ROME, N.Y. – U.S. Air Force researchers are asking for industry help in making big improvements in small, lightweight embedded computing for artificial intelligence (AI) and machine learning (AI/ML) capabilities in an embedded computing environment.

Officials of the Air Force Research Laboratory’s Information Directorate in Rome, N.Y., issued a broad agency announcement on Thursday (FA875019S7007) for the Robust and Efficient Computing Architectures, Algorithms, and Applications For Embedded Deep Learning.

The potential $99 million five-year project seeks to achieve orders of magnitude improvement in size, weight and power (SWaP) for deploying artificial intelligence and machine learning capabilities in an embedded computing environment.

Researchers are asking industry for embedded computing technologies with improved autonomy, intelligence, and assurance for command, control, communications, computers, intelligence, surveillance and reconnaissance (C4ISR) applications in SWaP-constrained Air Force applications. Of particular interest are advanced efficient computing architectures, algorithms, and applications.

The Air Force needs unconventional computing architectures for pattern recognition, event reasoning, decision making, adaptive learning, and autonomous tasking on energy-efficient Air Force manned and unmanned aircraft.

A major focus area is neuromorphic computing — or brain-inspired computing that involves processors more advanced than more-traditional the Von Neumann architectures. This kind of design could lead to unconventional circuits based on emerging nanotechnology like memristors and nano-photonics, researchers say.

There is a need for in-hardware and efficient adaptive learning architectures and algorithms, as well as novel artificial intelligence and machine learning algorithms optimized for neuromorphic computing hardware architectures.

Air Force researchers want to demonstrate modular computing for future real-time embedded plug-and-play capabilities. Technologies could include artificial intelligence and machine learning models for big data analytics for sensor processing; data fusion algorithms for situational awareness and sense making; and autonomous decision making.

Modular designs should support interchangeable sensors, with automatic software reconfiguration based on available resources. Companies participating should choose computing and interfaces to accommodate expected growth in data bandwidth in future systems. SWaP optimization is a priority.

Other considerations are ways to validate and improve scalability and security for artificial intelligence and machine learning technologies; deep-learning models and algorithms; and power-aware and energy-optimized deep learning models and algorithms for embedded computing.

Companies interested should email white papers no later than 27 May 2022 to the Air Force’s Albert Frantz at albert.frantz@us.af.mil. Other deadlines for white paper submissions are 30 April and 31 July 2019; 29 May 2020; and 28 May 2021.

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KIRTLAND AIR FORCE BASE ― The Air Force Research Laboratory will begin maneuvers today, Oct. 20, as the first-ever inspection mission to support real-time on-orbit spacecraft anomaly resolution operations. 

This effort will be a rendezvous between the experimental Mycroft satellite and a second experimental AFRL satellite called the Small Satellite Space Surveillance System, or S5. The S5, launched Feb. 22, 2019, is a small satellite designed to test affordable SmallSat space situational awareness constellation technologies. 

AFRL has experienced communication challenges with the S5 satellite and has had no communication with S5 since March 2019. Operators confirm that the spacecraft is alive and maintaining solar power by tracking the sun, but without communications S5 cannot perform its experiments. Mycroft is an AFRL-developed SmallSat launched with the EAGLE satellite April 14, 2018.

Mycroft separated from EAGLE and drifted about 35 kilometers away before transiting carefully back to within a few kilometers of EAGLE. It has performed space situational awareness, or SSA, and satellite inspection experiments over the past 18 months. The Mycroft experiment is aimed at improving autonomous rendezvous and proximity operations, or RPO, SSA, satellite inspection and characterization, and autonomous navigation technologies. 

Mycroft satellite operators will initiate a series of maneuvers to rendezvous with S5 near 6 degrees East longitude at Geosynchronous Orbit to support anomaly resolution efforts. EAGLE will also maneuver into the vicinity of the RPO to observe the inspection from a safe distance. Mycroft will inspect the S5 satellite and provide operators with verification of the fully-deployed solar array and of the sun pointing orientation. Mycroft will then examine the exterior of the S5 spacecraft to search for damaged components such as the solar array and antennas. 

The Mycroft-S5 RPO will occur in stages over a period of several weeks, demonstrating the utility of inspection and characterization capabilities in a real-world satellite recovery. AFRL is planning to transition operations to Air Force Space Command later this year.

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