Matching Items (16)

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Low-cost Image-assisted Inertial Navigation System for a Micro Air Vehicle

Description

The increasing civilian demand for autonomous aerial vehicle platforms in both hobby and professional markets has resulted in an abundance of inexpensive inertial navigation systems and hardware. Many of these

The increasing civilian demand for autonomous aerial vehicle platforms in both hobby and professional markets has resulted in an abundance of inexpensive inertial navigation systems and hardware. Many of these systems lack full autonomy, relying on the pilot's guidance with the assistance of inertial sensors for guidance. Autonomous systems depend heavily on the use of a global positioning satellite receiver which can be inhibited by satellite signal strength, low update rates and poor positioning accuracy. For precise navigation of a micro air vehicle in locations where GPS signals are unobtainable, such as indoors or throughout a dense urban environment, additional sensors must complement the inertial sensors to provide improved navigation state estimations without the use of a GPS. By creating a system that allows for the rapid development of experimental guidance, navigation and control algorithms on versatile, low-cost development platforms, improved navigation systems may be tested with relative ease and at reduced cost. Incorporating a downward-facing camera with this system may also be utilized to further improve vehicle autonomy in denied-GPS environments.

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Created

Date Created
  • 2014-12

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Extending ns-3 for Three-Dimensional Wireless Networks

Description

As technologies advance, so does the curiosity and exploration of humankind. There are many domains across this planet that are unexplored \u2014 the depths of Earth's ocean being one of

As technologies advance, so does the curiosity and exploration of humankind. There are many domains across this planet that are unexplored \u2014 the depths of Earth's ocean being one of the most predominant. While the ocean covers seventy percent of Earth's surface, a vast ninety-five percent of this realm remains untouched and unseen by the human eye. The biggest causality of this can be identified in the limitations of current technologies and the large expense associated with delving into these dangerous and uncharted areas. Underwater communication between unmanned devices is the solution to this problem. With the oceanic deployment of wirelessly connected unmanned underwater vehicles (UUVs), researchers can limit risk to human safely and retrieve invaluable oceanographic data from unimaginable depths. However, before this system can be physically deployed, the network topology and environmental interactions must be simulated. More specific to the application, how does attenuation of optical propagation degrade between transmissions? A widely used open source network simulator is the ns series: ns-1, ns-2, and ns-3. Ns-3 is the most recent version, and is a valuable tool for modeling network interactions. However, underwater simulation proposes a limitation \u2014 a three-dimensional consideration for pressure. To properly model this interaction, it is vital that an extension to ns-3 be provided in order to account for the affects pressure has on the propagation of a signal at varying depths.

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Created

Date Created
  • 2013-05

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Ecohydrology with unmanned aerial vehicles

Description

High-resolution characterizations and predictions are a grand challenge for ecohydrology. Recent advances in flight control, robotics and miniaturized sensors using unmanned aerial vehicles (UAVs) provide an unprecedented opportunity for characterizing,

High-resolution characterizations and predictions are a grand challenge for ecohydrology. Recent advances in flight control, robotics and miniaturized sensors using unmanned aerial vehicles (UAVs) provide an unprecedented opportunity for characterizing, monitoring and modeling ecohydrologic systems at high-resolution (<1 m) over a range of scales. How can the ecologic and hydrologic communities most effectively use UAVs for advancing the state of the art? This Innovative Viewpoints paper introduces the utility of two classes of UAVs for ecohydrologic investigations in two semiarid rangelands of the southwestern U.S. through two useful examples. We discuss the UAV deployments, the derived image, terrain and vegetation products and their usefulness for ecohydrologic studies at two different scales. Within a land-atmosphere interaction study, we utilize high-resolution imagery products from a rotary-wing UAV to characterize an eddy covariance footprint and scale up environmental sensor network observations to match the time-varying sampling area. Subsequently, in a surface and subsurface interaction study within a small watershed, we demonstrate the use of a fixed-wing UAV to characterize the spatial distribution of terrain attributes and vegetation conditions which serve as input to a distributed ecohydrologic model whose predictions compared well with an environmental sensor network. We also point to several challenges in performing ecohydrology with UAVs with the intent of promoting this new self-service (do-it-yourself) model for high-resolution image acquisition over many scales. We believe unmanned aerial vehicles can fundamentally change how ecohydrologic science is conducted and offer ways to merge remote sensing, environmental sensor networks and numerical models.

