SCALES: Spacecraft Compartmentalized Autonomous Learning and Edge-computing System (SCALES)

This work proposes to develop and test an integrated hardware / software system that enables the deployment of Machine Learning (ML) algorithms on-orbit. This system, SCALES (Spacecraft Compartmentalized Autonomous Learning and Edge-computing System), is an integration of commercial-off-the-shelf edge computing hardware that enhances on-orbit computing and a reusable software architecture that provides reliability and mission assurance. Acclaimed for its use on the Mars Ingenuity Helicopter, the open-source F’ flight software from NASA’s Jet Propulsion Laboratory (JPL) is the framework SCALES is based on. The proposed technology is enabling for small spacecraft operating autonomously, which there is known need for, and is a significant enhancement for small spacecraft networks conducting missions ranging from autonomous detection to collaborative science.

This proposal addresses the need for advanced autonomous functionality in SmallSats that is fueled by continual progress in computational power and application-specific hardware acceleration. This would enhance satellite productivity by enabling autonomous decision-making which is crucial for Cislunar and deep space operations.

This is early/mid-stage (TRL 4) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

None of these are guaranteed paths for this specific project — TechPort itself doesn't have an "apply" button. Reaching out to the contact(s) above with a specific question is usually the fastest way to find out what's actually open.