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At least 181 records · Page 10

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NASA NTRS2006

Retrieving Storm Electric Fields from Aircrfaft Field Mill Data: Part II: Applications

The Lagrange multiplier theory developed in Part I of this study is applied to complete a relative calibration of a Citation aircraft that is instrumented with six field mill sensors. When side constraints related to average fields are used, the Lagrange multiplier method performs well in computer simulations. For mill measurement errors of 1 V m(sup -1) and a 5 V m(sup -1) error in the mean fair-weather field function, the 3D storm electric field is retrieved to within an error of about 12%. A side constraint that involves estimating the detailed structure of the fair-weather field was also tested using computer simulations. For mill measurement errors of 1 V m(sup -l), the method retrieves the 3D storm field to within an error of about 8% if the fair-weather field estimate is typically within 1 V m(sup -1) of the true fair-weather field. Using this type of side constraint and data from fair-weather field maneuvers taken on 29 June 2001, the Citation aircraft was calibrated. Absolute calibration was completed using the pitch down method developed in Part I, and conventional analyses. The resulting calibration matrices were then used to retrieve storm electric fields during a Citation flight on 2 June 2001. The storm field results are encouraging and agree favorably in many respects with results derived from earlier (iterative) techniques of calibration.

Koshak, William↗

NASA NTRS1990

Space shuttle main engine computed tomography applications

For the past two years the potential applications of computed tomography to the fabrication and overhaul of the Space Shuttle Main Engine were evaluated. Application tests were performed at various government and manufacturer facilities with equipment produced by four different manufacturers. The hardware scanned varied in size and complexity from a small temperature sensor and turbine blades to an assembled heat exchanger and main injector oxidizer inlet manifold. The evaluation of capabilities included the ability to identify and locate internal flaws, measure the depth of surface cracks, measure wall thickness, compare manifold design contours to actual part contours, perform automatic dimensional inspections, generate 3D computer models of actual parts, and image the relationship of the details in a complex assembly. The capabilities evaluated, with the exception of measuring the depth of surface flaws, demonstrated the existing and potential ability to perform many beneficial Space Shuttle Main Engine applications.

Sporny, Richard F.↗

NASA NTRS1992

Failure mechanisms of 3-D woven SiC/SiC composites under tensile and flexural loading at room and elevated temperatures

Nicalon silicon carbide 3D yarn with silicon carbide matrix composites made through a chemical vapor infiltration (CVI) process were investigated under tensile and flexural loading at 23, 1200 and 1550 C in air. The effectiveness of a chemical vapor deposition (CVD) SiC surface coating was also evaluated in severe oxidizing environment. Acoustic emission sensors and in situ optical microscopy were used at room temperature to monitor the failure mechanisms. It is shown that the level of tensile stress at which nonlinear behavior begins is not drastically reduced at 1200 and 1550 C when composites were protected by a SiC surface coating. Extensive fiber pull-out was observed only in the 1550 C specimen. Similar behaviors were also found in flexural specimens.

Chulya, Abhisak↗

NASA NTRS2018

Remote Sensing of Antarctic Sea Ice with Coordinated Aircraft and Satellite Data Acquisitions

Remote sensing of Antarctic sea ice is required to characterize properties of the vast sea ice cover to understand its long-term increase in contrast to the decrease of Arctic sea ice. For this objective, the OIB/TanDEM-X Coordinated Science Campaign (OTASC) was successfully conducted in 2017 to obtain contemporaneous and collocated remote sensing data from NASA's Operation IceBridge (OIB) and the German Aerospace Center (DLR) TanDEM-X Synthetic Aperture Radar (SAR) system at X-band together with Sentinel-1 and RADARSAT-2 SARs at C-band in conjunction with WorldView satellite spectral sensors, surface measurements, and field observations. The Weddell Sea and the Ross Sea were two primary regions while SAR data were also collected over six other regions in the Southern Ocean. Satellite SAR data included both polarimetric and interferometric capabilities to infer snow and sea ice information in three dimensions (3D), while OIB/P-3 aircraft data include snow radar together with altimeter data for snow and sea ice observations in 3D over the Weddell Sea. Across the Ross Sea, IcePOD and AntNZ/York-University flights were carried out together with satellite SAR data acquisitions.

