Stochastic Trajectory Design of Deep Space Rendezvous for Low-Cost Mars Sample Return

Abstract

Returning samples from Mars is expected to provide significant scientific knowledge about the formation of planets and the origin of life. The LifeSpringsMars Mission, a novel mission concept designed by a multinational consortium from Australia, Japan, the United States, and New Zealand, aims to return samples from the Columbia Hills on Mars at a low cost. To achieve cost reduction, LifeSpringsMars mission plans to transfer samples in deep space instead of using the conventional method of transferring samples in Mars’ low orbit. However, relaying samples in deep space has a high risk of losing samples in deep space, so trajectory design that accounts for uncertainties of Mars Ascent Vehicle is required. This paper presents a method to optimize the rendezvous trajectories between multiple spacecraft by extending stochastic trajectory optimization that takes account of disturbances. Introducing the Unscented Transform, the method lets us compute and optimize the stochastic trajectories. Finally, numerical examples demonstrate the feasibility of the proposed mission architecture.