Publication Date
8-2024
Date of Final Oral Examination (Defense)
5-6-2024
Type of Culminating Activity
Thesis
Degree Title
Master of Science in Mechanical Engineering
Department Filter
Mechanical and Biomechanical Engineering
Department
Mechanical and Biomedical Engineering
Supervisory Committee Chair
Aykut Satici, Ph.D.
Supervisory Committee Member
John Chiasson, Ph.D.
Supervisory Committee Member
Zhangxian Deng, Ph.D.
Abstract
This research develops a GPS-denied state estimation system to localize and orient a drone for touch-based installations on power line towers and cables. As opposed to environments like underground tunnels or building interiors, our system effectively identifies and utilizes sparse landmarks such as towers, cables, and ground features. Our approach utilizes Simultaneous Localization and Mapping (SLAM) to create and reference three-dimensional maps in real time. Specifically, we employ Georgia Tech Smoothing and Mapping (GTSAM), proposed by Georgia Tech's BORG Lab, a factor graph-based data structure consisting of measurement factors and unknown pose variables that we are implementing for solving the problem of SLAM. A strong feature of GTSAM is that several custom observation factors can be implemented with diverse sensor inputs allowing for the optimization problem to be better defined. Using an NVIDIA Jetson as the processor, we equipped a TurtleBot with six cameras and an Inertial Measurement Unit (IMU) to successfully implement and validate the GTSAM-based SLAM in a lab environment. While this technique can utilize cameras and distance sensors for robust localization in enclosed spaces (buildings, mines, etc), its performance degrades near power lines where landmarks are spatially distant and devoid of clear features. Consequently, we have derived a novel measurement algorithm that utilizes the time-varying electromagnetic fields generated by the power lines. A unique configuration and filtering of the time-varying Electromagnetic (EM) field allows the estimation of the cable positions, which can be utilized as additional landmarks in GTSAM. Developed from first principles using Maxwell's equations and subsequently verified through EM Finite Element Method (FEM), this technique is set for in-flight experimental validation. The thesis ultimately aims to enhance localization capabilities around power lines using the surrounding electromagnetic fields.
DOI
https://doi.org/10.18122/td.2249.boisestate
Recommended Citation
Peterson, Alex, "Development and Implementation of a GPS-Agnostic Drone Localization System" (2024). Boise State University Theses and Dissertations. 2249.
https://doi.org/10.18122/td.2249.boisestate
