This project has deepened my understanding of the core principles behind interplanetary travel, introduced me to computational optimization techniques, and enhanced my appreciation for the engineering marvels behind space exploration.
Interplanetary missions to distant targets like Enceladus, Saturn’s potentially habitable moon, demand precise planning and fuel-efficient strategies to be feasible. This project investigates the application of gravity assist maneuvers to design and optimise a trajectory from Earth to Enceladus. By carefully timing planetary flybys, a spacecraft can gain or lose velocity and alter its course without relying only on onboard propulsion, significantly reducing fuel consumption. The study begins by reconstructing NASA’s Cassini-Huygens mission, which used assists from Venus, Earth, and Jupiter to reach Saturn. Using Python and Lambert’s problem, the mission trajectory is precisely recreated, serving as a foundation for further optimisation. The second phase involves designing a new mission to Enceladus without relying on a predefined sequence of flybys. Given the complex, non-linear, and chaotic nature of interplanetary trajectory planning, a hybrid optimisation approach is implemented, combining COBYLA (a local optimiser) with MBH (a global search method) to efficiently explore the solution space. The resulting trajectory demonstrates significant fuel savings and highlights the effectiveness of gravity assists when it comes to interplanetary space travel.