Browsing by Subject "Navigation"

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ACC 2013, An Airborne Experimental Test Platform: From Theory to Flight Companion Software Package
(2014-07-23) Dorobantu, Andrei
Collaborative data processing in wireless sensor networks.
(2008-12) Zhang, Qingquan
Wireless Sensor Networks (WSNs) have been used in many application domains, such as target tracking or environmental monitoring. Due to limitations of power supplies, power management and power efficient target tracking techniques have become more and more critical. In this dissertation, systematic approaches are proposed to address the above problems. In particular, efficient energy-aware architectural design aspects of a sensor network are developed, with the goal to reduce the control scheduling algorithm complexity and the power consumption of various components while maintaining the data quality and performance requirements. Research results on an efficient error-bounded sensing scheduling algorithm, a novel collaborative global error implied assisted scheduling algorithm(CIES) and fast target localization for mobile wireless sensor network are presented. Dynamic scheduling management in wireless sensor networks is one of the most challenging problems in long-lifetime monitoring applications. In this thesis, we propose and evaluate a novel data correlation-based stochastic scheduling algorithm, called Cscan. Our system architecture integrates an empirical data prediction model with a stochastic scheduler to adjust a sensor node’s operational mode. We demonstrate that substantial energy savings can be achieved while assuring that the data quality meets specified system requirements. We have evaluated our model using a light intensity measurement experiment on a Micaz testbed, which indicates that our approach works well in an actual wireless sensor network environment. We have also investigated the system performance using Wisconsin- Minnesota historical soil temperature data. The simulation results demonstrate that the system error meets specified error tolerance limits and up to a 70 percent savings in energy can be achieved in comparison to fixed probability sensing schemes. Building on the results obtained from CScan, we further propose and evaluate a collaborative error implication assisted scheduling algorithm, called CIES. This computationdistributive system integrates an implied-error based prediction model together with a stochastic scheduler to adjust neighboring sensors’ operational modes during the occurrence of rare or unusual sensing events. We demonstrate that substantial energy savings can be achieved while also satisfying a global error constraint. We have conducted extensive simulations to investigate the system performance by using realistic Wisconsin-Minnesota historical soil temperature data. The simulation results demonstrate that the system error meets the specified error tolerance and produces up to a 60 percent energy savings compared several fixed probability sensing references. In order to manage data link quality, a distributed sensor network with mobility provides an ideal system platform for surveillance as well as search and rescue applications. We consider a system design consisting of a set of autonomous robots communicating with each other and with a base station to provide image and other sensor data. A robot-mounted sensor which detects interesting information will coordinate with other mobile robots in its vicinity to stream its data back to the base station in a robust and energy-efficient fashion. The system is partitioned into twin sub-networks in such a way that any transmitting sensor will pair itself with another nearby robot to cooperatively transmit its data in a multiple-input, multiple-output (MIMO) fashion. At the same time, other robots in the system will cooperatively position themselves in such a way that the overall link quality is maximized and the total transmission energy in minimized. We efficiently simulate the system’s behavior using the Transaction Level Modeling (TLM) capability of SystemC. Our results demonstrate the efficiency of our simulation approach and provide insights into operation of the network. Finally, a fast target acquisition algorithm without the assistance of a map, call GraDrive, is introduced for search and rescue applications. We evaluate a novel gradientdriven method, which integrates per-node prediction with global collaborative prediction to estimate the position of a stationary target and to direct mobile nodes towards the target along the shortest path. We demonstrate that a high accuracy in localization can be achieved much faster than with random walk models, without any assistance from stationary sensor networks. We evaluate our model through a light-intensity matching experiment using MicaZ motes, which indicates that our model works well in a wireless sensor network environment. Through simulation, we demonstrate almost a 40% reduction in the target acquisition time, compared to a random walk model, while obtaining a small error in the estimate of the target position.
