Development of a multi-objective optimisation tool for interplanetary mission design applied to science planning

Abstract

The development of gravity-assist maneuvers has revolutionized interplanetary mission design, enabling the exploration of the solar system with reduced propellant requirements and more ambitious scientific objectives. Building on these advancements, recent research in trajectory optimization has used genetic algorithms and other metaheuristic methods to efficiently navigate complex mission design spaces, while improvements in tools for planning scientific observations have maximized the scientific return of space missions. By combining a multi-gravity assist optimizer with an advanced observation scheduling module, the proposed framework simultaneously identifies optimal spacecraft trajectories and generates activity plans that meet mission-specific scientific goals. We provide several arbitrary tests to demonstrate the feasibility of this approach, with room still left for improvement of the architecture and performance of the combined module.