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Logistics Reduction: RFID Enabled Autonomous Logistics Management (REALM) (LR-REALM)

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Project Description

REALM-1 EMBER Reader

The Advanced Exploration Systems (AES) Logistics Reduction (LR) project Radio-frequency identification (RFID) Enabled Autonomous Logistics Management (REALM) task focuses on automated localization and inventory of all physical assets pertaining to, or within, a vehicle utilizing RFID technologies. REALM technology can provide detailed data to enable autonomous operations such as automated crew procedure generation and robotic interaction with logistics and deep space habitats; this is especially of value where communication delays with Earth drive the need for self-reliance.  The REALM project is conducting a series of ISS technology demonstrations.  The first ISS demonstration, REALM-1, started in February 2017 and was completed at the end of FY19 when it was transitioned to the ISS Program for sustaining operations.  The second ISS demonstration, REALM-2, was commissioned in late 2021 and will continue through 2024.  The third demonstration, REALM-3, was commissioned in December 2022 and is currently operating as a payload.  

The problem of locating all mission items within and around a vehicle is complicated by many factors, including the desire to rely only on passive tags, restrictions on RF transmit power, layered storage of logistics, the challenging RF scattering environment of vehicles, and metallic storage enclosures. To address these complex problems, associated RFID technologies are partitioned into three classes:

Dense Zone technologies

Sparse Zone technologies

Complex Event Processing

Dense Zone technologies pertain to regions of high stowage densities where sufficient signal penetration from external antennas is unlikely.  Sparse zone technologies address all areas exclusive of the dense zones, including the open areas of a habitat module. These technologies include fixed-zone readers, steered-beam antenna readers, and mobile readers such as robotic elements, crew-held readers, or crew-worn readers. With both dense and sparse zones, guaranteed real-time, on-demand reads may not possible, so “smart” applications, e.g., Complex Event Processing (CEP), are required to infer item locations based on context from the sparse and dense zone technologies.

Mission details might drive a specific combination of one or more of these three technologies. Therefore, in addition to maturing these individual technology areas, the LR REALM team will learn which combinations of technologies are best suited for specific missions. For example, dense zone technologies can be made highly accurate but typically entail greater mass compared to sparse zone technologies. Sparse zone technologies typically cover greater volume per reader, but are more apt to miss tags because the radiated power density at the tag is typically lower in comparison. The operational intelligence provided by CEP can likely be traded for the size, weight, and power associated with dense and sparse zone technologies, but the extent, and specific implementation, remain as knowledge gaps to be addressed by this effort.

The REALM task is divided into five sub-technology projects: REALM-1, -2, -3, -6DoF, and REALM-RFID Sensing.

REALM-1

REALM-1 infrastructure was developed and evaluated on ISS, with RFID open-air readers and antennas deployed in ISS Node 1, U.S. Laboratory, and Node 2. A ground-based CEP center receives data from the ISS open-air readers and provides operational intelligence that infers item locations. The REALM-1 core system was considered sufficiently matured in FY19 and was transitioned to an operational ISS system midway between FY19 and mid-FY20, so that ISS became responsible for sustaining engineering of flight and ground REALM-1 assets.

With the REALM-1 on-orbit system having been fully transitioned from Payload status to System on ISS, the CEP/machine learning approaches remain a central focus going forward.  This task serves four primary purposes. First, the largest improvements to date in CEP localization occurred with machine learning classifier approaches in FY20.   Trials on five different machine learning (ML) algorithms continue to further extract value from this technology as deeper knowledge of both the ML tools and the problem space evolve.  Second, new context from REALM-2 and REALM-3 are being incorporated into the CEP, a critical step in understanding the value, impacts, and interdependencies of fixed reader systems, mobile reader systems, and stowage reader systems in ALM.  Third, the REALM Analog at JSC, which is a horizontal cylindrical habitat test bed similar to HALO in dimensions, will be employed to understand the impacts of habitat shell geometry and interior stowage regions and furnishings on localization accuracy.  Fourth and finally, the REALM Analog will be used to better understand and improve the ISS CEP performance, given the ability to better control experiments with an increased truth data size.