Data for Validating a Model of Architectural Hazard Visibility with Low-Vision Observers
(2020-07-22) Liu, Siyun; Thompson, William B.; Liu, Yichen; Shakespeare, Robert A.; Kersten, Daniel J.; Legge, Gordon E.; liux4433@umn.edu; Liu, Siyun; Department of Psychology, University of Minnesota; School of Computing, University of Utah; Department of Theatre, Drama, and Contemporary Dance, Indiana University Bloomington
Pedestrians with low vision are at risk of injury when hazards, such as steps and posts, have low visibility. This study aims at validating the software implementation of a computational model that estimates hazard visibility. The model takes as input a photorealistic 3-D rendering of an architectural space, and the acuity and contrast sensitivity of a low-vision observer, and outputs estimates of the visibility of hazards in the space. Our experiments explored whether the model can predict the likelihood of observers correctly identifying hazards. We tested fourteen normally sighted subjects with blur goggles that reduced acuity to 1.2 logMAR or 1.6 logMAR and ten low-vision subjects with acuities ranging from 0.8 logMAR to 1.6 logMAR. Subjects viewed computer-generated images of a walkway containing five possible targets ahead—large step up, large step-down, small step up, small step down, or a flat continuation. Each subject saw these stimuli with variations of lighting and viewpoint in 250 trials and indicated which of the five targets was present. The model generated a score on each trial that estimated the visibility of the target. If the model is valid, the scores should be predictive of how accurately the subjects identified the targets. We used logistic regression to examine the correlation between the scores and the participants’ responses. For twelve of the fourteen normally sighted subjects with artificial acuity reduction and all ten low-vision subjects, there was a significant relationship between the scores and the participant’s probability of correct identification. These experiments provide evidence for the validity of a computational model that predicts the visibility of architectural hazards. The software implementation of the model may be useful for architects to assess the visibility of hazards in their designs, thereby enhancing the accessibility of spaces for people with low vision.
Design and Evaluation of Dynamic Field-of-View Restriction Techniques to Mitigate Cybersickness in Virtual Reality
(2022-09) Wu, Fei
Although virtual reality has been gaining in popularity, users continue to report discomfort during and after the use of VR applications, and many experience symptoms associated with cybersickness. To mitigate this problem, dynamic field-of-view (FOV) restriction is a common technique that has been widely implemented in commercial VR games. FOV restriction artificially reduces the field of view during movement to limit optical flows and reduce discomfort caused by the mismatch between virtual motion and physical motion. FOV restriction has been shown in numerous studies to improve comfort and enhance user experience in virtual reality. The standard dynamic FOV restriction is created by adding a symmetrical black opaque mask at the periphery of the user’s filed-of-view and its size changes only with the user's virtual velocity. It does not take into account any differences in users, virtual environments, or other usage conditions. This simplistic implementation leads to some limitations. The first limitation is that the FOV restriction reduces users' visibility of the virtual environment and can negatively impact their subjective experience. The second limitation is that the unblocked imagery when applying restrictor is usually in the center of the field of view, which is incompatible with the users' eye movements during locomotion. The third limitation is that the classical restrictor is scaled by the velocity and angular velocity of users' virtual movements. This design assumes that users feel the same cybersickness when they experience the same velocity, which is unrealistic. Beyond these limitations, there is a lack of scientific understanding of how to effectively apply FOV restrictions for different types of virtual environments and virtual motions. This thesis presents four major contributions to the existing dynamic FOV restriction research. First, I present a novel technique known as passthrough FOV restriction, which combines the dynamic field of view modification with rest frames generated from 3D scans of the physical environment. The informal testing suggests that this approach is a promising method for reducing motion sickness and improving user safety at the same time. Secondly, I present a novel asymmetric field-of-view restrictor known as the ground-visible restrictor, which maintains the visibility of the ground plane during movement. User studies showed that ground-visible FOV restriction offers benefits for user comfort, postural stability, and a subjective sense of presence. Thirdly, I provide another variant of FOV restriction, referred to as the side restrictor, which expands side visibility and maintains restriction during rotation. A user study evaluated the new technology and demonstrated its benefits in reducing cybersickness and discomfort and improving visibility. Finally, I present an adaptive restrictor that uses the optical flow amount to determine the position and size of the restriction. A mixed design study investigated its performance and confirmed its superiority over traditional restrictors in providing a better subjective user experience.
