Air Force asks industry to develop human-machine interface for machine autonomy in satellite control

KIRTLAND AIR FORCE BASE, NM – US Air Force researchers are calling on industry to develop new types of human-machine interfaces to enable machine autonomy in the control of reconnaissance satellites, which could improve global surveillance capabilities.

Officials of the Space Control Technology Branch of the Space Vehicles Directorate at the Air Force Research Laboratory at Kirtland Air Force Base, NM, issued a solicitation on Wednesday (FA9453-21 -S-0001) for Advanced Space Technology Research – Accelerated Innovative Software and Hardware (STAR-FISH).

The tender relates to call four of the STAR-FISH project – Human-Machine Interface for Autonomous Satellite Systems – which aims to enable seamless and agile human-machine interaction by building trust between satellite operators and to reinforce the autonomy capacities of the satellites with advanced human capacities. – machine interface technology.

Air Force researchers seek to collaborate with industry to develop and integrate breakthrough space capabilities by developing a new human-machine interface for autonomous satellite systems.

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This collaboration should allow the American air and space forces to optimize machine autonomy and decision support with new functionalities in advanced human-machine interfaces for satellite control.

Researchers are asking industry to submit white papers describing human-machine interface concepts for autonomous satellite systems, as well as ways to modify existing satellite autonomy and control technologies.

For example, researchers could install one or more satellites in test beds to perform an inspection or a docking orbit around another cooperative satellite. The system is envisioned to have three controllers: an automatic or stand-alone primary controller; a backup controller provided via a runtime assurance wrapper; and a human operator.

In addition to these automatic controllers, the human operator can override them with a scripted command. Runtime Assurance monitors the primary controller and the scripted controller, and intervenes with a backup command when it detects a need to intervene to prevent satellite collisions and maintain satellite camera pointing restrictions.

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This training scenario will help define the human-machine interface prototype work for this contract to create an intuitive human-machine interface that facilitates the understanding and projection of the autonomous controller while making the most of directivity and the awareness shared between the human operator and the autonomy of the satellite. aptitude.

This man-machine interface will be written in a widely available programming language such as JavaScript, Java, Python, C or C++; describe the physical characteristics of the operator interface, controls, and design approach; provide transparency for autonomous control algorithms to include current state and projected future state; display runtime assurance outputs such as fault status and lockout conditions; provide data to the autonomous controller such as fuel limits per mission, fuel limits per maneuver, time limits, optimal time to complete, and lighting requirements; and will display autonomous outputs such as fault status and lockout conditions.

Industry white papers should describe the overall approach to developing a human-machine interface for an autonomous satellite; and software issues such as virtualized or containerized software using industry standard virtualization or containerization technology such as Docker.

Those who submit promising white papers will be invited to submit formal proposals. Interested companies should upload the white papers no later than May 9, 2022 to DoD Safe Online at https://safe.apps.mil.

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Email the Heavy Aircraft Contract Specialist at [email protected] at least three days prior to download to obtain a DoD Safe deposit request.

Email your questions or concerns to Avion Lourde at [email protected]; Robert Jefferys at [email protected]; Michelle Simon at [email protected]; or Michael Lopez at [email protected]

More information is online at https://sam.gov/opp/87dd122fc73e415d8f9c23682177bfc1/view.