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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
21

A Comparative Study of Feature Detection Methods for AUV Localization

Kim, Andrew Y 01 June 2018 (has links)
Underwater localization is a difficult task when it comes to making the system autonomous due to the unpredictable environment. The fact that radio signals such as GPS cannot be transmitted through water makes autonomous movement and localization underwater even more challenging. One specific method that is widely used for autonomous underwater navigation applications is Simultaneous Localization and Mapping (SLAM), a technique in which a map is created and updated while localizing the vehicle within the map. In SLAM, feature detection is used in landmark extraction and data association by examining each pixel and differentiating landmarks pixels from those of the background. Previous research on the performance of different feature detection methods have been done in environments such as cisterns and caverns where the effects of the ocean are reduced. Our objective, however, is to achieves robust localization in the open ocean environment of the Cal Poly pier. This thesis performs a comparative study between different feature detection methods including Scale Invariant Feature Transform (SIFT), Speeded-Up Robust Features (SURF), and Oriented FAST and Rotated BRIEF (ORB) on different sensors. We evaluate the feature detection and matching performance of these algorithms in a simulated open-ocean environment.
22

A robust AUV docking guidance and navigation approach to handling unknown current disturbances

Unknown Date (has links)
The main contribution in this thesis is the design of a robust AUV docking guidance and navigation approach that can guide and home an AUV towards an acoustic source located on an oriented bottom-mounted underwater docking station, under presence of unknown current disturbances and in the absence of any form of onboard velocity sensor. A Complementary Filter and various forms of Kalman Filters were separately formulated to estimate the current and vehicle positions with strategic vehicle manoeuvres. A current compensator uses the estimated current to maintain the desired vehicle course while under current disturbance. Tagaki-Sugeno-Kang Fuzzy Inference System was designed to realize fuzzy docking guidance manoeuvres. Finally, Monte Carlo runs were performed on a designed AUV docking simulator to evaluate the docking robustness against various docking conditions. Simulation results demonstrated robustness in the designed docking guidance and navigation approach. / by Hoe Eng Teo. / Thesis (M.S.C.S.)--Florida Atlantic University, 2010. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2010. Mode of access: World Wide Web.
23

A low-cost, high rate motion measurement system for an unmanned surface vehicle with underwater navigation and oceanographic applications

Unknown Date (has links)
Standard GPS receivers are unable to provide the rate or precision required when used on a small vessel such as an Unmanned Surface Vehicles (USVs). To overcome this, the thesis presents a low cost high rate motion measurement system for an USV with underwater and oceanographic purposes. The work integrates an Inertial Measurement Unit (IMU), a GPS receiver, a flux-gate compass, a tilt sensor and develops a software package, using real time data fusion methods, for an USV to aid in the navigation and control as well as controlling an onboard Acoustic Doppler Current Profiler (ADCP).While ADCPs non-intrusively measure water flow, they suffer from the inability to discriminate between motions in the water column and self-motion. Thus, the vessel motion contamination needs to be removed to analyze the data and the system developed in this thesis provides the motion measurements and processing to accomplish this task. / by Chrystel Gelin. / Thesis (M.S.C.S.)--Florida Atlantic University, 2010. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2010. Mode of access: World Wide Web.
24

A modular guidance, navigation and control system for unmanned surface vehicles

Unknown Date (has links)
The design and integration of an unmanned surface vehicle (USV) control system is described. A survey of related work in both USV control, and unmanned vehicle operating software is presented. The hardware subsystem comprising a modular Guidance, Navigation, and Control (GNC) package is explained. A multi-threaded software architecture is presented, utilizing a decentralized, mutex-protected shared memory inter-process communication subsystem to provide interoperability with additional software modules. A generic GNC approach is presented, with particular elaboration on a virtual rudder abstraction of differential thrust platforms. A MATLAB Simulink simulation is presented as a tool for developing an appropriate controller structure, the result of which was implemented on the target platform. Software validation is presented via a series of sea trials. The USV was tested both in open- and closed-loop control configurations, the results of which are presented here. Lastly recommendations for future development of the GNC system are enumerated. / by Thomas C. Furfaro. / Thesis (M.S.C.S.)--Florida Atlantic University, 2012. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2012. Mode of access: World Wide Web.
25

Augmented Terrain-Based Navigation to Enable Persistent Autonomy for Underwater Vehicles in GPS-Denied Environments

