## 1 Introduction
They may test whether the designed system has enough resources for battery or data storage to complete the expected operational scenario(s). At the same time, it can help validate and verify the designed functional architecture. For example, if there is the need to consider additional operative modes or a function that was overlooked during the initial design phases. The simulation of the operational scenarios can help with stakeholder consultation. Presenting a straightforward simulation of resource variation associated with a given scenario can help better frame the mission and pinpoint discrepancies between what is expected from the stakeholders and what the designers are providing. This study innovates from the state of the art, as follows:  
* It implements a simulation-backed analysis to study and validate the feasibility of operational scenarios;
* It stores all the mission instances in an MBSE model and provides traceability of changes;
* It defines the variables defining and MDP space starting from the resources defined in the MBSE model. The knowledge base for the study is the MBSE model that encodes all the parameters and products of the study. The proposed framework provides a plan that can be easily interfaced with middleware, such as the Robot Operating System (ROS). Hence, it will be possible to simulate the studied operational scenario(s) directly on an analogue robotic platform or a physics-based simulator to cross-validate the identified operational capabilities. For instance, [16] proposed a virtual mission operation framework with a validation-in-the-loop of the design applied to the satellite and leveraging STK to simulate the autonomous manoeuvres' sequences. However, nothing comparable has been found in the literature for planetary surface robotic systems. As highlighted in Figure 1, the presented framework identifies the main mission driver for the definition of the mission scope. The focus then shifts toward defining the MBSE model in its functional and physical declinations. The MBSE model is then morped into a Markov Decision Process (MDP) and applied to a reference scenario. A plan is computed, and if its output is satisfying, the designers may proceed with their study or test it on analogue platforms. The study case is a small rover moving on the lunar surface. The designed system weighs around 30 kg, with 3.3 kg of payload and an expected power consumption around 100 W. It is assumed that the rover can freely recharge its batteries and relay its communications to Earth or another system on the surface. Therefore, no specific flight rules are imposed on when to communicate or recharge the batteries. The system should observe different waypoints and sample some of them based on their scientific reward. All the decisions can be left to the solving algorithm. After this initial overview of the context and objective of this research, the remaining of the paper will be organized as follows: Section 2 provides a small overview of similar studies, Section 3 focuses on the background theories and definition guiding the proposed framework, Section 4 provides a set of sample results that can be obtained with the framework, Section 5 draws the main conclusions on this study and details its future development.