RecentNews Archive

Astrobee successfully locates RFID tag aboard the ISS!

Check out this video of the REALM RFID project flying on the ISS Astrobee free-flying robot!  METECS personnel were thrilled to see their hard work pay off and witness the robot able to sense and fly toward a particular RFID tag (which was celebrated by Astronaut Shannon Walker with a fist pump!). Congratulations to the METECS employees who have put so much effort into the RFID REALM project.

VIDEO:

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Training System Simulator Milestone!

Special Purpose Dexterous Manipulator (SPDM) training was performed using the Training System (TS) simulator for the first time ever last week! The TS simulation is used daily to train all of the functionality of the International Space Station (ISS), including Space Station Remote Manipulator System (SSRMS) operations, Visiting Vehicle docking, capture and berthing, and payload relocations. The SPDM is a 2 armed robot that can be used on the end of the SSRMS with its arms grasping tools to execute tasks that would otherwise require Astronauts performing a spacewalk. The METECS Team performed software development, integration, and testing in support of this highly anticipated training capability. Congrats to the METECS Team and all of the other NASA JSC teams involved in reaching this major TS training milestone!

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Metecs supports operations on ISS with the Astrobee robot.

Today the METECS team supported operations on the International Space Station with the free-flying Astrobee robot to perform the initial checkout of the REALM-2 RFID payload.  REALM is the RFID system being used on ISS to help track and locate various inventory and the REALM-2 component provides a payload on the Astrobee robot to provide a portable RFID capability.  This capability will allow Astrobee to seek out missing items, perform inventories, and provide additional RFID sensing capabilities in the ISS.  METECS provides all of the software for the REALM project as well as the hardware/software integration. Congratulations to METECS team members that contributed to the REALM-2 payload and a successful first flight!

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Installation of the new NanoRacks research airlock

The new NanoRacks Airlock, which expands external ISS research capabilities and supports satellite deployment, was installed on ISS over the weekend!  METECS developed the contact and mechanism models, as well as performed the simulation and graphics integration required to train ISS flight controllers on installing the NanoRacks Airlock on ISS using the Space Station Remote Manipulator System (SSRMS).  METECS is proud to contribute to this new ISS airlock and the exciting science it will support!

https://blogs.nasa.gov/spacestation/2020/12/21/new-science-airlock-expands-stations-research-capacity/?fbclid=IwAR1DqzfT4__eVqmZ8lUlQkWu65DJtDsges2X3evShGSY_AxvtEI3Q6HoS2c

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METECS Awarded Five-Year SASS Contract with NASA.

NASA has awarded METECS a contract to provide Simulation and Advanced Software Services (SASS) to the Engineering Directorate at Johnson Space Center in Houston. The SASS contract has a potential value of $100M over a base period of five years. Work under the contract will include support for the International Space Station, Orion Multi-Purpose Crew Vehicle, Commercial Crew, Gateway and Artemis programs.  

“We are looking forward to working with our team members Harmony Lane Studios, Spoonbill, VEDO Systems, and Tietronix Software to support NASA’s human space program over the next five years with the SASS contract,” said John MacLean, founder and president of METECS. “The advanced software and simulations we provide will be essential to NASA’s missions in low-earth orbit, return to the moon and deep-space exploration.”

This effort will include spacecraft systems engineering; developing and analyzing Trick-based simulations of space robotics, human biomechanics, Guidance Navigation and Control, vehicle subsystems, docking and berthing systems, and human-in-the-loop training systems; developing and deploying both ground and space-based custom software for avionics integration and test, Core Flight Software, embedded systems, advanced robotics, next generation human-computer interfaces, autonomous logistics, machine learning, augmented reality and virtual environments.

METECS employees apply engineering and advanced technologies every day to provide creative solutions to NASA and the agriculture, construction, and energy industries.

https://www.nasa.gov/press-release/nasa-awards-contract-in-support-of-simulation-model-development

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2020 Open Source Awards Winners!

Every year METECS allows our employees to vote for which open source projects they would like the company to financially contribute to.

METECS is proud to recognize and contribute financially to these great open source projects. The results for the 2020 METECS Open Source Awards are:

1st place: Wikipedia (through Wikimedia foundation
2nd place: Mozilla Foundation
3rd place: Git (through SFC)

Thanks to the winners along with all the other valuable open-source applications available.

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METECS supports next-generation ARGOS (Active Response Gravity Offload System)

Next-Generation Active Response Gravity Offload System (ARGOS) to hold Conceptual Design Review August 18th and 19th. METECS Software Engineers will present custom software design concepts to safely simulate lunar gravity for Astronauts in pressurized planetary space suits to perform complex Moon training and testing. METECS Systems Engineer will support the Conceptual Design Review to review engineering designs and integrate software, mechanical, electrical, and safety teams. The ARGOS eXploration EVA Simulator, known as ARGOS AXES, will simulate Moon gravity, terrain, and lighting conditions for up to three Astronauts training for the 2024 Artemis mission to the Moon.

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Launch of a new era in spaceflight! 05-30-20

The countdown begins! Our team is incredibly excited to have been a part in helping the commercial crew program get to this point. May 30ths scheduled launch of NASA’s SpaceX Demo-2 mission at the agency’s Kennedy Space Center in Florida, American astronauts will once again launch an American spacecraft from American soil to the International Space Station. 

Our hearts, prayers and excitement go out to everyone involved in today’s Launch! #LaunchAmerica
https://www.nasa.gov/content/live-launch-america-nasas-spacex-demo-2-mission-to-the-international-space-station

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REALM Team Directs Crew to Missing Cargo Transfer Bag on ISS.

Recent Radio-Frequency Identification (RFID)-Enabled Autonomous Logistics Management (REALM) advances in beta versions of a novel deep learning tool, “Tagnet”, and a random forest classification tool, “Fangorn”, led the crew and ISS Inventory Stowage Officers (ISOs) to a missing Cargo Transfer Bag (CTB) in Node 4. Tagnet was conceived by EV8 intern Joel Simonoff during a summer tour in 2019, and continued in 2020. Although further planned testing is required, this early success was an exciting step in the application of machine learning applied to RFID. The CTB was reported lost approximately a year ago, but was not required by the crew until April 20th, 2020. Initial human inspection of raw data indicated that the missing CTB was likely in Node 1 or PMA 1, but localizing to the rack level had proven exceedingly difficult using human analysis and other deterministic and machine learning tools to date. To further complicate localization of this particular CTB, the two readers in Node 1 had not been properly reading tags due to a network anomaly that is being worked. Tagnet and Fangorn were able to localize the CTB to the Node 4 location using previous training on several TB of archived and new data obtained through only US LAB RFID readers. Data mining and derivation of machine inferences from raw RFID data is a critical technology focus of the REALM project, as RFID technology has not previously been applied to localizing items to the level of accuracy required by NASA. Moreover, the complex scattering environment faced by NASA spacecraft and habitats presents additional RFID localization challenges. – Patrick Fink, EV8 REALM Deep Learning Directs Crew to Missing CTB on ISS

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