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Full-Text Articles in Engineering

Uav 6dof Simulation And Kalman Filter For Localizing Radioactive Sources, John G. Goulet May 2020

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 Mar 2020

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 Mar 2020

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 Jan 2020

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 …


Indoor Navigation For Visually Impaired Person Using Inertial And Geomagnetic Information, Jayanth Ammanabrolu Jan 2020

Indoor Navigation For Visually Impaired Person Using Inertial And Geomagnetic Information, Jayanth Ammanabrolu

All Graduate Theses, Dissertations, and Other Capstone Projects

Motivated by the need for assistance of indoor guidance for visually impaired persons (VIPs), a sensing system using inertial and geo-magnetic information has been developed to navigate a VIP person indoor. Orientation estimation, which is critical for indoor localization, is conducted using the information of the angular velocity, acceleration and geomagnetic field. By analyzing the characters of human gait, a method to eliminate the accumulated drift introduced by double integrations is introduced. By attaching the inertial sensor to the foot, the periodic stationary state will facilitate the drift correction. Also, the distinctive distortion of the geomagnetic field, which contains spatial …