A Genetic Algorithm Based Approach for Satellite Autonomy

TL;DR

This paper presents a genetic algorithm approach to autonomous spacecraft maneuver planning, successfully converting various initial orbits into polar, low eccentricity orbits through optimized impulse sequences.

Contribution

It introduces a genetic algorithm tailored for spacecraft maneuver optimization, demonstrating its effectiveness across multiple initial orbit scenarios.

Findings

Successfully achieved orbit transfer goals in all test cases

Demonstrated the genetic algorithm's capability for maneuver optimization

Discussed performance metrics and future improvements

Abstract

Autonomous spacecraft maneuver planning using an evolutionary algorithmic approach is investigated. Simulated spacecraft were placed into four different initial orbits. Each was allowed a string of thirty delta-v impulse maneuvers in six cartesian directions, the positive and negative x, y and z directions. The goal of the spacecraft maneuver string was to, starting from some non-polar starting orbit, place the spacecraft into a polar, low eccentricity orbit. A genetic algorithm was implemented, using a mating, fitness, mutation and crossover scheme for impulse strings. The genetic algorithm was successfully able to produce this result for all the starting orbits. Performance and future work is also discussed.