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NASA NTRS · 20210020182

Intra-Spacecraft RFID Localization

Jesse Berger·Patrick W Fink·Lazaro Daniel Rodriguez
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Abstract

Presentation addresses machine learning approaches to RFID localization. Experiences with the REALM-1 system on ISS are shared, as are the expansions with REALM-2 and REALM-3.

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RFIDmachine learningautonomous logistics management

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Jesse Berger, Patrick W Fink, Lazaro Daniel Rodriguez. Intra-Spacecraft RFID Localization. https://ntrs.nasa.gov/citations/20210020182

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Short Window Intra-Spacecraft RFID Localization

Logistics management has emerged as a key component to activities conducted in space. The RFID Enabled Autonomous Logistics Management (REALM) system has played a key role in providing cargo tracking capabilities in the noisy environment of the ISS. Currently, the inferencing engines used by REALM to predict the location of RFID tagged items operate on an hour of data. Movements aboard space stations occur on the scales of seconds. In this work we propose a new inferencing engine, that produces an embedding space that represents the location of RFID marked cargo on the scale of 30 seconds to 2 minutes of data, allowing for the categorization of movement of cargo, and predictions of a coarse location in less time than existing engines.

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