This research will investigate the problem of position estimation for planetary rovers. Diverse algorithmic filters are available for collecting input data and transforming that data to useful information for the purpose of position estimation process. The terrain has sandy soil which might cause slipping of the robot, and small stones and pebbles which can affect trajectory. The Kalman Filter, a state estimation algorithm was used for fusing the sensor data to improve the position measurement of the rover. For the rover application the locomotion and errors accumulated by the rover is compensated by the Kalman Filter. The movement of a rover in a rough terrain is challenging especially with limited sensors to tackle the problem. Thus, an initiative was taken to test drive the rover during the field trial and expose the mobile platform to hard ground and soft ground(sand). It was found that the LSV system produced speckle image and values which proved invaluable for further research and for the implementation of data fusion. During the field trial,It was also discovered that in a at hard surface the problem of the steering rover is minimal. However, when the rover was under the influence of soft sand the rover tended to drift away and struggled to navigate. This research introduced the laser speckle velocimetry as an alternative for odometric measurement. LSV data was gathered during the field trial to further simulate under MATLAB, which is a computational/mathematical programming software used for the simulation of the rover trajectory. The wheel encoders came with associated errors during the position measurement process. This was observed during the earlier field trials too. It was also discovered that the Laser Speckle Velocimetry measurement was able to measure accurately the position measurement but at the same time sensitivity of the optics produced noise which needed to be addressed as error problem. Though the rough terrain is found in Mars, this paper is applicable to a terrestrial robot on Earth. There are regions in Earth which have rough terrains and regions which are hard to measure with encoders. This is especially true concerning icy places like Antarctica, Greenland and others. The proposed implementation for the development of the locomotion system is to model a system for the position estimation through the use of simulation and collecting data using the LSV. Two simulations are performed, one is the differential drive of a two wheel robot and the second involves the fusion of the differential drive robot data and the LSV data collected from the rover testbed. The results have been positive. The expected contributions from the research work includes a design of a LSV system to aid the locomotion measurement system. Simulation results show the effect of different sensors and velocity of the robot. The kalman filter improves the position estimation process.

This research project on the campus of Southern Illinois University Carbondale is an extension to the inquiry into the feasibility and reliability of the technology known as Digital Laser Speckle Image Correlation (DiLSIC). This is a hybrid approach of combining two existing technologies. The first being Digital Image Correlation (DIC) which is a nondestructive evaluation commonly used to find displacement, in-plane strain, as well as deformation. The second being the of laser speckle patterns. This hybrid has achieved level of resolution measured to be 3.4μ. DiLSIC increases the application ability of the DIC technique to situations that generally would not be an option to use. DiLSIC needs no artifact speckle patterns to be applied to the specimen as a preparation for nondestructive testing. In DIC testing, the surface of a specimen must artifact speckles applied to the subject surface. Often the application of artifact speckles is not desirable or possible. DiLSIC is an acceptable alternative to the previously discussed industry-wide practice. This method broadens the usage of the DIC technique to situations which previously were not possible. This technology can identify, quantify, and detect the distribution of strain and stress concentrations in composite structures. For this study, a honeycomb-backed glass fiber reinforced polymer (GFRP) panel from a Cessna aircraft exterior luggage door was obtained and a defect panel is created. The panel is constructed with one area containing a repair compliant with manufacturer standardized methods and a repair area is not compliant and consists of multiple incorrect repair steps. An area with no repair is also tested to act as a control for comparison and quantification. The results for the inspected areas showed a linear strain increase in the noncompliant repair. The data plot for the compliant repair showed a trend of following the same basic curve as the no repair area. A verification process follows the DiLSIC testing consisting of using Infrared Thermography, Air-coupled ultrasonic, and white light artifact speckle DIC. These tests show DiLSIC is a viable alternative to the testing that is available in the industry. DiLSIC can detect defect location, size, geometry and map strain to determine the difference between compliant and noncompliant repairs when compared to a base level non-repair area

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1982. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Includes bibliographical references. / by Sun Tong Lau. / M.S.

