Date of Award
Fall 2021
Access Type
Thesis - Open Access
Degree Name
Master of Science in Aerospace Engineering
Department
Aerospace Engineering
Committee Chair
Troy A. Henderson
First Committee Member
Morad Nazari
Second Committee Member
Richard Prazenica
Abstract
The applications of visual sensing techniques have revolutionized the way autonomous systems perceive their environment on Earth. In space, the challenge of accurate perception has proven to be a difficult task. Due to adverse lighting conditions, high-noise images are common and degrade the performance of traditional feature-based estimation and perception algorithms. This work explores the applications of a variational filtering scheme founded in Lie Group theory to an autonomous rendezvous, proximity operations and docking problem. Two methodologies, a Monte Carlo approach and an Unscented Transform, for propagating uncertainty using a Lie Group Variational Filter are introduced and developed.
Scholarly Commons Citation
Hays, Christopher W., "Relative Pose Uncertainty Quantification Using Lie Group Variational Filtering" (2021). Doctoral Dissertations and Master's Theses. 565.
https://commons.erau.edu/edt/565
