial magnetic field mapping leads to enhanced attitude estimation. Finally, the particle filter is utilized with support from our magnetic field maps to estimate the position of a small quadrotor UAS. The magnetic field maps allow us to obtain UAS position vectors by tracking UAS movement through magnetic field data. The particle filter gives three-dimensional position estimates to within 0.2 meters for five out of our eight test flights. The root mean square error is within 0.1 meters for each test flight. The effects of magnetic field spatial variation are also analyzed. The accuracy of position estimation is higher for two out the four flights in the maximum magnetic gradient area, while the accuracy is similar in both minimum and maximum gradient regions for the remaining two flights. There is evidence to support an increase in accuracy for high magnetic variation areas, but further work is needed to confirm utility for practical applications. / Master of Science / This thesis investigates airborne magnetic field mapping for the Virginia Tech Swing Space motion capture indoor facility. Position and attitude estimation with magnetic field data acquired from a small uncrewed aircraft system (UAS) is comparatively performed with multiple estimation methods. Motion capture truth data is used in analyses. The first data processing method is called Gaussian process regression. This machine learning tool allows us to create magnetic field maps of the indoor test space by averaging or regressing field estimates over collected UAS data. The maps illustrate the magnetic field strengths and directions over a three dimensional volume in the Virginia Tech Swing Space motion capture lab. Next, a multiplicative extended Kalman filter is used with our Gaussian process regression magnetic field maps to estimate UAS attitude. Results show improvement in attitude estimation accuracy when magnetic field mapping is utilized compared to when it is not. Finally, a particle filter method is utilized with our magnetic field maps to estimate UAS position. The particle filter estimates three-dimensional UAS position estimates to within 0.2 meters for five out of our eight test flights. The effects of magnetic field spatial variation are also analyzed, indicating the need for future work before magnetic field based position estimation can be practically applied.

This thesis presents a unified nonlinear optimization based speed and position estimation method in position sensorless control of interior permanent magnet synchronous motor (IPMSM) drives at wide speed range including standstill. The existing electromotive force (EMF) based sensorless methods are suitable for medium and high speed operation, but they can't be applied at low speed and standstill condition due to the reduced EMF values. The conventional saliency tracking based sensorless methods usually employ the continuous voltage or current injection at low speed including standstill condition. However, these methods degrade at high speed by introducing higher loss and torque ripples caused by the injection. Additionally, the initial rotor position needs to be detected at the machine startup to avoid the reverse rotation and to guarantee the delivery of the expected torque. Therefore, different position estimation techniques need to be combined in the controller at wide speed range, which increases the control system complexity. Hence, a unified nonlinear optimization based speed and position estimation method is proposed. At startup and standstill conditions, three steps are employed for initial position estimation. Step I employs pulse voltage injection in the stationary reference frame and a cost function which contains the knowledge of initial rotor position. The rotor position can be estimated by minimizing the cost function with injected voltage and induced current. Since the estimation results in Step I have an ambiguity of 180 degree, a generalized approach to magnetic polarity detection which exploits asymmetries in machine specific differential inductance profiles is employed as Step II. In order to improve the estimation accuracy, continuous sinusoidal voltage is injected in estimated rotor reference frame in Step III. A modified cost function is minimized based on the injected voltage and resulting current. At running state, cost functions which employ both speed and position as decision variables are proposed and utilized for estimation. The speed and position estimation can be delivered by minimizing the proposed cost functions based on the measurements of the stator voltage and current. Since only one position estimator exists in the drive system, the speed and position estimation is unified at wide speed range. The feasibility of the proposed estimation algorithms is validated with the prototype 5 KW IPMSM drives test bench. In order to benchmark the proposed estimation method, the performance of the proposed method was compared with existing sensorless control methods on the same prototype IPMSM drives test bench. Under the same test conditions, the proposed method outperforms with improved transient performance and steady state accuracy. Moreover, the proposed method is capable of delivering estimation with different voltage injection types and involving the nonlinear motor parameters, which makes this method more flexible in practice. Additionally, the capability of estimating speed and position with low sampling frequency also makes the application of the proposed method promising in high power AC motor drive systems. / Thesis / Doctor of Philosophy (PhD)

Lors de ce projet de maîtrise, la contribution de l’intégration de l’information visuelle et vestibulaire sur le contrôle postural debout a été investiguée chez une population jeune et saine. Huit sujets (4 hommes; 4 femmes) furent soumis à diverses combinaisons de stimulation vestibulaire galvanique (SVG) et de stimulation optocinétique (rotation d’un nuage de point dans le plan frontal; SOC) impliquant 2 conditions visuelles (vision non-perturbée, nO; SOC droite, OS) et à 3 conditions vestibulaires (absence de stimulation, nG; SVG droite, GR; SVG gauche, GL). Ainsi, les 6 conditions expérimentales furent: absence de stimulation sensorielle (nG_nO), stimulation sensorielle indépendante (nG_OS, GR_nO and GL_nO) et combinée (GR_OS and GL_OS). Les mouvements angulaires de la tête et du tronc ainsi que du centre de pression (CoP) furent principalement évalués. Lors des conditions indépendantes de SVG (GR_nO et GL_nO), les résultats démontrent un déplacement de la tête, du tronc et du CoP en direction de l’anode. La nG_OS entraîne un déplacement angulaire comparable de la tête et du tronc vers la droite. La somme algébrique des réponses aux stimulations indépendantes (nG_OS et GR_nO) n’était pas significativement différente des résultats des stimulations combinées dans la même direction. Par ailleurs, la somme algébrique des stimulations nG_OS et GL_nO ne différait pas des stimulations combinées (GL_OS) ou de l’absence de stimulation (nG_nO). Finalement, les stimulations vestibulaires et visuelles ont entraîné une réponse posturale différente au niveau du CoP et les informations vestibulaires et visuelles semblent s’additionner de façon linéaire.