It is well known now that there exists a coupling between functional brain activity and regional blood flow response in the somatosensory cortex and other cortical areas. Various modalities, including functional magnetic resonance imaging and optical imaging (intrinsic signals as well as fluorescence), have been developed in the past to map functional brain activity. The complexity and fundamental physical constraints of the instruments preclude functional imaging in awake, behaving small animals. This thesis presents the method of Laser Speckle Imaging (LSI) of brain with high spatial and temporal resolution, and potential for imaging awake and behaving animals. The method has the potential to map brain activation with high sensitivity and spatiotemporal resolution without using any exogenous contrast agents. In LSI, scattered laser light with different paths produces a random interference pattern known as speckle, fluctuations of which contain information about the motion of particles in the underlying medium. A post-processing step is needed to extract information out of the speckle images, two of which we introduce in details. Our first method is based on Laser speckle contrast analysis (LASCA), which has been demonstrated as a full-field method for imaging the cerebral blood flow (CBF). However, conventional LASCA is limited to extremely low dynamic range because of the ambient background field, dark current and anomalies in the circuits of CCD camera, which makes it difficult to analyze the spatiotemporal variabilities in CBF. In this study, we propose an enhanced laser speckle contrast analysis (eLASCA) method to improve the dynamic range of LASCA based on monotonic point transformation (MPT). In addition, eLASCA greatly improves the CBF visualization, which is very helpful in demonstrating the details of CBF change. Our second method involves the second order features (SOFs) of the image; they are derived from the cooccurrence matrix that in turn was calculated over the same spatial and temporal window than for the contrast. The image quality metrics - equivalent number of looks, entropy and objective quality – showed superior performance of the SOFs comparing to the contrast analysis. / --

Doctor of Philosophy / Department of Mechanical and Nuclear Engineering / B. Terry Beck / The current experimental method to determine the transfer length in prestressed concrete members consists of measuring concrete surface strains before and after de-tensioning with a mechanical strain gage. The method is prone to significant human errors and inaccuracies. In addition, since it is a time-consuming and tedious process, transfer lengths are seldom if ever measured on a production basis. A rapid, non-contact method for determining transfer lengths in prestressed concrete members has been developed. The new method utilizes laser-speckle patterns that are generated and digitally recorded at various points along the prestressed concrete member. User-friendly software incorporating robust and fast digital image processing algorithms was developed by the author to extract the surface strain information from the captured speckle patterns. Based on the laser speckle measurement technique, four (4) successively improved generations of designs have been made. A prototype was fabricated for each design either on an optical breadboard for concept validation, or in a portable self-contained unit for field testing. For each design, improvements were made based on the knowledge learned through the testing of the previous version prototype. The most recent generation prototype, incorporating a unique modular design concept and self-calibration function, has several preferable features. These include flexible adjustment of the gauge length, easy expansion to two-axis strain measurement, robustness and higher accuracy. Extensive testing has been conducted in the laboratory environment for validation of the sensor’s capability in concrete surface strain measurement. The experimental results from the laboratory testing have shown that the measurement precision of this new laser speckle strain measurement technique can easily achieve 20 microstrain. Comparison of the new sensor measurement results with those obtained using traditional strain gauges (Whittemore gauge and the electrical resistance strain gauge) showed excellent agreement. Furthermore, the laser speckle strain sensor was applied to transfer length measurement of typical prestressed concrete beams for both short term and long term monitoring. The measurement of transfer length by the sensor was unprecedented since it appears that it was the first time that laser speckle technique was applied to prestressed concrete inspection, and particularly for use in transfer length measurement. In the subsequent field application of the laser speckle strain sensor in a CXT railroad cross-tie plant, the technique reached 50 microstrain resolution, comparable to what could be obtained using mechanical gauge technology. It was also demonstrated that the technique was able to withstand extremely harsh manufacturing environments, making possible transfer length measurement on a production basis for the first time.