Electrochemical Deposition of Magnetics Based Sensors
(2019-12) Hein, Matthew
Within the context of this thesis, advancements in sensor technology are driven in three separate applications. In each application electrochemistry is used as one of the primary fabrication steps, and magnetic phenomena are sensed in order to convey information about the different systems. The medical device industry is an area where various sensors are seeing increased use. Electromagnetic catheter tracking is an application that depends on high-quality magnetic sensors. The size of the sensor is a significant design constraint in catheters. Investigation of a microfabricated inductive sensor is pursued in chapter 4 of this thesis. High shape anisotropy inductive structures utilizing etched aluminum oxide as electroplating templates are investigated through first-order modeling and fabrication process development. Results show that the AAO is capable of producing high aspect ratio inductive structures though further development would be needed to achieve the consistency in etching required for large scale device fabrication. Biomimetic devices are another area of scientific interest where magnetics can play a role. Electroplated magnetic nanowires can act like large arrays of cilia. In chapter 5, biomimetic nanowire arrays are fabricated into microfluidic channels, and their movement sensed via a magnetic sensor. The nanowires provide a magnetic field that bends as fluid flows through the channel which enables a simple flow measurement through microfluidic channels. Similarly, a low frequency (>10Hz) vibration sensor is demonstrated utilizing a nanowire array above a magnetic sensor. Vibration of the sensor imparts momentum on the nanowires, which bend and leads to a time-varying field. In chapter 6, electrodeposition of Galfenol on a cylindrical surface is demonstrated for the first time. Galfenol has a large magnetostriction constant up to ~400 ppm. Utilizing a rotating cylinder electrode, the parameters to deposit Fe1-xGax films in the x = 15 to 35 range were found. The film's magnetostriction was then demonstrated as part of a torque sensor where magnetic anisotropy was controlled through texturing of the cylinder surface. The effect of magnetic shape anisotropy can be seen to play a significant role in the sensor's output by increasing the sensitivity of the sensor nearly 6x that of the non-textured film.
FASER Flight 10
(2012-08-13) Taylor, Brian
Gaussian-Pareto Overbounding: A Method for Managing Risk in Safety-Critical Navigation Systems
(2018-06) Larson, Jordan
An innovative method for managing the integrity risk of safety-critical navigation systems is presented. The method builds upon the current statistical technique used in the field of navigation known as overbounding which uses conservative probability distributions to bound risk probabilities. In particular, this work replaces the Gaussian distribution currently in use with a hybrid Gaussian-Pareto distribution. This change is motivated by results from Extreme Value Theory (EVT) and a simulation study assessing the Pareto distribution's potential as a model for the tails of distributions. Both of which are discussed thoroughly. By utilizing the hybrid Gaussian-Pareto overbound, the extreme error probabilities for distributions that display heavier-than-Gaussian tails can be truly overbounded which is necessary for constructing system output overbounds from input overbounds. The model also uses observed data more efficiently than current methods because it separates the extreme portion of the distribution from the core portion. Furthermore, the model can be less conservative than the Gaussian distribution across the entire domain which would lead to greater availability. To demonstrate this, the Gaussian-Pareto overbound is shown to be an appropriate model for double-differenced pseudoranges from two Continuously Operating Reference Stations (CORS) of the Global Navigation Satellite System (GNSS), an important measurement in many safety-critical navigation systems. Lastly, a novel approach for overbounding multivariate probability risks called norm overbounding is developed so that the Gaussian-Pareto model can be applied in the multivariate domain. This approach utilizes hyperspherical coordinates as well as domain partitioning in order to construct a robust model for bounding norms of random vectors which can be considered as multivariate errors. It is demonstrated for a simple 2-dimensional navigation application.
GPS FASER Flight 01
(2014-09-04) Taylor, Brian
GPS FASER Flight 03
(2014-09-04) Taylor, Brian
GPS FASER Flight 05
(2012-10-11) Taylor, Brian
Image Navigation UROP Research
(2014-07-23) VandenAvond, Sean
Inertially aided vector matching for opportunistic navigation in space
(International Astronautical Federation, IAF, 2017-10) Runnels, Joel T; Gebre Egziabher, Demoz
In this work, an estimator is developed for the joint estimation of orientation and position from astrophysical signals of opportunity, particularly pulsars. The filter is based on a combination of vector-matching techniques for estimating attitude and time-difference of arrival navigation for estimating position. The filter functions by computing the probability of association for each arriving photon with each signal source of interest, and using the association probabilities to perform the measurement update. The probability of association of a photon with a signal source is derived, as well as the probability of association with background. The estimation techniques proposed are tested using Monte Carlo analysis techniques. The accuracy of the resulting estimates is compared to other pulsar navigation techniques. The results of the simulation studies indicate that the technique proposed here generally outperforms other time difference of arrival estimation techniques.
