In Pursuit of Autonomous Mission Management in Space

Due to the unique set of constraints that need to be met for spacecraft mission software, the design of onboard autonomy needs to be carefully designed with various considerations. Although autonomy can bring many potential benefits to space missions such as simplified operations, enhanced mission capabilities, and overall cost savings, the trade-off is increased software complexity, which correspondingly increases the difficulty of software validation and verification, as well as increases the requirements of onboard system resources. The aim of this research is to provide a design and proof-of-concept of autonomous mission management software suitable for a wide range of potential space missions. First, the concept of autonomous image classification and processing is covered, including the design of various types of classifiers and a solution to assist users with training their parameters. This phase of research provides a baseline for mission operations that is used by the other two phases. Next, the design of a reusable schedule design and execution framework is covered, which can be used to allow mission operators to schedule sequences of heavily-constrained tasks for onboard execution with conflicts autonomously managed. This phase ties in the previous phase and shows how a schedule of tasks can be constructed and uploaded to enable autonomous image classification and handling while accounting for variability in task execution status and resource availability. Finally, the established schedule management framework is applied to the context of multi-spacecraft missions and the process of testing and code analysis is explored in further detail. This final phase of research demonstrates how the designed software architecture can enable robust decentralized satellite cluster coordination for tasks such as synchronized data capture