Digital Laser Speckle Image Correlation (DiLSIC) is a technique that utilizes a laser generated speckle pattern with Digital Image Correlation (DIC). This technology eliminates the need to apply an artifact speckle pattern to the surface of the material of interest, and produces a finer speckle pattern resulting in a more sensitive analysis. This investigation explores the parameters effecting laser speckle patterns for DIC and studies DiLSIC as a tool to measure surface strain and detect subsurface defects on pressure vessels. In this study a 632.8 nm 30 mW neon-helium laser generated the speckle pattern by passing through the objective end of an objective lens. All experiments took place in a lab setting on a high performance laminar flow stabilizer optical table.This investigation began with a deeper look at the camera settings that effect the effectiveness of using laser speckles with DIC. The first studies were concentrated on the aperture size (f-stop), shutter speed, and gain (ISO) of the camera. Through a series of zero-correlation studies, translation tests, and settings studies, it was discovered that, much like white light DIC, an increased gain allowed for more noise and less reliable measurements when using DiLSIC. It was shown that the aperture size and shutter speed will largely depend on the surface composition of the material, and that these factors should be investigated with each new sample of different surface finish.To determine the feasibility of using DiLSIC on pressure vessels two samples were acquired. The first was a standard ASTM filament wound composite pressure vessel (CPV) which had an upper load limit of 40 psi. The second was a plastic vessel that had internal subsurface defects added with the use of an air pencil grinder. Both vessels were put under a pressure load with the use of a modified air compressor that allowed for multiple loading cycles through the use of a pressure relief valve. The CPV was mapped out in 10-degree increments between the 90° and 180° markings that were on the pressure vessel, occurring in three areas, each one inch apart. The CPV had a pressure load applied to at 10, 20, 30,and 40 psi. DiLSIC was able to measure increasing displacement with increased loading on the surface of the CPV, however with a load limit of 40 psi no strains were detected. The plastic vessel had known subsurface defects, and these areas were the focus of the investigation. The plastic vessel was loaded with a pressure load at 5, 10, 12, 15, 17, and 20 psi. The 5 psi loaded image was used as a reference image for the correlation and decorrelation consistently occurred at 20 psi. This investigation proved that DiLSIC can detect and locate subsurface defects through strain measurement. The results were verified with traditional white light DIC, which also showed that the subsurface defects on pressure vessels were detectable. The DIC and DiLSIC results did not agree on maximum strain measurement, with the DiLSIC prediciting much larger strains than traditional DIC. This is due to the larger effect out-of-plane displacement has on DiLSIC. DiLSIC was able to detect subsurface defects on a pressure vessel. The median measured hoop strain was in agreement for DiLSIC, DIC and the predicted hoop strain for a wall thickness of 0.1 inches. However, DiLSIC also produced unreliable maximum strain measurements. This technique shows potential for future applications, but more investigations will be needed to implement it for industrial use. A full investigation into the parameters surrounding this technique, and the factors that contribute the most to added noise and unreliability should be conducted. This technology is being developed by multiple entities and shows promising results, and once further advanced could be a useful tool for rapid surface strain measurement and subsurface defect detection in nondestructive evaluation applications. Therefore, it is recommended to continue further investigations into this technology and its applications.

<p>This thesis describes the development of a low-cost, low-power, accurate sensor designed for precise, feedback control of an autonomous vehicle to a hitch. Few studies have been completed on the hitching problem, yet it is an important challenge to be solved for vehicles in the agricultural and transportation industries. Existing sensor solutions are high cost, high power, and require modification to the hitch in order to work. Other potential sensor solutions such as LiDAR and Digital Fringe Projection suffer from these same fundamental problems. </p> <p>The solution that has been developed uses an active stereo vision system, combining classical stereo vision with a laser speckle projection system, which solves the correspondence problem experienced by classic stereo vision sensors. A third camera is added to the sensor for texture mapping. As a whole, the system cost is $188, with a power usage of 2.3 W.</p> <p>To test the system, a model test of the hitching problem was developed using an RC car and a target to represent a hitch. In the application, both the stereo system and the texture camera are used for measurement of the hitch, and a control system is implemented to precisely control the vehicle to the hitch. The system can successfully control the vehicle from within 35⁰ of perpendicular to the hitch, to a final position with an overall standard deviation of 3.0 mm of lateral error and 1.5⁰ of angular error. Ultimately, this is believed to be the first low power, low cost hitching system that does not require modification of the hitch in order to sense it. </p>

