Year: 2019
Type: dissertation
Abstract: Debris in Low Earth Orbit (LEO) poses a great risk to humanity’s access to space in the coming\nyears. Seemingly the only way to prevent a full scale catastrophe rendering LEO unusable is to\nbegin a series of active debris removal (ADR) missions.\nAn approach for designing a series of active debris removal missions is presented in this thesis.\nThis approach has multiple steps and begins with a large list of high risk, high mass debris objects.\nThe first stage of the planning process entails the use of clustering algorithms to partition a large\ncatalogue of orbits into groups of user defined sizes. It is shown that this operation is tantamount\nto histogram analysis in non-Euclidean spaces.\n\n The second stage of the approach then solves a dynamic traveling salesman problem to compute an order of visitation through each cluster.\nLastly, a novel trajectory optimization technique is presented, using Chebyshev polynomials to\napproximate the dynamics of the system (rather than the states, which is typical). This technique\nis then used to further optimize the solution of the dynamic traveling salesman problem in order to\narrive at a locally optimal solution to each multi-rendezvous problem.
Author: Tyler J. Doogan
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2994283579