Document Type
Article
Publication Date
2022
Journal Article Version
Accepted Manuscript
First Page
1
Last Page
12
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Abstract
Autonomous satellite control is becoming increasingly important as the number satellites and their respective missions increase in complexity. This paper develops and evaluates three rapid planning techniques used to aid the scheduling of satellites in performing an earth imaging mission. A mixed-integer linear programming (MILP) solver from previous work is used both as motivation and comparison. Previous results suggest that the optimal solution produced by the MILP solver is very similar to a longest path, even though the constraints disallow the longest path solution. Thus, a greedy modification to a longest path search is used as a means to rapidly find a path. The second planner developed is based upon ant colony optimization techniques to allow random walks to be used as a means to im prove upon the solution. The final technique presented for comparison is to use these greedy planners as a hot start for the MILP optimization. Simulation results show application of the rapid planning techniques for a constellation of 100 satellites in LEO with thousands of points-of-interest (POIs) to be imaged.
Recommended Citation
Andrews, Konnor; Swedeen, James; and Droge, Greg, "Rapid Discrete Planning for Satellite Constellation Imaging Missions" (2022). Space Dynamics Laboratory Publications. Paper 312.
https://digitalcommons.usu.edu/sdl_pubs/312