Reis, Gregory M 14 June 2018 (has links)
Aquatic robots, such as Autonomous Underwater Vehicles (AUVs), play a major role in the study of ocean processes that require long-term sampling efforts and commonly perform navigation via dead-reckoning using an accelerometer, a magnetometer, a compass, an IMU and a depth sensor for feedback. However, these instruments are subjected to large drift, leading to unbounded uncertainty in location. Moreover, the spatio-temporal dynamics of the ocean environment, coupled with limited communication capabilities, make navigation and localization difficult, especially in coastal regions where the majority of interesting phenomena occur. To add to this, the interesting features are themselves spatio-temporally dynamic, and effective sampling requires a good understanding of vehicle localization relative to the sampled feature. Therefore, our work is motivated by the desire to enable intelligent data collection of complex dynamics and processes that occur in coastal ocean environments to further our understanding and prediction capabilities. The study originated from the need to localize and navigate aquatic robots in a GPS-denied environment and examine the role of the spatio-temporal dynamics of the ocean into the localization and navigation processes. The methods and techniques needed range from the data collection to the localization and navigation algorithms used on-board of the aquatic vehicles. The focus of this work is to develop algorithms for localization and navigation of AUVs in GPS-denied environments. We developed an Augmented terrain-based framework that incorporates physical science data, i.e., temperature, salinity, pH, etc., to enhance the topographic map that the vehicle uses to navigate. In this navigation scheme, the bathymetric data are combined with the physical science data to enrich the uniqueness of the underlying terrain map and increase the accuracy of underwater localization. Another technique developed in this work addresses the problem of tracking an underwater vehicle when the GPS signal suddenly becomes unavailable. The methods include the whitening of the data to reveal the true statistical distance between datapoints and also incorporates physical science data to enhance the topographic map. Simulations were performed at Lake Nighthorse, Colorado, USA, between April 25th and May 2nd 2018 and at Big Fisherman's Cove, Santa Catalina Island, California, USA, on July 13th and July 14th 2016. Different missions were executed on different environments (snow, rain and the presence of plumes). Results showed that these two methodologies for localization and tracking work for reference maps that had been recorded within a week and the accuracy on the average error in localization can be compared to the errors found when using GPS if the time in which the observations were taken are the same period of the day (morning, afternoon or night). The whitening of the data had positive results when compared to localizing without whitening.
26

Terrain Aided Underwater Navigation using Bayesian Statistics / Terrängstöttad undervattensnavigering baserad på Bayesiansk statistik

Karlsson, Tobias January 2002 (has links)
<p>For many years, terrain navigation has been successfully used in military airborne applications. Terrain navigation can essentially improve the performance of traditional inertial-based navigation. The latter is typically built around gyros and accelerometers, measuring the kinetic state changes. Although inertial-based systems benefit from their high independence, they, unfortunately, suffer from increasing error-growth due to accumulation of continuous measurement errors. </p><p>Undersea, the number of options for navigation support is fairly limited. Still, the navigation accuracy demands on autonomous underwater vehicles are increasing. For many military applications, surfacing to receive a GPS position- update is not an option. Lately, some attention has, instead, shifted towards terrain aided navigation. </p><p>One fundamental aim of this work has been to show what can be done within the field of terrain aided underwater navigation, using relatively simple means. A concept has been built around a narrow-beam altimeter, measuring the depth directly beneath the vehicle as it moves ahead. To estimate the vehicle location, based on the depth measurements, a particle filter algorithm has been implemented. A number of MATLAB simulations have given a qualitative evaluation of the chosen algorithm. In order to acquire data from actual underwater terrain, a small area of the Swedish lake, Lake Vättern has been charted. Results from simulations made on this data strongly indicate that the particle filter performs surprisingly well, also within areas containing relatively modest terrain variation.</p>
27

Mems Sensor Based Underwater Ahrs(attitude And Heading Reference System) Aided By Compass And Pressure Sensor

Ozgeneci, Ercin Mehmet 01 September 2012 (has links) (PDF)
Attitude and Heading angles are crucial parameters for navigation. Conventional navigation methods mostly uses IMU and GPS devices to calculate these angles. MEMS technology offers small sized, low cost IMU sensors with moderate performance. However, GPS cannot be used in underwater. Therefore, different aiding sensors are used in underwater vehicles in order to increase the accuracy. As the accuracy of devices increases, the cost of these devices also increases. In this thesis, rather than using GPS and high quality IMU sensors, low cost MEMS IMU sensor is used together with a magnetometer and a pressure sensor as aiding sensors. Considering the IMU error model and motion dynamics, two systems are designed and simulated using real data. The results seem to be satisfactory and using pressure sensor as an aiding sensor improves the attitude angles estimation.
28

