Development of a mission analysis and trajectory optimization software via ESA GODOT

This thesis’ objective is to describe the development process, in collaboration with the start-up AerisGate, of a set of python applications for mission analysis and trajectory optimization by explaining the theory behind these applications and showing the results of tests conducted. The applications are based on GODOT (General Orbit Determination and Optimisation Toolkit), a European Space Agency flight dynamics software for orbit determination and analysis, that allows to model the universe and perform spacecraft’s trajectory propagation. By combining this tool with the optimization library PyGMO, the developed applications aim to be as generic as possible, in order to analyse many types of missions. The two main optimization algorithms applied are SLSQP (Sequential Least Squares Programming) and IPOPT (Interior Point OPTimizer). These are non-linear optimization Local algorithms, thus they aim to find the local minima of the function studied. This mean that an initial guess must be given to the algorithms and it has to be in the space of the solutions, otherwise these algorithms won’t converge. To perform the preliminary analysis required to obtain a good initial guess, the Lambert’s problem has been solved to obtain a mission’s porkchop plots. To show the capabilities of the applications three test missions have been analysed and successfully optimized: a Mars orbit insertion departing from Earth via B-plane targeting; a free-return trajectory from Earth to Moon; an in-plane station-keeping manoeuvres analysis for Sun-Synchronous orbits via the implementation of a bisection algorithm.