OIB↗

NASA NTRS2010

Predicting Long-Range Traversability from Short-Range Stereo-Derived Geometry

Based only on its appearance in imagery, this program uses close-range 3D terrain analysis to produce training data sufficient to estimate the traversability of terrain beyond 3D sensing range. This approach is called learning from stereo (LFS). In effect, the software transfers knowledge from middle distances, where 3D geometry provides training cues, into the far field where only appearance is available. This is a viable approach because the same obstacle classes, and sometimes the same obstacles, are typically present in the mid-field and the farfield. Learning thus extends the effective look-ahead distance of the sensors.

Turmon, Michael↗

NASA NTRS2017

Dual Ion Spectrometers and Their Calibration for the Fast Plasma Investigation on NASA's Magnetospheric Multiscale Mission

The scientific target of NASA's Magnetospheric Multiscale (MMS) mission is to study the fundamentally important phenomenon of magnetic reconnection. Theoretical models of this process predict a small size, on the order of hundred kilometers, for the ion diffusion region where ions are demagnetized at the dayside magnetopause. This region may typically sweep over the spacecraft at relatively high speeds of 50 km/s, requiring the fast plasma investigation (FPI) instrument suite to have an extremely high time resolution for measurements of the 3D particle distribution functions. As part of the FPI on MMS, the 16 dual ion spectrometers (DIS) will provide fast (150 ms) 3D ion velocity distributions, from 10 to 30,000 eV/q, by combining the measurements from four dual spectrometers on each of four MMS spacecraft. For any multispacecraft mission, the response uniformity among the spectrometer set assumes an enhanced importance. Due to these demanding instrument requirements and the effort of calibrating more than 32 sensors (16 × 2) within a tight schedule, a highly systematic and precise calibration was required for measurement repeatability. To illustrate how this challenge was met, a brief overview of the FPI DIS was presented with a detailed discussion of the calibration method of approach and implementation. Finally, a discussion of DIS performance results, their unit-to-unit variation, and the lessons learned from this calibration effort are presented.

Coffey, V. N.↗

NASA NTRS2017

A UAV-Based Fog Collector Design for Fine-Scale Aerobiological Sampling

Airborne microbes are found throughout the troposphere and into the stratosphere. Knowing how the activity of airborne microorganisms can alter water, carbon, and other geochemical cycles is vital to a full understanding of local and global ecosystems. Just as on the land or in the ocean, atmospheric regions vary in habitability; the underlying geochemical, climatic, and ecological dynamics must be characterized at different scales to be effectively modeled. Most aerobiological studies have focused on a high level: 'How high are airborne microbes found?' and 'How far can they travel?' Most fog and cloud water studies collect from stationary ground stations (point) or along flight transects (1D). To complement and provide context for this data, we have designed a UAV-based modified fog and cloud water collector to retrieve 4D-resolved samples for biological and chemical analysis.Our design uses a passive impacting collector hanging from a rigid rod suspended between two multi-rotor UAVs. The suspension design reduces the effect of turbulence and potential for contamination from the UAV downwash. The UAVs are currently modeled in a leader-follower configuration, taking advantage of recent advances in modular UAVs, UAV swarming, and flight planning.The collector itself is a hydrophobic mesh. Materials including Tyvek, PTFE, nylon, and polypropylene monofilament fabricated via laser cutting, CNC knife, or 3D printing were characterized for droplet collection efficiency using a benchtop atomizer and particle counter. Because the meshes can be easily and inexpensively fabricated, a set can be pre-sterilized and brought to the field for 'hot swapping' to decrease cross-contamination between flight sessions or use as negative controls.An onboard sensor and logging system records the time and location of each sample; when combined with flight tracking data, the samples can be resolved into a 4D volumetric map of the fog bank. Collected samples can be returned to the lab for a variety of analyses. Based on a review of existing flight studies, we have identified ion chromatography, metagenomic sequencing, cell staining and quantification, and ATP quantification as high-priority assays for implementation. Support for specific toxicology assays, such as methylmercury quantification, is also planned.