Navigation And Path Planning Of An Unmanned Underwater Vehicle

Gul, Ugur Dogan 01 September 2012 (has links) (PDF)
Due to the conditions peculiar to underwater, distinctive approaches are required to solve the navigation and path planning problem of an unmanned underwater vehicle (UUV). In this study, first of all, a detailed 6 degrees-of-freedom (DOF) mathematical model is formed, including the coupled non-linear forces and moments acting on an underwater vehicle. The hydrodynamic coefficients which correspond to the geometry of the vehicle which the model is based on are calculated using the strip theory. After the mathematical model is obtained, by applying appropriate linearization on the model, &ldquo / Linear Quadratic Regulator (LQR)&rdquo / control method is implemented to govern the surge, heave, pitch and yaw motions of the underwater vehicle. Path planning algorithm of the vehicle is based on tracking the waypoints. Permutation of the waypoints is obtained by solving the &ldquo / Travelling Salesman Problem (TSP)&rdquo / via genetic algorithm. Linked with that, &ldquo / Rapidly-Exploring Random Trees (RRT)&rdquo / algorithm is introduced into the path planning algorithm to avoid collisions in environments with obstacles. Underwater navigation solution is based on the &ldquo / Inertial Navigation System (INS)&rdquo / outputs, located on the vehicle. To correct the long-term drift of the inertial solution, &ldquo / Kalman Filter&rdquo / based integration algorithm is used and external aids such as &ldquo / Global Navigation Satellite System (GNSS)&rdquo / , &ldquo / Ultra-Short Baseline (USBL)&rdquo / acoustic navigation system and attitude sensors have been utilized. The control method, path planning and navigation algorithms used in this study are verified by simulation results.
29

Terrain Aided Underwater Navigation using Bayesian Statistics / Terrängstöttad undervattensnavigering baserad på Bayesiansk statistik

Karlsson, Tobias January 2002 (has links)
For many years, terrain navigation has been successfully used in military airborne applications. Terrain navigation can essentially improve the performance of traditional inertial-based navigation. The latter is typically built around gyros and accelerometers, measuring the kinetic state changes. Although inertial-based systems benefit from their high independence, they, unfortunately, suffer from increasing error-growth due to accumulation of continuous measurement errors. Undersea, the number of options for navigation support is fairly limited. Still, the navigation accuracy demands on autonomous underwater vehicles are increasing. For many military applications, surfacing to receive a GPS position- update is not an option. Lately, some attention has, instead, shifted towards terrain aided navigation. One fundamental aim of this work has been to show what can be done within the field of terrain aided underwater navigation, using relatively simple means. A concept has been built around a narrow-beam altimeter, measuring the depth directly beneath the vehicle as it moves ahead. To estimate the vehicle location, based on the depth measurements, a particle filter algorithm has been implemented. A number of MATLAB simulations have given a qualitative evaluation of the chosen algorithm. In order to acquire data from actual underwater terrain, a small area of the Swedish lake, Lake Vättern has been charted. Results from simulations made on this data strongly indicate that the particle filter performs surprisingly well, also within areas containing relatively modest terrain variation.
30

Performance analysis for lateral-line-inspired sensor arrays

Fernandez, Vicente I January 2011 (has links)
Thesis (Ph. D.)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2011. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 223-232). / The lateral line is a critical component of the fish sensory system, found to affect numerous aspects of behavior including maneuvering in complex fluid environments, schooling, prey tracking, and environment mapping. This sensory organ has no analog in modem ocean vehicles, despite its utility and ubiquity in nature, and could fill the gap left by sonar and vision systems in turbid cluttered environments. Yet, while the biological sensory system suggests the broad possibilities associated with such a sensor array, nearly nothing is known of the input processing and what information is available via the real lateral line. This thesis demonstrates and characterizes the ability of lateral-line-inspired linear pressure sensor arrays to perform two sensory tasks of relevance to biological and man-made underwater navigation systems, namely shape identification and vortex tracking. The ability of pressure sensor arrays to emulate the "touch at a distance" feature of the lateral line, corresponding to the latter's capability of identifying the shape of objects remotely, is examined with respect to moving cylinders of different cross sections. Using the pressure distribution on a small linear array, the position and size of a cylinder is tracked at various distances. The classification of cylinder shape is considered separately, using a large database of trials to identify two classification approaches: One based on differences in the mean flow, and one trained on a subset which utilizes information from the wake. The results indicate that it is in general possible to extract specific shape information from measurements on a linear pressure sensor array, and characterize the classes of shapes which are not distinguishable via this method. Identifying the vortices in a flow makes it possible to predict and optimize the performance of flapping foils, and to identify imminent stall in a control surface. Vortices in wakes also provide information about the object that generated the wake at distances much larger than the near-field pressure perturbations. Experimental studies in tracking a vortex pair and an individual vortex interacting with a flat plate demonstrate the ability to track vortices with a linear pressure sensor array from both small streamlined bodies and large flat bodies. Based on a theoretical analysis, the relationship between the necessary array parameters and the range of vortices of interest is established. / by Vicente I. Fernandez. / Ph.D.

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