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Marina Moreira

Publications and source records attributed to Marina Moreira.

8 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Integrated System for Autonomous and Adaptive Caretaking (ISAAC) Simulated Cargo Logistics Demo Video

This video shows a simulation of autonomous cargo logistics using ISAAC (Integrated System for Autonomous and Adaptive Caretaking). The video shows autonomous planning and execution of a cargo scenario in which the R2 robot moves a cargo bag from a stowed location to a transfer location in the US Lab on the International Space Station. The Astrobee robot then moves the bag from the transfer location to a new temporary stowage location in the Japanese Experiment Module (JEM).

ISAAC↗
NASA NTRSDate not supplied

Astrobee On-Orbit Commissioning Manuscript and Presentation

The Astrobee free flying robots operate autonomously inside the International Space Station (ISS) with oversight from a ground operator or ISS crew. They replace the Synchronized Position Hold Engage and Reorient Experimental Satellites (SPHERES) as research platforms for zero-g free-flying robotics. Astrobee can also serve as a mobile camera/sensor platform for flight and payload controllers to improve ISS operations. Development began in late 2014, and flight hardware deployed to the ISS on several launches starting from November 2018 to October 2019. Shortly after the first two robots arrived in April 2019, we began a series of commissioning activities to validate the Astrobee robots. This paper reviews the Astrobee system and describes the on-orbit commissioning activities and results.

ISS↗
NASA NTRSDate not supplied

ISAAC: An Integrated System for Autonomous and Adaptive Caretaking

The Integrated System for Autonomous and Adaptive Caretaking (ISAAC) project is developing technology for autonomous caretaking of spacecraft, primarily during uncrewed mission phases. ISAAC aims to integrate autonomous intra-vehicular robots (IVR) with spacecraft infrastructure (power, life support, etc.) and ground control. It focuses on capabilities required for NASA’s Gateway cis-lunar outpost that also apply to human missions to Mars and beyond. Its development strategy is to test using existing IVR on the ISS (the Astrobee free-flyer and Robonaut dextrous manipulator) as an analog for future IVR on Gateway.

Trey Smith↗
NASA NTRSDate not supplied

Mapping the ISS with the Autonomous Free-Flying Astrobee Robots

Space intra-vehicular robots (IVR) can provide coverage survey and targeted close-up inspection imagery capabilities that improve ground operator situation awareness. We report on a series of activities using the autonomous Astrobee robotic free-flyers that mapped the interior of three ISS modules, generating a panoramic tour of the ISS interior without astronaut manual photography. For the ISS, these capabilities can complement or replace time-consuming crew inspection tasks, providing panoramic data products that are easier to navigate than the baseline crew safety videos. For future exploration vehicles with extended uncrewed mission phases, robotic inspection will play a more critical role of providing the primary “eyes in the sky” for vehicle operators.

robotics↗
NASA NTRSDate not supplied

Unsupervised Change Detection for Space Habitats Using 3D Point Clouds

This work presents an algorithm for scene change detection from point clouds to enable autonomous robotic caretaking in future space habitats. Autonomous robotic systems will help maintain future deep-space habitats, such as the Gateway space station, which will be uncrewed for extended periods. Existing scene analysis software used on the International Space Station (ISS) relies on manually-labeled images for detecting changes. In contrast, the algorithm presented in this work uses raw, unlabeled point clouds as inputs. The algorithm first applies modified Expectation-Maximization Gaussian Mixture Model (GMM) clustering to two input point clouds. It then performs change detection by comparing the GMMs using the Earth Mover’s Distance. The algorithm is validated quantitatively and qualitatively using a test dataset collected by an Astrobee robot in the NASA Ames Granite Lab comprising single frame depth images taken directly by Astrobee and full-scene reconstructed maps built with RGB-D and pose data from Astrobee. The runtimes of the approach are also analyzed in depth. The source code is publicly released to promote further development.

robotics↗