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Center Independent Research & Development: GSFC IRAD

Supervised-machine Learning for Intelligent Collision Avoidance Decision-making and Sensor Tasking

Completed Technology Project

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Project Description

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Supervised-Learning parameter-set determination for satellite collision avoidance using neuro-fuzzy logic based decision making.

Building an autonomous architecture that uses directed self-learning neuro-fuzzy networks with the aim of developing an intelligent autonomous collision avoidance decision-making process; including ground and space based sensor tasking and data transfer for on-board autonomous maneuver decision.

Anticipated Benefits

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This will allow for robust autonomous decision making involving the improvement of the initial uncertainties, knowledge of information quality and decision fidelity that will provide potential cost savings for sensor operations, reduce false alarm maneuvers and improved asset protection.

Project Library

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Primary U.S. Work Locations and Key Partners

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Organizations Performing Work	Role	Type	Location
Goddard Space Flight Center (GSFC)	Lead Organization	NASA Center	Greenbelt, Maryland
Purdue University-Main Campus	Supporting Organization	Academia	West Lafayette, Indiana