A Genetic Algorithm Based Approach for Satellite Autonomy
This addresses the problem of autonomous orbit adjustment for satellites, but it is incremental as it applies an existing evolutionary method to a specific space mission scenario.
The paper tackled autonomous spacecraft maneuver planning by using a genetic algorithm to generate sequences of delta-v impulses, successfully achieving a target polar, low-eccentricity orbit from various non-polar starting orbits in simulations.
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.