(Georgia Institute of Technology, 2007-04-09)
Salazar Kardozo, Alexandros
Satellite constellations are an increasingly attractive option for many commercial and military applications. They provide a robust and distributed method of accomplishing the goals of expensive monolithic satellites. Among the many challenges that satellite constellations engender (challenges in control, coordination, disposal, and other areas), refueling is of particular interest because of the many methods one can use to refuel a constellation and the lifetime implications on the satellites.
The present work presents a methodology for carrying out peer-to-peer refueling maneuvers within a constellation. Peer-to-peer (P2P) refueling can be of great value both in cases where a satellite unexpectedly consumes more fuel than it was alloted, and as part of a mixed refueling strategy that will include an outside tanker bringing fuel to the constellation. Without considering mixed-refueling, we formulate the peer-to-peer refueling problem as an assignment problem that seeks to guarantee that all satellites will have the fuel they need to be functional until the next refueling, while concurrently minimizing the cost in fuel that the refueling maneuvers entail. The assignment problem is then solved via auctions, which, by virtue of their distributed nature, can easily and effectively be implemented on a constellation without jeopardizing any robustness properties.
Taking as a given that the P2P assignment problem has been solved, and that it has produced some matching among fuel deficient and fuel sufficient satellites, we then seek to sequence those prescribed maneuvers in the most effective manner. The idea is that while a constellation can be expected to have some redundancy, enough satellites leaving their assigned orbital slots will eventually make it impossible for the constellation to function. To tackle this problem, we define a wide class of operability conditions, and present three algorithms that intelligently schedule the maneuvers. We then briefly show how combining the matching and scheduling problems yields a complete methodology for organizing P2P satellite refueling operations.
(Georgia Institute of Technology, 2007-04-02)
Bakolas, Efstathios
The main objective of this thesis is to present a new path
planning scheme for solving the shortest (collision-free) path
problem for an agent (vehicle) operating in a partially known
environment. We present two novel algorithms to solve the planning
problem. For both of these approaches we assume that the agent has
detailed knowledge of the environment and the obstacles only in
the vicinity of its current position. Far away obstacles or the
final destination are only partially known and may even change
dynamically at each instant of time. The path planning scheme is
based on information gathered on-line by the available on-board
sensor devices. The solution minimizes the total length of the
path with respect to a metric that includes actual path length,
along with a risk-induced metric. In order to obtain an
approximation of the whole configuration space at different levels
of fidelity we use a wavelet approximation scheme. In the first
proposed algorithm, the path-planning problem is solved using a
multi-resolution cell decomposition of the environment obtained
from the wavelet transform. In the second algorithm, we extend the
results of the the first one by using the multiresolution
representation of the environment in conjunction with a conformal
mapping to polar coordinates. By performing the cell decomposition
in polar coordinates, we can naturally incorporate sector-like
cells that are adapted to the data representation collected by the
on-board sensor devices.