Design↗

NASA NTRS2016

A UAV-Based Fog Collector Design for Fine-Scale Aerobiological Sampling

Airborne microbes are found throughout the troposphere and into the stratosphere. Knowing how the activity of airborne microorganisms can alter water, carbon, and other geochemical cycles is vital to a full understanding of local and global ecosystems. Just as on the land or in the ocean, atmospheric regions vary in habitability; the underlying geochemical, climatic, and ecological dynamics must be characterized at different scales to be effectively modeled. Most aerobiological studies have focused on a high level: 'How high are airborne microbes found?' and 'How far can they travel?' Most fog and cloud water studies collect from stationary ground stations (point) or along flight transects (1D). To complement and provide context for this data, we have designed a UAV-based modified fog and cloud water collector to retrieve 4D-resolved samples for biological and chemical analysis.Our design uses a passive impacting collector hanging from a rigid rod suspended between two multi-rotor UAVs (Unmanned Aerial Vehicles). The suspension design reduces the effect of turbulence and potential for contamination from the UAV downwash. The UAVs are currently modeled in a leader-follower configuration, taking advantage of recent advances in modular UAVs, UAV swarming, and flight planning.The collector itself is a hydrophobic mesh. Materials including Tyvek, PTFE, nylon, and polypropylene monofilament fabricated via laser cutting, CNC knife, or 3D printing were characterized for droplet collection efficiency using a benchtop atomizer and particle counter. Because the meshes can be easily and inexpensively fabricated, a set can be pre-sterilized and brought to the field for 'hot swapping' to decrease cross-contamination between flight sessions or use as negative controls.An onboard sensor and logging system records the time and location of each sample; when combined with flight tracking data, the samples can be resolved into a 4D volumetric map of the fog bank. Collected samples can be returned to the lab for a variety of analyses. Based on a review of existing flight studies, we have identified ion chromatography, metagenomic sequencing, cell staining and quantification, and ATP quantification as high-priority assays for implementation. Support for specific toxicology assays, such as methyl-mercury quantification, is also planned.

Design↗

NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Deep Reinforcement Learning

To support sustainable infrastructure on the Moon, NASA needs to leverage lunar resources for in-situ processing and construction. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for these tasks. To reliably perform these operations on the lunar surface, RASSOR's sensors and control systems need to be robust and maximize information extracted from a reduced sensor payload. Herein, we present our findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments in which we applied reinforcement learning algorithms to learn autonomous trenching controllers and produced state estimation architectures. We developed two simulations: a 2D excavation simulation used to facilitate parameter selection, and a 3D simulation developed using a game physics engine to simulate simplified soil interactions and incorporate robotic agents parameterized by dynamic models. Within these simulations, we learned autonomous excavation routines that exceed excavation efficiency measures as compared against RASSOR's existing control and teleoperation-based methods.

RASSOR↗

NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Deep Reinforcement Learning

