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Human motion collected in real-world environments without instruction from researchers - or natural motion - is an understudied area of the field of motion capture that could increase the efficacy of assistive devices such as exoskeletons, robotics, and prosthetics. With this goal in mind, a natural motion dataset is presented in this thesis alongside algorithms for analyzing human motion. The dataset contains more than 36 hours of inertial motion capture data collected while the 16 participants went about their lives. The participants were not instructed on what actions to perform and interacted freely with real-world environments such as a home improvement store and a college campus. We apply our dataset in two experiments. The first is a study into how manual material handlers lift and bend at work, and what postures they tend to use and why. Workers rarely used symmetric squats and infrequently used symmetric stoops typically studied in lab settings. Instead, they used a variety of different postures that have not been well-characterized such as one-legged lifting and split-legged lifting. The second experiment is a study of how to infer human motion using limited information. We present methods for inferring human motion from sparse sensors using Transformers and Seq2Seq models. We found that Transformers perform better than Seq2Seq models in producing upper-body and full-body motion, but that each model can accurately infer human motion for a variety of postures like sitting, standing, kneeling, and bending given sparse sensor data. / Master of Science / To better design technology that can assist people in their daily lives, it is necessary to better understand how people move and act in the real-world with little to no instruction from researchers. Personal assistants such as Alexa and Google Assistant have benefited from what researchers call natural language processing. Similarly, natural motion processing will be useful for everyday assistive devices like prosthetics and exoskeletons. Unscripted human motion in real-world environments - or natural motion - has been made possible with recent advancements in motion capture technology. In this thesis, we present data from 16 participants who wore a suit that captures accurate human motion. The dataset contains more than 36 hours of unscripted human motion data in real-world environments that is usable by other researchers to develop technology and advance our understanding of human motion. In addition, we perform two experiments in this thesis. The first is a study into how manual material handlers lift and bend at work, and what postures they tend to use and why. The second is a study into how we can determine what a person's body is doing with a limited amount of information from only a few sensors. This study could be useful for making commercial devices like smartphones, smartwatches, and smartglasses more valuable and useful.

Wearable computers and e-textiles are becoming increasingly widespread in today's society. Motion capture is one of the many potential applications for on-body electronic systems. Previous work has been performed at Virginia Tech's E-textiles Laboratory to design a framework for a self-contained loose fit motion capture system. This system gathers information from sensors distributed throughout the body on a "smart" garment. This thesis presents the hardware and software components of the framework, along with improvements made to it. This thesis also presents an analysis of both the on-body and off-body network communication to determine how many sensors can be supported on the garment at a given time. Finally, this thesis presents a method for determining the accuracy of the smart garment and shows how it compares against a commercially available motion capture system. / Master of Science

The robotics field has grown in recent years to a point where unmanned systems are no longer limited by their capabilities. As such, the mission profiles for unmanned systems are becoming more and more complicated, and a demand has risen for the deployment of unmanned systems into the most complex of environments. Additionally, the objectives for unmanned systems are once more complicated by the necessity for beyond line of sight teleoperation, and in some cases complete vehicle autonomy. Such systems require adequate sensory devices for appropriate situational awareness. Additionally, a large majority of what is currently being done with unmanned systems requires visual data acquisition. A stereo vision system is ideal for such missions as it doubles as both an image acquisition device, and a range finding device. The 2D images captured with a stereo vision system can be mapped to three dimensional point clouds with reference to the optic center of one of the stereo cameras. While stand alone commercial stereo vision systems are capable of doing just that, the GPS/INS aided stereo vision system also has integrated 3-axis accelerometers, 3-axis gyros, 3-axis magnetometer, and GPS receiver allowing for the measurement of the system's position and orientation in global coordinates. This capability provides the potential to geo-reference the 3D data captured with the stereo camera. The GPS/INS aided stereo vision system integrates a combination of commercial and in-house developed devices. The total system includes a Point Grey Research Bumblebee stereovision camera, a Versalogic PC104 computer, a PCB designed for sensor acquisition and power considerations, and a self contained battery. The entire system is all contained within a 9.5â x 5â x 6.5â aluminum enclosure and weighs approximately 6 lbs. The system is also accompanied with a graphical user interface which displays the geo-referenced data within a 3D virtual environment providing adequate sensor feedback for a teleoperated unmanned vehicle. This thesis details the design and implementation of the hardware and software included within this system as well as the results of operation. / Master of Science

Autonomous Underwater Vehicles (AUVs) are currently being used for many underwater tasks such as mapping underwater terrain, detection of underwater objects, and assessment of water quality. Possible uses continue to grow as the vehicles become smaller, more agile, and less expensive to operate. However, trade-offs exist between making less expensive, miniature AUVs and the quality at which they perform. One area affected by cost and size is the onboard navigation system. To achieve the challenges of low-cost rate sensors, this thesis examines calibration methods that are suitable for identifying calibration coefficients in low-cost MEMS gyros. A brief introduction to underwater navigation is presented and is followed by the development of a model to describe the operation of a rate gyro. The model uses the integral relationship between angular rate and angular position measurements. A compass and two tilt sensors provide calibrated angular position data against which the three single axis gyros are compared to obtain an error signal describing errors present in the angular rate measurements. A calibration routine that adaptively identifies error parameters in the gyros is developed. Update laws are chosen to recursively apply estimated error parameters to minimize the system error signal. Finally, this calibration method is applied to a simple dead reckoning algorithm in an attempt to measure the improvements calibration provides. / Master of Science