Other ongoing CEP work includes continuation of tag motion inferences and mining of crew procedures.  Identifying tag motion enables other capabilities such as determining items that are being transferred to a visiting vehicle – either as intended or otherwise.  Mining of ISS databases allows for additional CEP context in estimating item locations and enables auto-alerts when REALM detects that logistics required in next-day’s procedures are not where IMS indicates.  ISS database mining efforts were initiated in late FY20 and initial results provided corroboration with the ISS database, or alerted when REALM detected significant deviations.

Other ISS experiments at various stages of maturity are being developed with anticipated use of the REALM-1 infrastructure.  These include the REALM-2 and REALM-3 systems, described in more detail below, and the 6-Degrees of Freedom (DoF) Wireless Hybrid Identification and Sensing Platform for Equipment Recovery (WHISPER).

The REALM-1 system is baselined for the Gateway Program’s HALO, iHAB and Esprit Refueling Module elements.  Up to 8 REALM-1 antennas willbe placed in HALO, with primary functionality providing assurance of cargo transfer between the Logistics Module and the Human Lander System.  The system will also be capable of tracking cargo to and from the Orion vehicle.  REALM instrumentation in additional Artemis and  Gateway elements is expected.

REALM-2

REALM-2 (aka “Recon”) is an AES LR RFID interrogator payload on the Space Technology Mission Directorate (STMD) Next Generation Free-Flyer (NGFF), aka “Astrobee.”  REALM-2, located inside the ISS, is capable of conducting inventory missions, or audits, as well as search missions to locate lost items and homing missions to pinpoint item locations.  Another capability afforded by REALM-2, referred to as “CEP Context,” is the CEP integration of data received over the four REALM-2 antennas with the REALM-1 data to improve tag localization accuracy.  The REALM-2 flight system was delivered for a November FY20 launch.  Crew installation of REALM-2 was completed in January 2021 with commissioning and checkout completed and further experiments occurring through FY23.

Two REALM-2 science missions were executed in FY21.  In Science-1, Astrobee was perched inside the hatch of the Permanent Multi-Purpose Module (PMM), giving REALM-2 a vantage point with visibility into the largest logistics stowage volume on ISS.  The number of unique tags read, as a fraction of all tags in PMM (as reported by the ISS database), jumped from just under 3% from REALM-1, only, to 65% by REALM-2.  In addition, several stowage tracking anomalies were uncovered by REALM-2 during this three-hour mission.  In a Science-2 mission, the homing functionality was further tested, and code errors were discovered in the pitch and yaw commands, attributed to inverted test article orientation required for ground testing.  In FY22, the code error was corrected and confirmed in Science-3 mission, in which REALM-2 guided Astrobee on several successful homing runs.  In Science-4, Astrobee was perched in various positions and translated in JPM in order to assess RFID inventory capture effectiveness in perched versus mobile scenarios.  A Science-5 mission is being planned for September 2022 in which Astrobee monitors for crew cargo translations in an attempt to emulate Gateway logistics transfers.

REALM-3

In general terms, REALM-3 is a dense zone reader enclosure in the form of “smart” drawers, cargo bags, and work bags, where a large number of RFID-tagged items occupy a relatively small volume.  Open reader systems such as REALM-1 do not typically handle regions such as this with high read accuracy, either due to the high tag density or metallic racks/enclosures.  Studies with REALM-1 indicate that the real time RFID audit accuracy in NOD1 ranges from 72-76% of all tagged items there, as reported by the ISS database; REALM-3 technology can significantly improve total read accuracy.

In FY21, flight development of REALM-3 under the ISS Payload named “RFID-Smart Sensing” began with subsequent deployment beginning in November 2022.  “RFID-Smart Sensing” comprises Smart Stow and the Drawer Monitor System.  Both of these technologies were conceived to overcome the aforementioned challenges with dense packing and/or items with metal or liquid content.  The Smart Stow system comprises RFID signals routed to antennas embedded in a stowage enclosure.  While highly effective, Smart Stow requires too much instrumentation to replicate throughout every rack on a vehicle.  The Drawer Monitor System complements Smart Stow and entails much lower mass, so it is more amenable to wide proliferation throughout a vehicle, with Smart Stow allotted to stowage enclosures of frequent usage. The Drawer Monitor System is based on RFID sensor technology and hence is addressed in that section below.

