Engineering Commons^™

Analysis Of Localization Algorithms For Wireless Sensor Networks Using Binary Data, Alexander Joseph Hart

Graduate Research Theses & Dissertations

The detection, localization, and tracking of environmental and physical conditions can be accomplished using wireless sensor networks (WSNs). Recent advancements in sensors, processors, and wireless communications have improved the quality and acquisition speed of data in WSNs. However, the data gathered by a WSN is inherently random due to component and environmental variations. Thus, statistical signal processing algorithms are needed to analyze the random data in a robust way. Though many algorithms for the analysis of random data are established and available, they are problem-specific and must be adapted to the application. This thesis provides an analysis of established localization …

Exploiting The Advantages And Overcoming The Challenges Of The Cable In A Tethered Drone System, Rogerio Rodrigues Lima

Graduate Theses, Dissertations, and Problem Reports

This dissertation proposes solutions for motion planning, localization, and landing of tethered drones using only tether variables. A tether-based multi-model localization framework for tethered drones is proposed. This framework comprises three independent localization strategies based on a different model. The first strategy uses simple trigonometric relations assuming that the tether is taut; the second method relies on a set of catenary equations for the slack tether case; the third estimator is a neural network-based predictor that can cover different tether shapes. Multi-layer perceptron networks previously trained with a dataset comprised of the tether variables (i.e., length, tether angles on the …

Planning Algorithms Under Uncertainty For A Team Of A Uav And A Ugv For Underground Exploration, Matteo De Petrillo

Graduate Theses, Dissertations, and Problem Reports

Robots’ autonomy has been studied for decades in different environments, but only recently, thanks to the advance in technology and interests, robots for underground exploration gained more attention. Due to the many challenges that any robot must face in such harsh environments, this remains an challenging and complex problem to solve.

As technology became cheaper and more accessible, the use of robots for underground ex- ploration increased. One of the main challenges is concerned with robot localization, which is not easily provided by any Global Navigation Services System (GNSS). Many developments have been achieved for indoor mobile ground robots, making …

Uav 6dof Simulation And Kalman Filter For Localizing Radioactive Sources, John G. Goulet

Electronic Theses and Dissertations

Unmanned Aerial Vehicles (UAVs) expand the available mission-space for a wide range of budgets. Using MATLAB, this project has developed a six degree of freedom (6DOF) simulation of UAV flight, an Extended Kalman Filter (EKF), and an algorithm for localizing radioactive sources using low-cost hardware. The EKF uses simulated low-cost instruments in an effort to estimate the UAV state throughout simulated flight.

The 6DOF simulates aerodynamics, physics, and controls throughout the flight and provides outputs for each time step. Additionally, the 6DOF simulation offers the ability to control UAV flight via preset waypoints or in realtime via keyboard input.

Using …

Comparison Of Visual Simultaneous Localization And Mapping Methods For Fixed-Wing Aircraft Using Slambench2, Patrick R. Latcham

Theses and Dissertations

Visual Simultaneous Localization and Mapping (VSLAM) algorithms have evolved rapidly in the last few years, however there has been little research evaluating current algorithm's effectiveness and limitations when applied to tracking the position of a fixed-wing aerial vehicle. This research looks to evaluate current monocular VSLAM algorithms' performance on aerial vehicle datasets using the SLAMBench2 benchmarking suite. The algorithms tested are MonoSLAM, PTAM, OKVIS, LSDSLAM, ORB-SLAM2, and SVO, all of which are built into the SLAMBench2 software. The algorithms' performance is evaluated using simulated datasets generated in the AftrBurner Engine. The datasets were designed to test the quality of each …

Pedestrian Navigation Using Artificial Neural Networks And Classical Filtering Techniques, David J. Ellis

Theses and Dissertations

The objective of this thesis is to explore the improvements achieved through using classical filtering methods with Artificial Neural Network (ANN) for pedestrian navigation techniques. ANN have been improving dramatically in their ability to approximate various functions. These neural network solutions have been able to surpass many classical navigation techniques. However, research using ANN to solve problems appears to be solely focused on the ability of neural networks alone. The combination of ANN with classical filtering methods has the potential to bring beneficial aspects of both techniques to increase accuracy in many different applications. Pedestrian navigation is used as a …

