A Markovian based approach for autonomous space systems

On-board autonomy is becoming a crucial aspect of currently developed and future space projects, especially for deep space exploration missions. In the near future, spacecrafts will be able to receive, process and achieve high-level goals even in an uncertain or dynamically varying context. This paper presents a Markovian based approach in order to model on-board autonomy mechanisms. This approach fits the three layered autonomous space systems architecture and integrates a partially observable non-homogenous Markov model for the decisional layer with a Markov decision process for the operational layer. Autonomous spacecraft reconfigurability is particularly addressed.