Study of Jovian Tours for mission design

Abstract

Recent advances in optimization methods have dramatically expanded our ability to design complex interplanetary missions. Space exploration remains one of humanity’s most ambitious endeavors, and the efficiency with which mission trajectories are planned directly impacts both scientific return and mission cost. In particular, the use of multi-gravity-assist maneuvers has become central to reducing propellant requirements and enabling tours of multiple targets (such as Jupiter’s Galilean moons) within a single mission. This project extends AMGATO—a preliminary mission-design framework based on gravity assists—so that it can automatically generate sequences of multiple flybys around Jupiter’s Galilean moons. The focus is on filling the gap in AMGATO’s sequence-generation stage (the Tisserand PathFinder, TPF) by incorporating the identification and targeting of p:q resonant orbits, which enable repeated satellite encounters without additional propellant expenditure. A new module computes the constant-energy levels corresponding to resonances and overlays them on the Tisserand graph, a graphical tool that shows the possible pathways to go from one celestial body to another. A routine then detects where each contour in the graph crosses these resonance lines and inserts the appropriate nodes into the graph-traversal algorithm. This routine is designed in modules to coexist with existing constraints, allowing users to enable or disable each feature independently. Benchmark tests in a representative Jovian scenario verify that the enhanced TPF successfully produces resonant-flyby sequences while respecting the other restrictions. The graphical user interface has been updated to visualize resonance bands, toggle resonance and other criteria interactively, and display intermediate nodes along each contour. Validation against a trajectory retrieved from the literature confirms that the TPF extension can replicate key sequences from real missions. This sets the stage for future work integrating resonance data into AMGATO’s optimizer to generate complete, fuel-efficient Jovian tour trajectories.