Investigation of Human Environment Learning in Agile Guidance Tasks
(2017-11-20) Verma, Abhishek; Mettler, Berenice; mettler@umn.edu; Mettler, Berenice; University of Minnesota, Department of Aerospace Engineering and Mechanics, Interactive Guidance and Control Lab
Human environment learning experiments are done in a simulated environment. The environment is quasi 3-D, made of polygonal obstacles. The simulated environment is displayed to subjects who can navigate in the environment using a joystick. Vehicle motion is restricted to horizontal plane. Subjects start from a specified start state in the obstacle field. Subjects have to learn fastest routes to a specified goal state over multiple runs. The simulation system provides first-person view of the task environment to subjects. The experiment system records trajectory, control, and human gaze location in the displayed environment. Experiments are done with eight subjects.
Mapping Gps Satellite Signal Visibility, Specularity, And Multipath For Improved Urban Navigation
(2023-07) Zeller, Emma
GPS has been a key positioning tool since it was first introduced, and improved space and control segments have led users to expect accurate positioning. However, there are still uncertainties and errors in the user segment that can’t be fully accounted for upfront due to challenges specific to each user. GPS positioning in urban environments is challenging as tall buildings often block, reflect, or diffract signals. When signals reflect off buildings or other surfaces they reach the receiver via a non-line-of-sight (NLOS) path. Multipath is a phenomenon that occurs when a signal from a single satellite reaches the receiver via both a direct-line-of-sight (DLOS) and NLOS path. When a strong reflected signal reaches the receiver at a delay less than ~300m relative to the direct path signal, the interference due to the combination of both signals causes errors in the computed position solution. Many techniques in conventional software defined radios (SDRs) equipped to detect multipath attempt to mitigate the resulting errors by removing the NLOS component or the entire signal. However, very few approaches attempt to utilize both the DLOS and NLOS signals as additional measurements to aid in positioning. The approach discussed in this work uses urban mapping to predict visibility and specularity at any location of interest within the mapped environment, as well as the Multipath Estimating Delay Lock Loop (MEDLL) to characterize multipath signals. These are then incorporated into Direct Position Estimation (DPE), an alternative positioning approach that directly computes a multi-dimensional spatial correlogram from the individual satellite correlations, rather than individually tracking each to get a navigation solution. Experimental data from both a stationary and driving experiment done in Denver, CO are used to test the different methods. When positioning results using DPE integrating visibility and specularity predictions from both urban mapping and MEDLL are compared to standard SDR positioning, improvements are seen.
Methods for enhancing carrier phase GNSS positioning and attitude determination performance.
(2010-05) Zheng, Guijin
This thesis explores the methods for enhancing the performance of using low cost, single frequency Carrier phase Differential Global Navigation Satellite System (CDGNSS) in real-time, safety or liability critical applications. This is done by improving the integer ambiguity resolution performance and carrier phase error modeling. CDGNSS is considered for a broad range of real-time applications which require both a high precision relative positioning and attitude determination system. This is because of the drift-free nature of the GNSS measurement errors and the precise nature of the carrier phase measurement. The key to making full use of the precise nature of the carrier phase measurement is to fix the integer ambiguity quickly and reliably. This poses the biggest challenge for a low cost single frequency system. For the attitude determination problem, the precisely known baseline lengths can be used to improve the integer ambiguity resolution performance. Traditionally, the relative positioning problem was solved independently of the attitude determination problem and, thus could not leverage the precisely known baseline lengths of the attitude determination system. However, by integrating the two systems together, the precisely known baseline lengths can be used to improve the relative positioning system as well. The first part of the thesis develops an integration framework to improve the integer ambiguity resolution performance for the relative positioning system and the attitude determination system simultaneously. The second part of the thesis provides a GNSS antenna Phase Center Variation (PCV) error model development to improve the accuracy of the integrated system. It also examines the feasibility analysis of using the developed error model for a real-time dynamic application. The challenging of using this in the real time lies in the fact that PCV error magnitude is small (less than 2cm) and the developed error model is a function of unknown parameter such as attitude. A feasibility analysis of the developed model with a set of specific antennas is performed and assessed.
