State aggregation approximate dynamic programming for model-based spacecraft autonomy
Massimo Tipaldi, Luigi Glielmo · 2016
Spacecraft autonomy is a crucial aspect of currently developed and future space projects. This paper presents a Markovian Decision Process (MDP) based framework as a way of modeling spacecraft on-board autonomy mechanisms. Its applicability to the three layered autonomous space systems architecture is shown. Special attention is given to its deliberative layer, where Approximate Dynamic Programming (ADP) state aggregation techniques are applied to determine the corresponding sub-optimal policies. An example of such approach is presented, where it is shown how the MDP structure can determine some important properties of the calculated policy, such as the balancing of the spacecraft safety versus the completion of relevant mission objectives.