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Created

Date Created
  • 2014-10-01

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Resource allocation in communication and social networks

Description

As networks are playing an increasingly prominent role in different aspects of our lives, there is a growing awareness that improving their performance is of significant importance. In order to

As networks are playing an increasingly prominent role in different aspects of our lives, there is a growing awareness that improving their performance is of significant importance. In order to enhance performance of networks, it is essential that scarce networking resources be allocated smartly to match the continuously changing network environment. This dissertation focuses on two different kinds of networks - communication and social, and studies resource allocation problems in these networks. The study on communication networks is further divided into different networking technologies - wired and wireless, optical and mobile, airborne and terrestrial. Since nodes in an airborne network (AN) are heterogeneous and mobile, the design of a reliable and robust AN is highly complex. The dissertation studies connectivity and fault-tolerance issues in ANs and proposes algorithms to compute the critical transmission range in fault free, faulty and delay tolerant scenarios. Just as in the case of ANs, power optimization and fault tolerance are important issues in wireless sensor networks (WSN). In a WSN, a tree structure is often used to deliver sensor data to a sink node. In a tree, failure of a node may disconnect the tree. The dissertation investigates the problem of enhancing the fault tolerance capability of data gathering trees in WSN. The advent of OFDM technology provides an opportunity for efficient resource utilization in optical networks and also introduces a set of novel problems, such as routing and spectrum allocation (RSA) problem. This dissertation proves that RSA problem is NP-complete even when the network topology is a chain, and proposes approximation algorithms. In the domain of social networks, the focus of this dissertation is study of influence propagation in presence of active adversaries. In a social network multiple vendors may attempt to influence the nodes in a competitive fashion. This dissertation investigates the scenario where the first vendor has already chosen a set of nodes and the second vendor, with the knowledge of the choice of the first, attempts to identify a smallest set of nodes so that after the influence propagation, the second vendor's market share is larger than the first.

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Created

Date Created
  • 2014

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Novel waypoint generation method for increased mapping efficiency

Description

This project is to develop a new method to generate GPS waypoints for better terrain mapping efficiency using an UAV. To create a map of a desired terrain, an UAV

This project is to develop a new method to generate GPS waypoints for better terrain mapping efficiency using an UAV. To create a map of a desired terrain, an UAV is used to capture images at particular GPS locations. These images are then stitched together to form a complete map of the terrain. To generate a good map using image stitching, the images are desired to have a certain percentage of overlap between them. In high windy condition, an UAV may not capture image at desired GPS location, which in turn interferes with the desired percentage of overlap between images; both frontal and sideways; thus causing discrepancies while stitching the images together. The information about the exact GPS locations at which the images are captured can be found on the flight logs that are stored in the Ground Control Station and the Auto pilot board. The objective is to look at the flight logs, predict the waypoints at which the UAV might have swayed from the desired flight path. If there are locations where flight swayed from intended path, the code should generate a new set of waypoints for a correction flight. This will save the time required for stitching the images together, thus making the whole process faster and more efficient.

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Agent

Created

Date Created
  • 2014

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Design of miniaturized underwater vehicle with propulsions for deep-sea research applications

Description

The ocean is vital to the health of our planet but remains virtually unexplored. Many researchers seek to understand a wide range of geological and biological phenomena by developing

The ocean is vital to the health of our planet but remains virtually unexplored. Many researchers seek to understand a wide range of geological and biological phenomena by developing technologies which enable exploration of the deep-sea. The task of developing a technology which can withstand extreme pressure and temperature gradients in the deep ocean is not trivial. Of these technologies, underwater vehicles were developed to study the deep ocean, but remain large and expensive to manufacture. I am proposing the development of cost efficient miniaturized underwater vehicle (mUV) with propulsion systems to carry small measurement devices and enable deep-sea exploration. These mUV's overall size is optimized based on the vehicle parameters such as energy density, desired velocity, swimming time and propulsion performance. However, there are limitations associated with the size of the mUV which leads to certain challenges. For example, 2000 m below the sea level, the pressure is as high as 3000 psi. Therefore, certain underwater vehicle modules, such as the propulsion system, will require pressure housing to ensure the functionality of the thrust generation. In the case of a mUV swimming against the deep-sea current, a thrust magnitude is required to enable the vehicle to overcome the ocean current speed and move forward. Therefore, the size of the mUV is limited by the energy density and the propeller size. An equation is derived to miniaturize underwater vehicle while performing with a certain specifications. An inrunner three-phase permanent magnet brushless DC motor is designed and fabricated with a specific size to fit inside the mUV's core. The motor is composed of stator winding in a pressure housing and an open to water ring-propeller rotor magnet. Several ring-propellers are 3D printed and tested experimentally to determine their performances and efficiencies. A planer motion optimal trajectory for the mUV is determined to minimize the energy usage. Those studies enable the design of size optimized underwater vehicle with propulsion to carry small measurement sensors and enable underwater exploration. Developing mUV's will enable ocean exploration that can lead to significant scientific discoveries and breakthroughs that will solve current world health and environmental problems.

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Created

Date Created
  • 2014

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Continuous spatio temporal tracking of mobile targets

Description

There has been extensive study of the target tracking problems in the recent years. Very little work has been done in the problem of continuous monitoring of all the mobile

There has been extensive study of the target tracking problems in the recent years. Very little work has been done in the problem of continuous monitoring of all the mobile targets using the fewest number of mobile trackers, when the trajectories of all the targets are known in advance. Almost all the existing research discretized time (and/or space), or assume infinite tracker velocity. In this thesis, I consider the problem of covering (tracking) target nodes using a network of Unmanned Airborne Vehicles (UAV's) for the entire period of observation by adding the constraint of fixed velocity on the trackers and observing the targets in continuous time and space. I also show that the problem is NP-complete and provide algorithms for handling cases when targets are static and dynamic.