PURPOSE: This study aims to quantify the retinal vascular blood flow in eyes affected by unilateral central retinal vein occlusions (CRVO) or branch retinal vein occlusions (BRVO). We created and explored a new, unitless metric for the severity of these diseases: relative blood flow (RBF). We then contextualized RBF in terms of patient demographics, ocular presentation and other systemic conditions, as well as explored its efficacy as a predictor of future outcomes. METHODS: Data was collected from 20 control subjects and 32 patients with clinically diagnosed retinal vein occlusions (15 CRVO and 17 BRVO). Laser speckle flowgraphy was then used to quantify retinal vascular blood flow in terms of mean blur rate, a metric shown to be highly heterogeneous between patients but fairly consistent in intra-patient repeated measurements over time. After confirming this and establishing a strong correlation between a healthy patient’s two eyes, we used an RVO patient’s fellow eye as a nondiseased expectation and presented relative blood flow as the ratio between their diseased and healthy eye. We then correlated this data with demographic variables and disease characteristics from patients’ medical history. RESULTS: We found an average blood flow decrease of 26% in CRVO eyes relative to healthy eyes in the same patients and an average decrease of 7% in BRVO eyes. In CRVO, duration of occlusion, central macular thickness, intraocular pressure, diabetes, previous laser and injection treatments, and an injection within three months after blood flow measurement were significantly associated with relative blood flow. In BRVO, no demographic variables or disease characteristics were significantly associated with relative blood flow. CONCLUSIONS: Relative blood flow represents a promising new, consistent and informative metric for quantifying the severity of unilateral retinal vein occlusions. With both descriptive and predictive properties in eyes with CRVO, future work should explore its great potential.

Cerebral blood flow (CBF) is a biomarker for brain health, facilitating the advancement of studies on brain states in both healthy and diseased individuals. While there are indirect approaches of CBF based on human physiology, there is a need for technology that measures CBF directly and continuously. Laser speckle contrast imaging (LSCI) is an optical modality that measures changes in CBF by analyzing the blurring of speckle patterns. LSCI has been extensively employed to obtain two-dimensional blood flow maps in thinned-skull mouse brains and has found diverse applications in studies involving the retina, skin, and strokes. However, the effectiveness of LSCI has been limited in animal models due to the lack of depth-sensitivity. Speckle contrast optical spectroscopy (SCOS), an extension of LSCI for non-invasive human brain studies, has recently been developed to probe dynamics in deeper tissue regions by increasing the source-detector separation. But the low photon flux detected from human brain limits the usability of SCOS for brain activation measurements. To address these limitations, this thesis focuses on advancements made in laser speckle technology for improved measure of blood flow in both animal and human brains. Firstly, analytical and numerical methods have been developed for an interferometric LSCI system, which employs a heterodyne detection scheme to enhance CBF within the coherence volume in small animals. Next, a dynamic speckle model (DSM) is created to simulate the temporal evolution of the speckle patterns. DSM has been utilized to quantify the impact of noise sources on speckle contrast, particularly relevant in human brain measurements utilizing SCOS where low photon counts is a norm. Finally, a fiber-based SCOS system with a long source-detector separation has been presented to perform human brain activation studies. Through experiments involving three healthy subjects performing a mental subtraction task, changes in brain activation have been observed. Importantly, the SCOS system has demonstrated an order of magnitude improvement in the signal-to-noise ratio compared to the state-of-the-art diffuse correlation spectroscopy system.These methods serve as valuable tools to augment existing LSCI systems and promoting the widespread adoption of SCOS in human brain activation studies thus contributing to the development of future non-invasive, continuous, and cost-effective blood flow monitoring devices.

Lights is almost always detected by its interaction with matter. One of these interaction phenomena is the scattering of light by small particles. A model is developed that estimates the amount of energy that is scattered towards a detector from a beam given the locations of the source, detector and particle. This collection of particles is allowed to be very dense so that a photon scattered from the beam can be scattered several times before leaving the scattering medium. By considering the single-scatter component and multiple-scatter component separately, the model retains the characteristics of both types.