RASSOR↗

NASA NTRSDate not supplied

Evaluation of Markerless Motion Capture for Monitoring Sensorimotor Performance

BACKGROUND Astronauts returning from long-duration exposure to microgravity frequently exhibit alterations in sensorimotor function leading to postural imbalance, impaired locomotion, and operational challenges to manual control. Mission duration and individual responses often influence both the severity of performance decrements and the variability in adaptation timelines. Postflight disruptions during functional tasks are often detected through body-worn inertial measurement unit (IMU) devices. While IMU sensors are relatively compact, the long-term wear may lead to discomfort, displacement of the sensors on the body, and restrictions in movement or crew behavior. Although IMU data offers valuable insights from a research standpoint, interpreting changes in pre- and post-flight measures can be difficult for crew support personnel beyond the research domain, which can hinder the application for medical assessments and rehabilitation. Finally, the availability of inertial sensors in-flight is limited. There is a need for unobtrusive monitoring tools to improve our ability to monitor adaptation following gravitational transitions in various postflight evaluations and rehabilitation settings. Markerless motion capture (MMC) is an evolving unobtrusive technology that builds upon decades of research with marker-based motion capture systems to provide 3D human pose estimation from multiple synchronized 2D camera views using deep learning algorithms. Markerless technology can revolutionize how data is captured pre- and post-flight and potentially in-flight during intravehicular activity by enabling pose estimation of multiple crew members from onboard camera hardware. METHODS The following presents the initial evaluation of a state-of-the-art commercial-off-the-shelf MMC system, Theia Markerless, compared to IMU devices during various ground-based functional tasks and environmental conditions. The featured functional tasks include assessments from Human Research Program (HRP) funded studies such as Sensorimotor Standard Measures and Sensorimotor Assessments. Synchronous data collected using both motion capture and IMUs are analyzed for six male and female subjects of varying anthropometry. The analysis includes limited assessments of clothing, capture volume configurations, and the tool's sensitivity to detecting performance changes after a spaceflight analog centrifuge exposure. The development of visualization tools to enhance the application of the pose estimation output is also presented. RESULTS Initial results demonstrate comparable root mean square error (RMSE) to existing literature evaluating markerless and marker-based motion capture systems. Considering the relative functional range of motion of the cervical spine, normalized error values for the markerless system’s accuracy of the head was 0.032 in pitch, 0.025 in roll, and 0.018 in yaw plane of motion across a subset of functional tasks. The raw RMSE values were 3.49, 2.25, and 2.81 degrees respectively. For the torso, results suggest normalized errors of 0.469 in pitch, 0.191 in roll, and 0.307 in yaw planes of motion and raw RMSE values of 3.52, 1.53, and 3.07 degrees respectively. The data suggests the functional demands of a particular task influences the estimation accuracy of the MMC system where more dynamic motion and cases where subjects are not upright may introduce diminished tracking accuracy. DISCUSSION The following work lays the foundation for future implementations leveraging markerless motion capture to assess the time course of recovery and provide insight for rehabilitation protocols to enhance crew readiness for the resumption of daily activities. These tools offer effective methods for anonymizing sensitive crew data, facilitating numerous applications across research, medical, and rehabilitation groups. Collaborations with the Anthropometry and Biomechanics Facility will provide further comparisons of the Markerless system to a marker-based system. ACKNOWLEDGEMENT</ This work is supported by NASA’s Exploration Systems Development Mission Directorate Mars Campaign Office Crew Health Countermeasures.

Hannah M. Weiss↗

NASA NTRS2002

Science Target Assessment for Mars Rover Instrument Deployment

This paper introduces the system being developed at NASA Ames Research Center, intended for the Mars '09 Smart Lander, to robustly place sensors or tools against rocks in a single communications cycle. Science targets must be assessed prior to instrument placement in order to segment them from the background and determine where, if possible, to position the instrument. An initial result of this research effort is a novel Bayesian based method for segmenting rocks from the ground using 3D data.

Pedersen, Liam↗

NASA NTRS2017

Eclipse of the Floating Orbs: Controlling Robots on the International Space Station

I will describe the Control Station for a free-flying robot called Astrobee. Astrobee will serve as a mobile camera, sensor platform, and research testbed when it is launched to the International Space Station (ISS)in 2017. Astronauts on the ISS as well as ground-based users will control Astrobee using the Eclipse-based Astrobee Control Station. Designing theControl Station for use in space presented unique challenges, such as allowing the intuitive input of 3D information without a mouse or trackpad. Come to this talk to learn how Eclipse is used in an environment few humans have the chance to visit.

ground control↗

NASA NTRS1992

On pose determination using point features

Consideration is given to the vision subsystem of an Orbital Replacement Unit (ORU) that was placed onto its base at Goddard Space Flight Center by a PUMA 762 robot equipped with a wrist-mounted CCD camera and a wrist-mounted force sensor. It is found that a simple adaptive thresholding method works quite well for images taken under various lighting conditions. The pose computed using the quadrangle method is reasonable for real images. In the presence of image feature noise the accuracy of the computed pose can be considerably reduced. This problem can be solved by using a 3D marker and an alternative pose computation algorithm.

