Autonomous Science and Technology for Responsive Adaptation (ASTRA)

Overview

Development stage

In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.

High-impact designation

Not high-impactSource: c) Not high-impact

Impact justification

Not reported

Start date

Not reported

Withheld from public reporting

NoSource: a) No

Mission

Topic area

Science

Operational functions

No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

The ASTRA team is working to develop and mature capabilities for extensibility and science autonomy. Extensibility would give us the ability to add and collaborate among multi-organizational assets to form a new, distributed and disaggregated mission. Our onboard Science AI would allow missions to make decisions for future action onboard using real-time data, enabling adaptable and responsive exploration and discovery.

Expected benefits

Intelligent and interoperable extensible architectures for space developed and deployed under ASTRA are poised to become a “get with it or get out” technology, similar to the protocols for the internet, bluetooth, etc. We utilize two key capabilities developed by the ASTRA team in FY25: 1) Intelligent Extensible Mission Architectures (IEMA) and 2) Objective-Based Artificial Intelligence (OBAI). IEMA code includes the ability to broadcast capabilities and requests, and to join in a coordinated effort with assets that were previously unknown. OBAI code includes the ability to use established observational priorities to analyze data in real-time, make recommendations and decisions for future action based on the perceived importance of observation(s), and carry out actions in a new, coordinated multi-asset effort.

System outputs

classification, prediction, confidence in prediction, anomalies

Technology

AI classification

Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…

System name(s)

Not reported

Custom-developed code

Not reported

Public source code

Not reported

Sourcing

How it was built

Not reported

Vendor (as reported)

Not reported

Vendors (standardized)

None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII

Not reported

Privacy Impact Assessment

Not reported

Authorization to Operate

Not reported

Demographic features

Not reported

Training and evaluation data

Not reported

Federal Data Catalog

Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Potential impacts and how they were identified

Not reported