Genetic Algorithm Based Robust and Optimal Path Planning for Sample-Return Mission from an Asteroid on an Earth Fly-By Trajectory

TL;DR

This paper presents a genetic algorithm approach for designing robust and optimal interplanetary trajectories for asteroid sample-return missions, minimizing V and enhancing robustness against uncertainties.

Contribution

The study introduces a genetic algorithm that optimizes V for asteroid rendezvous while incorporating robustness to uncertainties, improving mission reliability.

Findings

Enhanced robustness of rendezvous solutions.

Reduced sensitivity to propulsive errors.

Maintained minimal V increase.

Abstract

In this study, an interplanetary space flight mission design is established to obtain the minimum \(\Delta V\) required for a rendezvous and sample return mission from an asteroid. Given the initial (observed) conditions of an asteroid, a (robust) genetic algorithm is implemented to determine the optimal choice of \(\Delta V\) required for the rendezvous. Robustness of the optimum solution is demonstrated through incorporated bounded-uncertainties in the outbound \(\Delta V\) maneuver via genetic fitness function. The improved algorithm results in a solution with improved robustness and reduced sensitivity to propulsive errors in the outbound maneuver. This is achieved over a solution optimized solely on \(\Delta V\), while keeping the increase in \(\Delta V\) to a minimum, as desired. Outcomes of the analysis provide significant results in terms of improved robustness in asteroid rendezvous missions.