Study: implementation of an interplanetary trajectory optimisation algorithm using the Tisserand graph

Abstract

Nowadays, technology advances have given us the chance to achieve things that a couple generations ago could not even dream of. Space exploration is one of those achievements and space mission designing is a vital part of it. Since the firsts space missions, the methods used to design them have been increasingly evolving and sophisticating with time. Scheduling a space mission is a complex task that takes time and effort to achieve. A crucial factor to determine a space mission trajectory is cost, which is basically reflected in the fuel used to accomplish the mission. In order to reduce the quantity of propellant used in a mission, multi-gravity assists provide the capability to the spacecraft of altering its speed and path. Throughout this process, analysis to optimize the path of the mission are done. To do so, the optimizers need a list of planet sequences to start analyzing. A first approach to obtain viable lists of planets is using Tisserand graphs. The Tisserand graph is a graphical tool developed to aid in searching for paths for a space mission. The aim of this bachelor’s thesis is to implement a code that uses a tree search algorithm to find viable multi-gravity-assist trajectories from a Tisserand graph in an automatic manner. Several versions of the code have been implemented until reaching a definitive version that fulfills the requirements of the thesis. The final version uses a depth-limited search algorithm to explore a search tree generated automatically in an iterative process from a Tisserand graph, storing in the process all the found flybys sequences.