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In order for a robot to operate autonomously in an environment, it must be able to locate itself within it. A robot's position and orientation cannot be directly measured by physical sensors, so estimating it is a non-trivial problem. Some sensors provide this information, such as the Global Navigation Satellite System (GNSS) and Motion capture (Mo-cap). Nevertheless, these sensors are expensive to set up, or they are not useful in environments where autonomous vehicles are often deployed. Our proposal explores a new approach to sensing for relative motion and position estimation. It consists of one vision sensor and a marker that utilizes moiré phenomenon to estimate the position of the vision sensor by using Convolutional Neural Networks (CNN) trained to estimate the position from the pattern shown on the marker. We share the process of data collection and training of the network and share the hyperparameter search method used to optimize the structure of the network. We test the trained network in a setup to evaluate its ability in estimating position. The system achieved an average absolute error of 1 cm, showcasing a method that could be used to overcome the current limitations of vision approaches in pose estimation.

Le placement des pieds en fonction de la position du corps est un facteur clé dans l’équilibre postural nécessaire à la marche mais les adaptations de cette relation géométrique pied-corps lorsque l’environnement l’exige demeure incomprises. Dans cette étude, dix jeunes participants masculins sains marchaient au niveau du sol et devaient enjamber un obstacle qui pouvait soudainement se déplacer vers l’avant au point du contact de pied un ou deux pas avant son franchissement. Le but était de perturber la position de l’obstacle avec deux délais temporels afin de quantifier la position relative entre le corps, les pieds et l’environnement afin de démontrer l’importance géométrique nécessaire pour un franchissement d’obstacle sécuritaire. Les diverses conditions expérimentales ont permis de montrer que la distance horizontale entre l’obstacle et les pieds précédent le franchissement de l’obstacle est une variable assez flexible dans la réussite de cette tâche. Au moment des contacts talons avant et après le franchissement de l’obstacle, la distance relative entre le bassin et le pied nouvellement posé au sol était maintenue pour toutes les conditions. Les résultats présentés dans ce mémoire suggèrent une priorisation de maintenir une relation géométrique stéréotypée entre le pied supportant le corps et le bassin et cela peu importe les distances horizontales entre les pieds et l’obstacle. / Foot placement in relation to the body is known to be a key control factor for level walking but how that body-environment geometry plays in adapting locomotion is still not well understood. For this study, ten healthy young male adults walked on a flat surface as well as when stepping over an obstacle that could move away from them at the point of foot contact one or two steps just before clearance. The goal was to perturb the position of the obstacle with two time delays to quantify relative positioning between the body, feet and environment in order to reveal stereotyped postural geometry necessary for an obstacle crossing task. The various experimental conditions allowed us to show that the horizontal distance between the obstacle and the feet can be modified without influencing successful clearance. At heel contacts before and after the obstacle crossing, the relative distance between the pelvis and the new contacting foot was maintained for all conditions. Those results suggest that there is a priority for the relative geometric relationship between the supporting foot and pelvis over foot proximity for obstacle crossing.

Wireless communication has enjoyed explosive growth over the past decade. As demands for increased capacity and quality grow, improved methods for harnessing the multipath wireless channel must be developed. The use of adaptive antenna arrays is one area that shows promise for improving capacity of wireless systems and providing improved safety through position location capabilities. These arrays can be used for interference rejection through spatial filtering, position location through direction finding measurements, and developing improved channel models through angle of arrival channel sounding measurements. This thesis provides an overview of the technical challenges involved in position location of wireless users and details the hardware development of a multi-sensor testbed at the Mobile and Portable Radio Research Group at Virginia Tech. This testbed is to be used for position location experiments as well as a host of other adaptive signal processing applications. / Master of Science

No / To examine the independent contribution of various stimulus characteristics to positional judgements, we measured vernier alignment performance for three types of Gabor stimuli. In one, only the contrast envelope of the upper and lower stimulus elements was offset, with the luminance-modulated carrier grating remaining in alignment. In the second, only the carrier grating was offset. In the third, both carrier and envelope were offset together. Performance was examined over a range of element separations. When both cues are available, thresholds for small separations are dominated by carrier offset information and are inversely proportional to carrier frequency. At large separations, thresholds are governed by the spatial scale characteristics of the envelope. For broad-band stimuli such as lines, bars or dots typically used for vernier acuity, their higher frequency content can be used when separations are small, but as separation increases a smooth transition between the scales that determine threshold results in the continuum known as Weber's law for position. That is, with increasing separation, larger scales must be used, and thresholds increase in direct proportion to 1/frequency.