Hwang, Vincent↗

NASA NTRS2013

Robotics On-Board Trainer (ROBoT)

ROBoT is an on-orbit version of the ground-based Dynamics Skills Trainer (DST) that astronauts use for training on a frequent basis. This software consists of two primary software groups. The first series of components is responsible for displaying the graphical scenes. The remaining components are responsible for simulating the Mobile Servicing System (MSS), the Japanese Experiment Module Remote Manipulator System (JEMRMS), and the H-II Transfer Vehicle (HTV) Free Flyer Robotics Operations. The MSS simulation software includes: Robotic Workstation (RWS) simulation, a simulation of the Space Station Remote Manipulator System (SSRMS), a simulation of the ISS Command and Control System (CCS), and a portion of the Portable Computer System (PCS) software necessary for MSS operations. These components all run under the CentOS4.5 Linux operating system. The JEMRMS simulation software includes real-time, HIL, dynamics, manipulator multi-body dynamics, and a moving object contact model with Tricks discrete time scheduling. The JEMRMS DST will be used as a functional proficiency and skills trainer for flight crews. The HTV Free Flyer Robotics Operations simulation software adds a functional simulation of HTV vehicle controllers, sensors, and data to the MSS simulation software. These components are intended to support HTV ISS visiting vehicle analysis and training. The scene generation software will use DOUG (Dynamic On-orbit Ubiquitous Graphics) to render the graphical scenes. DOUG runs on a laptop running the CentOS4.5 Linux operating system. DOUG is an Open GL-based 3D computer graphics rendering package. It uses pre-built three-dimensional models of on-orbit ISS and space shuttle systems elements, and provides realtime views of various station and shuttle configurations.

Johnson, Genevieve↗

NASA NTRSDate not supplied

Towards Physics Guided Optical Flow for Tracking Atmospheric Motion

Observations of atmospheric 3D winds are critical for improving short-range and long-range forecasting. Such advancement in forecasting directly applies to research in a number of areas including convective processes, wildfire plumes and tornado prediction. Atmospheric Motion Vectors (AMVs) provide a passively sensed approach to quantifying horizontal motion and cloud heights, which are typically sourced from geostationary sensors due to the availability of high frequency observations. Recent work has shown that estimating AMVs by tracking individual pixels with dense optical flow is a promising new direction. In this work, we compare state-of-the-art convolutional neural networks for optical flow in a physics-guided deep learning framework for predicting AMVs. The approach is semi-supervised and uses physically informed wind vectors from high-resolution numerical simulations for supervised learning followed by fine-tuning though warping and reconstruction of full-disk geostationary images (GOES-16). In the vertical direction, we use labels from the CALIPSO low-earth orbit satellite to predict cloud height from 16-band geostationary images with a neural network. We present results for both tasks on held-out time periods and secondary datasets.

Geostationary↗

NASA NTRS1989

ROTEX-TRIIFEX: Proposal for a joint FRG-USA telerobotic flight experiment

The concepts and main elements of a RObot Technology EXperiment (ROTEX) proposed to fly with the next German spacelab mission, D2, are presented. It provides a 1 meter size, six axis robot inside a spacelab rack, equipped with a multisensory gripper (force-torque sensors, an array of range finders, and mini stereo cameras). The robot will perform assembly and servicing tasks in a generic way, and will grasp a floating object. The man machine and supervisory control concepts for teleoperation from the spacelab and from ground are discussed. The predictive estimation schemes for an extensive use of time-delay compensating 3D computer graphics are explained.

Hirzinger, G.↗

NASA NTRS2005

Self-Examination

The operation of the new U.S./Canadian Orbiter Boom Sensor System (OBSS) by the STS-114 Discovery's crew "will be the most complicated space robotics job of the shuttle program," say Paul Hill, lead flight director. The OBSS is a laser-and-imaging-sensor- equipped 50-ft. extension to the existing 50-ft. arm, increasing the shuttle's reach to 100 ft. The return-to-flight mission will debut the autonomous robotic self-inspection capability to detect and possibly aid the repair of the type of damage that doomed Columbia and her crew, were it to occur again. With 3D imaging and laser contour-mapping capability, the OBSS will enable the diagnosis of cracks in reinforced carbon-carbon (RCC) wing and nose areas and thermal protection system (TPS) tiles beyond the view of the standard manipulator arm. Given the major changes to the shuttle external tank, no damage is expected. But the OBSS is a direct response to the Columbia Accident Investigation Board's recommendations. The new boom and a significant amount of its supporting software was developed by MacDonald Dettwiler heads. Space and Advanced Robotics Ltd. (MD Robotics) in Brampton, Ontario, a key contractor in the shuttle program for 25 years. The Canadian Space Agency is also heavily involved in supporting shuttle and International Space Station (ISS) robotics.

Covault, Craig↗