V-Slam And Sensor Fusion For Ground Robots, Ejup Hoxha

Dissertations and Theses

In underground, underwater and indoor environments, a robot has to rely solely on its on-board sensors to sense and understand its surroundings. This is the main reason why SLAM gained the popularity it has today. In recent years, we have seen excellent improvement on accuracy of localization using cameras and combinations of different sensors, especially camera-IMU (VIO) fusion. Incorporating more sensors leads to improvement of accuracy,but also robustness of SLAM. However, while testing SLAM in our ground robots, we have seen a decrease in performance quality when using the same algorithms on flying vehicles.We have an additional sensor for ground …

Rss-Based Device-Free Passive Detection And Localization Using Home Automation Network Radio Frequencies, Tiffany M. Phan

Theses and Dissertations

This research provided a proof of concept for a device-free passive (DfP) system capable of detecting and localizing a target through exploitation of a home automation network’s radio frequency (RF) signals. The system was developed using Insteon devices with a 915 MHz center frequency. Without developer privileges, limitations of the Insteon technology like no intrinsic received signal strength (RSS) field and silent periods between messages were overcome by using software-defined radios to simulate Insteon devices capable of collecting and reporting RSS, and by creating a message generation script and implementing a calibrated filter threshold to reduce silent periods. Evaluation of …

A Novel Approach To Complex Human Activity Recognition, Md Osman Gani

Dissertations (1934 -)

Human activity recognition is a technology that offers automatic recognition of what a person is doing with respect to body motion and function. The main goal is to recognize a person's activity using different technologies such as cameras, motion sensors, location sensors, and time. Human activity recognition is important in many areas such as pervasive computing, artificial intelligence, human-computer interaction, health care, health outcomes, rehabilitation engineering, occupational science, and social sciences. There are numerous ubiquitous and pervasive computing systems where users' activities play an important role. The human activity carries a lot of information about the context and helps systems …

Indoor Scene Localization To Fight Sex Trafficking In Hotels, Abigail Stylianou

McKelvey School of Engineering Theses & Dissertations

Images are key to fighting sex trafficking. They are: (a) used to advertise for sex services,(b) shared among criminal networks, and (c) connect a person in an image to the place where the image was taken. This work explores the ability to link images to indoor places in order to support the investigation and prosecution of sex trafficking. We propose and develop a framework that includes a database of open-source information available on the Internet, a crowd-sourcing approach to gathering additional images, and explore a variety of matching approaches based both on hand-tuned features such as SIFT and learned features …

Walkcompass: Finding Walking Direction Leveraging Smartphone's Inertial Sensors, Nirupam Roy

Theses and Dissertations

Determining moving direction with smartphone's inertial sensors is a well known problem in the field of location service. Compass alone cannot solve this problem because smartphone's compass cannot achieve high accuracy. Moreover GPS is not suitable in indoor scenario. Another well known approach is dead-reckoning but dead-reckoning needs to know phones initial orientation and over time it keeps accumulating errors and after some time the estimation becomes to noisy to use. To overcome these limitations, we propose a solution called WalkCompass which is specially designed for pedestrians keeping in mind the variation of force during normal human walk. Therefore the …

Robotic Swarming Without Inter-Agent Communication, Daniel Jonathan Standish

USF Tampa Graduate Theses and Dissertations

Many physical and algorithmic swarms utilize inter-agent communication to achieve advanced swarming behaviors. These swarms are inspired by biological swarms that can be seen throughout nature and include bee swarms, ant colonies, fish schools, and bird flocks. These biological swarms do not utilize inter-agent communication like their physical and algorithmic counterparts. Instead, organisms in nature rely on a local awareness of other swarm members that facilitates proper swarm motion and behavior. This research aims to pursue an effective swarm algorithm using only line-of-sight proximity information and no inter-agent communication. It is expected that the swarm performance will be lower than …