Modeling Considerations for Developing Deep Space Autonomous Spacecraft and Simulators

TL;DR

This work tackles the challenge of enabling deep-space autonomy by examining how subsystem model fidelity affects system-level reasoning. It analyzes a spectrum of subsystem models (power, Attitude GNC, navigation, and communications) and demonstrates, via MuSCAT, that interconnecting low- and high-fidelity models can support autonomous rendezvous with distant small bodies. The paper provides a qualitative fidelity taxonomy, discusses modeling trades, and offers a case study showing how cross-subsystem interactions yield robust situational awareness. Its findings inform the design of onboard autonomy algorithms and the development of physics-based simulators that can validate system-level behaviors in future deep-space missions.

Abstract

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. 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.

Figures (8)

• Figure 1: Models for spacecraft onboard autonomy. Models are a fundamental component of spacecraft onboard autonomy. They describe the behavior of onboard functional-level subsystems (blue), which in turn enables the development of functional-level autonomy algorithms including planning, prediction, estimation, control. Future missions to worlds with uncertain and dynamic environments will require system-level autonomy (orange) to develop and maintain situational awareness in nominal and off-nominal scenarios. Such system-level capabilities must aggregate and resolve information across various functional-level subsystems and at multiple time-scales, thereby also relying on the quality of the underlying models for robust reasoning and decision making.
• Figure 2: Autonomous small body exploration mission. We ground our analysis of subsystem model fidelity in the context of deep space exploration of small bodies with an autonomous SmallSat; a mission concept based on the Deep-space Autonomous Robotic Explorer (DARE) project at NASA JPL. While DARE consists of all mission phases ranging from cruise to proximity operations, we focus our assessment on the cruise and approach mission phases. These mission phases reflect nominal operating conditions suitable for assessing the role of model fidelity in four major spacecraft subsystems.
• Figure 3: Spacecraft design for small body exploration. For the autonomous rendezvous mission with a small body, we design a SmallSat spacecraft that consists of the main subsystems we analyze in this work. The spacecraft is powered by five solar arrays and equipped with several actuators for linear and angular control including a solar electric propulsion thruster, microthrusters, and reaction wheel assemblies.
• Figure 4: MuSCAT simulation software. We run our experiments in MuSCAT, a simulation tool that implements low-fidelity spacecraft and environment models, autonomous onboard flight software (both functional-level and system-level capabilities), science instruments and payload, and other spacecraft onboard components. Different from existing simulators, which often target high-fidelity simulation of a single spacecraft subsystem, MuSCAT integrates low-fidelity models across multiple spacecraft subsystems to support the prototyping and simulation of mission concepts that may benefit from onboard autonomy.
• Figure 5: Power subsystem case study. Power onboard the spacecraft is generated by solar arrays and directly distributed to electrical components and batteries. The results above are the predictions of low-fidelity power generation, distribution, and battery state of charge models used during the small-body mission (see Figure \ref{['fig:SB-mission']}). Generated power predictions fluctuate with the changing attitude of the spacecraft, while peaks in consumed power correspond to firing solar electric propulsion thrusters. Notice that when more power is consumed than generated, the predicted battery state of charge gradually decreases until thirty percent, at which point the system-level software executive schedules an immediate charging cycle.