In FY20, a new approach was initiated to increase the RFID coverage area with significantly lower mass than would be required by simply adding more readers and antennas.  This approach, termed “HYDRA” (HYper-Distributed RFID Antenna), is based on switched multiplexing of one or more of the reader RFID ports.  The increased proliferation of the RFID signal is anticipated to allow blurring of the “dense” and “sparse” zones, as a single reader could support both using HYDRA.  This concept was rapidly advanced from TRL 3 to TRL 6 by the end of FY21, and is now integrated within the Smart Stow textile insert in the ISS NOD1S4 rack.  A reader instance, of the same type used by REALM-1, is dedicated to Smart Stow, and will be scheduled on intervals of nominally 15 minutes to successively interrogate each of four quadrants in NOD1S4.  Each quadrant contains several HYDRA nodes and six antennas.  Although this instrumentation is much denser than is anticipated in future vehicles, the intent is to fully test a HYDRA system in ISS that would eventually be distributed over a significantly larger vehicle volume.

REALM-6DoF (6 Degrees of Freedom)

The REALM team is collaborating with Advanced Systems and Technologies Inc. (AS&T) to advance an ultra-precise WHISPER (Wireless Hybrid Identification and Sensing Platform for Equipment Recovery) RFID tracking system that will be compatible with the REALM-1 infrastructure.  The AS&T WHISPER technology is being developed under a Small Business Innovative Research (SBIR) award.  AS&T's new tag and tracking system enhancement permits demonstrated tracking accuracies at centimetric and, theoretically at, millimetric levels as well as orientation tracking. In FY20 and FY21, AS&T developed a reduced size infrared projector, referred to as the “Intermediate WHISPER Projector” (IWP).  Although not as small as the eventual target, its 3”x3”x3” size renders it suitable for an ISS technology demonstration experiment.

In Q4 of FY21, AS&T performed two virtual demonstrations of the WHISPER technology, with highlights including tracking of a human subject, a translated articulated robotic appendage, and a helicopter drone.  At the end of FY21, AS&T delivered to NASA six IWP projectors.  In FY23, AS&T set up and calibrated the projectors at JSC, with the goal of providing demonstrations and evaluations for prospective end user applications, including robotic manipulation of logistics and resolution of the Human Research Program (HRP) knowledge gap regarding how the crew utilizes habitat volume.

 

REALM-RFID Sensing

The REALM team is leveraging RFID integrated circuits (ICs) that offer serial interfaces in addition to the more conventional over-the-air radiated interface to an RFID tag.  The serial interface permits attachment of a microcontroller and low-power sensors such that the resulting tag is capable of returning sensor data in addition to the typical code that uniquely identifies the tag.  In FY20, the REALM team began applying this technology in the form of RFID tags that monitor door motion, and in FY21 began development of a flight Drawer Monitor System (DMS).

In the DMS concept of operation, the REALM-1 system will read tagged items until they are placed inside of a drawer and cease to be “seen.”  Data pulled from the door-mounted DMS tags will relay door motion events and the time of those events.  The CEP system will use that sensor data from the door tag, in addition to the data read from the conventional RFID tag on the item, and wil infer whether the tag has been moved into a particular drawer.

In FY22, the REALM team completed fabrication, assembly, and certification of the flight Drawer Monitor System tags and the system was launched to ISS in November 2022.  Although the DMS tags were designed for a 5+ year life, the batteries experienced an anomalous drain so that only 4 of the 16 deployed tags were functional upon deployment.  However, over the operational period of a month, the functionality of the tags demonstrated the basic concept in helping to confirm logistics transfers.  The root cause of the anomaly was traced to a firmware bug.  The DMS tags were returned for firmware reflash and are expected to be relaunched in FY24.

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