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METRON, INCORPORATED SBIR Phase I Award, May 2021

A SBIR Phase I contract was awarded to Liteweaver Technologies, Inc. in May, 2021 for $124,921.0 USD from the NASA.

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Contents

sbir.gov/node/2117089
Is a
SBIR/STTR Awards
SBIR/STTR Awards

SBIR/STTR Award attributes

SBIR/STTR Award Recipient
Liteweaver Technologies, Inc.
Liteweaver Technologies, Inc.
0
Government Agency
NASA
NASA
0
Award Type
SBIR0
Contract Number (US Government)
80NSSC21C02890
Award Phase
Phase I0
Award Amount (USD)
124,9210
Date Awarded
May 7, 2021
0
End Date
November 19, 2021
0
Abstract

Asnbsp;we strive to createnbsp;space systemsnbsp;that arenbsp;more capable andnbsp;conductnbsp;manned and unmannednbsp;missions further from Earth,nbsp;pre-mission planning will be insufficient to handle uncertainty in operations. This is further exacerbated by communications limitations coupled with the absence of human mechanics onboard to handle issues that may arise over the course of a mission. Thesenbsp;realities compoundnbsp;mission risks.nbsp;In particular, missionnbsp;control may not have accurate enough situational awarenessnbsp;tonbsp;be able to providenbsp;timelynbsp;decision support.nbsp;To address such risksnbsp;andnbsp;account for the uncertainty of extended-duration operations, NASA needs robust and explainable fault management solutions that incorporate machine forethought, where the platform responds appropriately to situations that can impact platform health and mission reliability.Metron proposes to develop a full-system fault management solution for autonomous space platforms. Our solution will address the technical challenges of providing short-term fault mitigation that evaluates long-term platform considerations, preemptively planning fault mitigation procedures, and properly responding to faults when mission goals and fault mitigation procedures come in conflict. Our fault management solution fuses fault detection, diagnosis and mitigation with current mission primitives, priorities, and platform capabilities. It will respond to system degradation, faults, and lost platform capabilities in such a way that preserves mission-relevant capabilities by leveraging an expert system ontology for self-assessed capability analysis, adaptive search techniques for fault mitigation, and statistical and symbolic fault detection and identification. This solution will provide high-level functions normally performed by human operators, such as determining the ideal machinery plant alignments to facilitate a given mission, fault diagnosis and recovery, and reconfiguring of the machinery plant alignment for increased performance.

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