Relative Pose Uncertainty Quantification Using Lie Group Variational Filtering

<p>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.</p>

Name thesis:degree_name

Master of Science in Aerospace Engineering

Level thesis:degree_level

Thesis - Open Access

Discipline thesis:degree_discipline

Aerospace Engineering

Year

2021

Author dc:creator

• Hays, Christopher W.

• visual sensing
• variational filtering
• Lie Group theory
• Aerospace Engineering

Repository record dc:identifier

https://commons.erau.edu/edt/565

OAI identifier oai:identifier

oai:commons.erau.edu:edt-1567