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Created

Date Created
  • 2014

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Methods for calibration, registration, and change detection in robot mapping applications

Description

Multi-sensor fusion is a fundamental problem in Robot Perception. For a robot to operate in a real world environment, multiple sensors are often needed. Thus, fusing data from various sensors

Multi-sensor fusion is a fundamental problem in Robot Perception. For a robot to operate in a real world environment, multiple sensors are often needed. Thus, fusing data from various sensors accurately is vital for robot perception. In the first part of this thesis, the problem of fusing information from a LIDAR, a color camera and a thermal camera to build RGB-Depth-Thermal (RGBDT) maps is investigated. An algorithm that solves a non-linear optimization problem to compute the relative pose between the cameras and the LIDAR is presented. The relative pose estimate is then used to find the color and thermal texture of each LIDAR point. Next, the various sources of error that can cause the mis-coloring of a LIDAR point after the cross- calibration are identified. Theoretical analyses of these errors reveal that the coloring errors due to noisy LIDAR points, errors in the estimation of the camera matrix, and errors in the estimation of translation between the sensors disappear with distance. But errors in the estimation of the rotation between the sensors causes the coloring error to increase with distance.

On a robot (vehicle) with multiple sensors, sensor fusion algorithms allow us to represent the data in the vehicle frame. But data acquired temporally in the vehicle frame needs to be registered in a global frame to obtain a map of the environment. Mapping techniques involving the Iterative Closest Point (ICP) algorithm and the Normal Distributions Transform (NDT) assume that a good initial estimate of the transformation between the 3D scans is available. This restricts the ability to stitch maps that were acquired at different times. Mapping can become flexible if maps that were acquired temporally can be merged later. To this end, the second part of this thesis focuses on developing an automated algorithm that fuses two maps by finding a congruent set of five points forming a pyramid.

Mapping has various application domains beyond Robot Navigation. The third part of this thesis considers a unique application domain where the surface displace- ments caused by an earthquake are to be recovered using pre- and post-earthquake LIDAR data. A technique to recover the 3D surface displacements is developed and the results are presented on real earthquake datasets: El Mayur Cucupa earthquake, Mexico, 2010 and Fukushima earthquake, Japan, 2011.

Contributors

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Created

Date Created
  • 2016

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Moving obstacle avoidance for unmanned aerial vehicles

Description

There has been a vast increase in applications of Unmanned Aerial Vehicles (UAVs) in civilian domains. To operate in the civilian airspace, a UAV must be able to sense and

There has been a vast increase in applications of Unmanned Aerial Vehicles (UAVs) in civilian domains. To operate in the civilian airspace, a UAV must be able to sense and avoid both static and moving obstacles for flight safety. While indoor and low-altitude environments are mainly occupied by static obstacles, risks in space of higher altitude primarily come from moving obstacles such as other aircraft or flying vehicles in the airspace. Therefore, the ability to avoid moving obstacles becomes a necessity

for Unmanned Aerial Vehicles.

Towards enabling a UAV to autonomously sense and avoid moving obstacles, this thesis makes the following contributions. Initially, an image-based reactive motion planner is developed for a quadrotor to avoid a fast approaching obstacle. Furthermore, A Dubin’s curve based geometry method is developed as a global path planner for a fixed-wing UAV to avoid collisions with aircraft. The image-based method is unable to produce an optimal path and the geometry method uses a simplified UAV model. To compensate

these two disadvantages, a series of algorithms built upon the Closed-Loop Rapid Exploratory Random Tree are developed as global path planners to generate collision avoidance paths in real time. The algorithms are validated in Software-In-the-Loop (SITL) and Hardware-In-the-Loop (HIL) simulations using a fixed-wing UAV model and in real flight experiments using quadrotors. It is observed that the algorithm enables a UAV to avoid moving obstacles approaching to it with different directions and speeds.

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Created

Date Created
  • 2015

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Incorporating supervisory human inputs into autonomous robot navigation

Description

With robots being used extensively in various areas, a certain degree of robot autonomy has always been found desirable. In applications like planetary exploration, autonomous path planning and navigation are

With robots being used extensively in various areas, a certain degree of robot autonomy has always been found desirable. In applications like planetary exploration, autonomous path planning and navigation are considered essential. But every now and then, a need to modify the robot's operation arises, a need for a human to provide it some supervisory parameters that modify the degree of autonomy or allocate extra tasks to the robot. In this regard, this thesis presents an approach to include a provision to accept and incorporate such human inputs and modify the navigation functions of the robot accordingly. Concepts such as applying kinematical constraints while planning paths, traversing of unknown areas with an intent of maximizing field of view, performing complex tasks on command etc. have been examined and implemented. The approaches have been tested in Robot Operating System (ROS), using robots such as the iRobot Create, Personal Robotics (PR2) etc. Simulations and experimental demonstrations have proved that this approach is feasible for solving some of the existing problems and that it certainly can pave way to further research for enhancing functionality.

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Created

Date Created
  • 2013