Navigating through buildings with impaired vision: challenges and solutions.
(2009-06) Kalia, Amy Ashwin
Navigation is the ability to plan and follow routes between locations, often with an internal or external map of the environment. Vision is an important way to access environmental information for navigation. Consequently, independent navigation is a significant challenge for individuals with visual impairment. This thesis describes three studies that investigate how real or simulated visual impairment affects the ability to navigate inside buildings. Furthermore, these experiments explore methods for compensating for the loss of visual information, either by using other senses or by using assistive technology. The visual information in an environment that is useful for navigation can be categorized as two types: geometric (visual information conveying layout geometry such as hallways and intersections), and non-geometric (features other than geometry such as lighting, texture, and object landmarks). The first experiment (Chapter 2) tested the effects of visual impairment and age on the use of these two types of visual information for navigation. In the second experiment (Chapter 3), visually-impaired individuals were tested on their ability to follow verbal route instructions provided by an indoor navigation technology. The instructions described distances in one of three ways: feet, number of steps, and travel time in seconds. This study compared route-following performance with the three distance modes. The third experiment (Chapter 4) investigated the integration of visual and walking information for localization in a hallway. We predicted that humans integrate information: 1) only when they perceive themselves to be near a landmark after walking (congruency), and 2) by weighing each information source according to its reliability. Normally-sighted participants judged their location in a hallway after viewing a target and then walking blindfolded to either the visual target or to a slightly different location. Participants viewed targets in two conditions that manipulated visual reliability: normal viewing and blurry viewing. This experiment tested and confirmed a statistical model of human perception in a novel domain. Together, these three studies enhance our understanding of the effects of visual impairment on navigation ability. These studies also suggest that information provided by other senses or assistive technology can improve navigation ability with low vision.
A Positioning and Mapping Methodology Using Bluetooth and Smartphone Technologies to Support Situation Awareness and Wayfinding for the Visually Impaired
(Center for Transportation Studies, University of Minnesota, 2018-11) Liao, Chen-Fu
People with vision impairment often face challenges while traveling in an unfamiliar environment largely due to uncertainty and insufficient accessible information. To improve mobility, accessibility, and the level of confidence the visually impaired experience in using the transportation system, it is important to remove information barriers that could potentially impede their mobility. A "condition aware" infrastructure using Bluetooth low-energy (BLE) technology was developed to provide up-to-date and correct audible information to users at the right location. A Multivariable Regression (MR) algorithm using the Singular Value Decomposition (SVD) technique was introduced to model the relationship between Bluetooth Received Signal Strength (RSS) and the actual ranging distance in an outdoor environment. This methodology reduced the environmental uncertainty and dynamic nature of RSS measurements in a Bluetooth network. The range output from the MR-SVD model was integrated with an extended Kalman filter to provide positioning and mapping solutions. Using 6 BLE beacons at an intersection in St. Paul, Minnesota, our approach achieved an average position accuracy of 2.5 m and 3.8 m in X and Y directions, respectively. A few statistical techniques were implemented and were able to successfully detect whether the location of one or multiple BLE beacons in a network changed based on Bluetooth RSS indications. With the self-monitoring network, information associated with each Bluetooth beacon can be provided to the visually impaired at the right location to support their wayfinding in a transportation network.
Prescription drug brand Web sites: Guidance where none exists
(University of Minnesota, College of Pharmacy, 2010) Glinert, Lewis
This paper applies insights from linguistics and discourse analysis to prescription drug brand Web sites, with special reference to the 100 top-selling drugs. Such sites give the outward appearance of being a place to go for straightforward information about a specific brand. In reality, they present a confused mix of brand information, health information and hype, muddled organization, and poor indication of authority, creating an imbalance between benefit and risk content. In so doing, they breach the letter and spirit of the regulations governing direct-to-consumer advertising, which the FDA has by default applied to such Web sites but which were not designed for this special type of discourse. The many communicative difficulties proven to be caused by Web sites in general, in particular for the elderly and less literate, also pose ethical problems. A rethinking of the verbal and visual design of these drug sites is needed -- and new regulatory guidance, for which this paper offers recommendations. At stake is not just the quality of health information at brand drug sites but also their credibility.
