Modeling Considerations for Developing Deep Space Autonomous Spacecraft and Simulators

• Published in: 2024 IEEE Aerospace Conference pp. 1 - 20
• Main Authors: Agia, Christopher, Vila, Guillem Casadesus, Bandyopadhyay, Saptarshi, Bayard, David S., Cheung, Kar-Ming, Lee, Charles H., Wood, Eric, Aenishanslin, Ian, Ardito, Steven, Fesq, Lorraine, Pavone, Marco, Nesnas, Issa A.D.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 02.03.2024
• Subjects: Analytical models; Computational modeling; Productivity; Schedules; Software algorithms; Space missions; Space vehicles
• DOI: 10.1109/AERO58975.2024.10521055

Over the last two decades, space exploration systems have incorporated increasing levels of onboard autonomy to perform mission-critical tasks in time-sensitive scenarios or to bolster operational productivity for long-duration missions. Such systems use models of spacecraft subsystems and the environment to enable the execution of autonomous functions (functional-level autonomy) within limited time windows and/or with constraints. These models and constraints are carefully crafted by experts on the ground and uploaded to the spacecraft via prescribed safe command sequences for the spacecraft to execute. Such practice is limited in its efficacy for scenarios that demand greater operational flexibility.To extend the limited scope of autonomy used in prior missions for operation in distant and complex environments, there is a need to further develop and mature autonomy that jointly reasons over multiple subsystems, which we term system-level autonomy. System-level autonomy establishes situational awareness that resolves conflicting information across subsystems, which may necessitate the refinement and interconnection of the underlying spacecraft and environment onboard models. However, with a limited understanding of the assumptions and tradeoffs of modeling to arbitrary extents, designing onboard models to support system-level capabilities presents a significant challenge. For example, simple onboard models that exclude cross-subsystem effects may compromise the efficacy of an autonomous spacecraft, while complex models that capture interdependencies among spacecraft subsystems and the environment may be infeasible to simulate under the real-world operating constraints of the spacecraft (e.g., limited access to space-craft and environment states, and computational resources).In this paper, we provide a detailed analysis of the increasing levels of model fidelity for several key spacecraft subsystems, with the goal of informing future spacecraft functional- and system-level autonomy algorithms and the physics-based simulators on which they are validated. We do not argue for the adoption of a particular fidelity class of models but, instead, highlight the potential tradeoffs and opportunities associated with the use of models for onboard autonomy and in physics-based simulators at various fidelity levels. We ground our analysis in the context of deep space exploration of small bodies, an emerging frontier for autonomous spacecraft operation in space, where the choice of models employed onboard the spacecraft may determine mission success. We conduct our experiments in the Multi-Spacecraft Concept and Autonomy Tool (MuSCAT), a software suite for developing spacecraft autonomy algorithms.