Simulating Operational Concepts for Autonomous Robotic Space Exploration Systems: A Framework for Early Design Validation

During mission design, the concept of operations (ConOps) describes how the system operates during various life cycle phases to meet stakeholder expectations. ConOps is sometimes declined in a simple evaluation of the power consumption or data generation per mode. Different operational timelines are typically developed based on expert knowledge. This approach is robust when designing an automated system or a system with a low level of autonomy. However, when studying highly autonomous systems, designers may be interested in understanding how the system would react in an operational scenario when provided with knowledge about its actions and operational environment. These considerations can help verify and validate the proposed ConOps architecture, highlight shortcomings in both physical and functional design, and help better formulate detailed requirements. Hence, this study aims to provide a framework for the simulation and validation of operational scenarios for autonomous robotic space exploration systems during the preliminary design phases. This study extends current efforts in autonomy technology for planetary systems by focusing on testing their operability and assessing their performances in different scenarios early in the design process. The framework uses Model-Based Systems Engineering (MBSE) as the knowledge base for the studied system and its operations. It then leverages a Markov Decision Process (MDP) to simulate a set of system operations in a relevant scenario. It then outputs a feasible plan with the associated variation of a set of considered resources as step functions. This method was applied to simulate the operations of a small rover exploring an unknown environment to observe and sample a set of targets.

Automated summary

The concept of operations (ConOps) during mission design is crucial for meeting stakeholder expectations. While ConOps is often evaluated based on power consumption or data generation, highly autonomous systems require an understanding of their reaction in operational scenarios. This study provides a framework for simulating and validating operational scenarios for autonomous robotic space exploration systems, utilizing Model-Based Systems Engineering (MBSE) and Markov Decision Process (MDP) to generate feasible plans and assess resource variations. Applied to a small rover, this method enhances the design process by testing operability and performance in different scenarios.