Real-time Kinematic Positioning: Background, Assessment and Forecasting
(2018-07) Jackson, John
This thesis presents an introduction and work performed related to real-time kinematic (RTK) positioning. RTK positioning is a differential positioning method that uses signals from global navigation satellite systems (GNSS). Position solutions using RTK methods have a nominal accuracy on the order of centimeters and are available in real-time, making them useful for such applications as autonomous vehicles and mobile robotics, driver-assist technologies, and precise geospatial data collection. First, a background on positioning using GNSS and RTK methods is presented. Next, an assessment of low-cost RTK receivers for the Minnesota Department of Transportation is described. Several low-cost RTK-capable receivers were assessed using metrics related to accuracy, availability, continuity and ini- tialization in different environments during static and dynamic tests. The low-cost mul- tifrequency receiver tested performed more consistently than the single-frequency low-cost receivers, especially for the dynamic tests. Of the low-cost single frequency receivers, there is a wide range in performance metrics. In addition, a multi-thousand dollar receiver was tested and outperformed all of the low-cost receivers in all environments. Finally, a fore- casting method using recurrent neural networks is explored to increase the robustness of RTK positioning. The methodology presented here was unable to create a reliable RTK solution, but suggestions are offered for future work. The goal of this thesis is to familiarize the reader with the basic premise of RTK positioning and educate them on the capabilities of low-cost receivers.
Six Degree Of Freedom Navigation Using X-Ray Pulsar Signals
(2019-08) Runnels, Joel
Navigation in deep space, far away from Earth, is an ongoing challenge and research topic. While spacecraft near Earth have a number of readily available methods for navigation (including GPS and radio ranging), far away from Earth it is more challenging for spacecraft to determine their position. In the absence of external reference objects that can be used to estimate position (for instance nearby planetary objects), the current state-of-the-art for navigation in space relies on NASA's Deep Space Network to provide Earth-based position measurements of the spacecraft. This means of navigation suffers from limitations, including limited availability, high cost, and decreased accuracy far from Earth. Consequently, alternative means of navigation are of interest. X-ray navigation, or XNAV is a proposed means by which spacecraft can navigate using signals generated by astrophysical signal sources. In particular, x-ray pulsars have been proposed as a naturally occurring signal source which could be used to generate a position, navigation and timing (PNT) solution in space. The basic concept in XNAV is that a spacecraft can compute a PNT solution based on time of arrival (TOA) measurement of signals from x-ray pulsars. Some x-ray pulsars, in particular millisecond pulsars, have extremely precise timing characteristics, with timing stability comparable to modern atomic clocks. If the TOA of signals from several millisecond pulsars could be measured, these TOAs could be used to compute a PNT solution for the spacecraft. The basic concept of XNAV is somewhat analogous to GPS, in that the position of the user is determined by measuring multiple signal TOAs generated by sources with precisely known timing characteristics. While this technique has been proposed numerous times in literature, there are still several implementation challenges which must be overcome in order for XNAV to become a viable navigation technology. In this dissertation, we address some of the major challenges associated with implementation of XNAV. The first challenge addressed in this dissertation is the development of a method of determining the signal time of arrival based on measurements of x-ray photon arrival times. This challenge is at the heart of any XNAV implementation, because in order to use pulsar signals as PNT signals, the time-difference of arrival of the signal must be measured. The estimation of time-difference of arrival from pulsar signals is complicated by the fact that pulsar signals are incredibly weak, resulting in a signal-to-noise ratio near zero. In this dissertation, we develop a recursive algorithm which estimates the time-difference of arrival of a pulsar signal which is based upon adaptive filtering techniques. The second challenge addressed in this dissertation is the problem of data association. Photons measured by an x-ray detector in space have no way of knowing with certainty the origin of the photons. The presence of the uniform x-ray background results in background photons diluting an already extremely weak signal. If the detector's attitude is known, then the attitude may be used to determine which photons are likely to have originated from a signal source of interest. However, the reliance upon attitude to correctly associate the photons with the correct signal source causes the position and attitude estimates to be coupled. In this dissertation, we present an algorithm which addresses this coupling of the attitude and PNT solutions for the XNAV problem. A joint six degree-of-freedom position and attitude estimator is developed based on the joint probabilistic data association filter. We further demonstrate the effects of attitude uncertainty on the accuracy of the PNT solution using Monte Carlo simulations.

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