Towards intelligent trajectory optimisation in astrodynamics

Authors
Sprague, Christopher Iliffe
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Other Contributors
Anderson, Kurt S.
Embrechts, Mark J.
Hicken, Jason
Oehlschlaeger, Matthew A.
Issue Date
2017-05
Keywords
Aeronautical engineering
Degree
MS
Terms of Use
Attribution-NonCommercial-NoDerivs 3.0 United States
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
Full Citation
Abstract
In this work trajectory optimisation is explored through four different avenues, namely: 1. Direct Methods, 2. Heuristics, 3. Reinforcement learning, 4. Supervised Learning Each method builds off of its preceding session. It is shown that each method poses the capability to be utilised for autonomous real-time optimal control in astrodynamics applications.
A housefly is a rather simple organism, yet it is able to independently make decisions to achieve its goals, such as navigating to a food-source and avoiding obstacles. Inspecting closer, a housefly is able to make these decisions instantaneously, such as in the case of being swatted at by a human. If one thinks about the descent of a landing capsule onto the Martian surface, the nature of the situation is quite the same. Because communication with Earth is prolonged, the lander must make decisions on its own in order to safely land on the surface. If a common housefly can independently make decisions in real-time, in uncertain dynamic environments, than surely a spacecraft should be able to do the same in an environment where the objective is clearly outlined.
Description
May 2017
School of Engineering
Department
Dept. of Mechanical, Aerospace, and Nuclear Engineering
Publisher
Rensselaer Polytechnic Institute, Troy, NY
Relationships
Rensselaer Theses and Dissertations Online Collection
Access
CC BY-NC-ND. Users may download and share copies with attribution in accordance with a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. No commercial use or derivatives are permitted without the explicit approval of the author.