Inertial navigation systems require a precise knowledge of gravity to function properly. The inability of models to account for the small amplitude, short wavelength components of the gravity field leads to errors which are frequently viewed as random; these random errors can introduce a significant cumulative impact on system performance. A model is studied which, in the context of an appropriate scaling, consists of a gravity field having a known deteministic long scale behavior and an unknown random short scale behavior. The short wavelength random fluctuations are assumed to satisfy a strong mixing (asymptotic independence) property; no a priori stationary or isotropy assumptions are made. Results of Khas'minskii (Theory of Probability and Its Applications, Vol. XI, No. 2, 1966, pp 211-228) are extended and applied. In an appropriate asymptotic limit, the vehicle motion is approximated by the sum of a deterministic trajectory and a Gauss-Markov fluctuation process. / Ph. D.

Z-Pinch IFE (Inertial Fusion Energy) reactor designs will likely utilize high yield targets (~ 3 GJ) at low repetition rates (~ 0.1 Hz). Appropriately arranged thick liquid jets can protect the cavity walls from the target x-rays, ions, and neutrons. However, the shock waves and mechanical loadings produced by rapid heating and evaporation of incompressible liquid jets may be challenging to accommodate within a small reactor cavity. This investigation examines the possibility of using two-phase compressible (liquid/gas) jets to protect the cavity walls in high yield IFE systems, thereby mitigating the mechanical consequences of rapid energy deposition within the jets. Two-phase, free, vertical jets with different cross sections (planar, circular, and annular) were examined over wide ranges of liquid velocities and void fractions. The void fraction and bubble size distributions within the jets were measured; correlations to predict variations of the slip ratio and the Sauter mean diameter were developed. An exploding wire system was used to generate a shock wave at the center of the annular jets. Attenuation of the shock by the surrounding single- or two-phase medium was measured. The results show that stable coherent jets can be established and steadily maintained over a wide range of inlet void fractions and liquid velocities, and that significant attenuation in shock strength can be attained with relatively modest void fractions (~ 1%); the compressible two-phase jets effectively convert and dissipate mechanical energy into thermal energy within the gas bubbles. The experimental characteristics of single- and two-phase jets were compared against predictions of a state-of-art CFD code (FLUENT®). The data obtained in this investigation will allow reactor system designers to predict the behavior of single- and two-phase jets and quantify their effectiveness in mitigating the consequences of shock waves on the cavity walls in high yield IFE systems.

This thesis reports the development of micromachined accelerometers and gyroscopes that can be used for micromachined inertial measurement units (IMUs). Micromachined IMUs started to appear in the market in the past decade as low cost, moderate performance alternative in many inertial applications including military, industrial, medical, and consumer applications. In the framework of this thesis, a number of accelerometers and gyroscopes have been developed in three different fabrication processes, and the operation of these fabricated devices is verified with extensive tests. In addition, the fabricated accelerometers were combined with external readout electronics to obtain hybrid accelerometer systems, which were tested in industrial test facilities. The accelerometers and gyroscopes are designed and optimized using the MATLAB analytical simulator and COVENTORWARE finite element simulation tool. First set of devices is fabricated using a commercial foundry process called SOIMUMPs, while the second set of devices is fabricated using the electroplating processes developed at METU-MET facilities. The third set of devices is designed for a new advanced process based on DRIE, which is under development. Mechanical and electrical test results of the fabricated accelerometers and gyroscopes are in close agreement with the designed values. The testing of the SOI and nickel accelerometers is also performed in industrial test environments. In order to perform these tests, accelerometers are hybrid connected to commercially available capacitive readout circuits. These accelerometer systems require only two DC supply voltages for operation and provide an analog output voltage related to the input acceleration. The industrial tests show that the SOI accelerometer system yields a 799 &micro / g/&amp / #8730 / Hz average noise floor, a 1.8 mg/&amp / #8730 / Hz peak noise floor, a 22.2 mV/g sensitivity, and a 0.1 % nonlinearity, while the nickel accelerometer system yields a 228 &micro / g/&amp / #8730 / Hz average noise floor, a 375 &micro / g/&amp / #8730 / Hz peak noise floor, a 1.02 V/g sensitivity, and a 0.23 % nonlinearity. Long-term drift components of the accelerometers are determined to be smaller than 20 mg. These systems are the highest performance micromachined accelerometer systems developed in Turkey, and they can be used in implementation of a national inertial measurement unit.

This master thesis report presents the developement of an INS/GPS navigation loop written in ANSI C++ using a standard matrix library. The filter have been tested on an Unmanned Aerial Vehicle (UAV) called Brumby. Here data have been logged from the Inertial Measurement Unit (IMU) and the Global Positioning System (GPS) receiver. This data have then been postprocessed and run through the navigation filter for estimation of position, attitude and velocity of the vehicle during the flights. The error feedback to the Inertial Navigation System (INS) is done with a complement filter implemented using a kalman filter written in information form.The resulting navigation filter estimates the attitude within two degrees with 95% confidence and the position within two meter using 95% confidence. / <p>Validerat; 20101217 (root)</p>

QC 20110412