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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

NASA's Near Earth Asteroid Scout Mission

NASA is developing solar sail propulsion for a near-term Near Earth Asteroid (NEA) reconnaissance mission and laying the groundwork for their future use in deep space science and exploration missions. The NEA Scout mission, funded by NASA's Advanced Exploration Systems Program and managed by NASA MSFC, will use the sail as primary propulsion allowing it to survey and image one or more NEA's of interest for possible future human exploration. NEA Scout uses a 6U cubesat (to be provided by NASA's Jet Propulsion Laboratory), an 86 m2 solar sail and will weigh less than 14 kilograms. The solar sail for NEA Scout will be based on the technology developed and flown by the NASA NanoSail-D and The Planetary Society's Lightsail-A. Four ~7 m stainless steel booms wrapped on two spools (two overlapping booms per spool) will be motor deployed and pull the sail from its stowed volume. The sail material is an aluminized polyimide approximately 3 microns thick. NEA Scout will launch on the Space Launch System (SLS) first mission in 2018 and deploy from the SLS after the Orion spacecraft is separated from the SLS upper stage. The NEA Scout spacecraft will stabilize its orientation after ejection using an onboard cold-gas thruster system. The same system provides the vehicle Delta-V sufficient for a lunar flyby. After its first encounter with the moon, the 86 m2 sail will deploy, and the sail characterization phase will begin. A mechanical Active Mass Translation (AMT) system, combined with the remaining ACS propellant, will be used for sail momentum management. Once the system is checked out, the spacecraft will perform a series of lunar flybys until it achieves optimum departure trajectory to the target asteroid. The spacecraft will then begin its two year-long cruise. About one month before the asteroid flyby, NEA Scout will pause to search for the target and start its approach phase using a combination of radio tracking and optical navigation. The solar sail will provide continuous low thrust to enable a relatively slow flyby of the target asteroid under lighting conditions favorable to geological imaging. Once complete, NASA will have demonstrated the capability to fly low-cost, high Delta-V cubesats to perform interplanetary missions.

Johnson, Les↗
NASA NTRS1993

Expansion-based passive ranging

A new technique of passive ranging which is based on utilizing the image-plane expansion experienced by every object as its distance from the sensor decreases is described. This technique belongs in the feature/object-based family. The motion and shape of a small window, assumed to be fully contained inside the boundaries of some object, is approximated by an affine transformation. The parameters of the transformation matrix are derived by initially comparing successive images, and progressively increasing the image time separation so as to achieve much larger triangulation baseline than currently possible. Depth is directly derived from the expansion part of the transformation. To a first approximation, image-plane expansion is independent of image-plane location with respect to the focus of expansion (FOE) and of platform maneuvers. Thus, an expansion-based method has the potential of providing a reliable range in the difficult image area around the FOE. In areas far from the FOE the shift parameters of the affine transformation can provide more accurate depth information than the expansion alone, and can thus be used similarly to the way they were used in conjunction with the Inertial Navigation Unit (INU) and Kalman filtering. However, the performance of a shift-based algorithm, when the shifts are derived from the affine transformation, would be much improved compared to current algorithms because the shifts - as well as the other parameters - can be obtained between widely separated images. Thus, the main advantage of this new approach is that, allowing the tracked window to expand and rotate, in addition to moving laterally, enables one to correlate images over a very long time span which, in turn, translates into a large spatial baseline - resulting in a proportionately higher depth accuracy.

Barniv, Yair↗
DOE OSTI2022

Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry

Estimation of riverbed profiles, also known as bathymetry, plays a vital role in many applications, such as safe and efficient inland navigation, prediction of bank erosion, land subsidence, and flood risk management. The high cost and complex logistics of direct bathymetry surveys, i.e, depth imaging, have encouraged the use of indirect measurements such as surface flow velocities. However, estimating high-resolution bathymetry from indirect measurements is an inverse problem that can be computationally challenging. Here, we propose a reduced-order model (ROM) based approach that utilizes a variational autoencoder (VAE), a type of deep neural network with a narrow layer in the middle, to compress bathymetry and flow velocity information and accelerate bathymetry inverse problems from flow velocity measurements. In our application, the shallow-water equations (SWE) with appropriate boundary conditions (BCs), e.g., the discharge and/or the free surface elevation, constitute the forward problem, to predict flow velocity. Then, ROMs of the SWEs are constructed on a nonlinear manifold of low dimensionality through a variational encoder and the bathymetry inversion problem is derived on the low-dimensional latent space in a Hierarchical Bayesian setting. Further, the reformulation allows variational inference with a small number (e.g., $\mathscr{O}$ (100) of ROM runs and efficient uncertainty quantification. We have tested our inversion approach on a one-mile reach of the Savannah River, GA, USA. Once the neural network is trained (offline stage), the proposed technique can perform the inversion operation orders of magnitude faster than traditional inversion methods that are commonly based on linear projections, such as principal component analysis (PCA), or the principal component geostatistical approach (PCGA). Furthermore, tests show that the algorithm can estimate the bathymetry with good accuracy even with sparse flow velocity measurements.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Optical Characterization of CLPS MiniatureLaser Retroreflector Arrays

Laser retroreflector arrays (LRAs) consisting of corner cube retroreflectors (CCRs) can act as fiducial markers for decades of laser ranging on the Moon and other planetary bodies. Upcoming lunar lander missions from government space agencies and commercial partners offer a unique opportunity to support lunar science and exploration through the deployment of small LRAs on lander decks. Placement of an LRA on the deck of a lander or rover enables tracking with an orbital laser altimeter to aprecision on the order of centimeters. When mounted alongside a suite of scientific instruments the LRA enables precise geolocation of those instruments in the lunar geodetic frame. Finally, optical markers such as LRAs can support precision autonomous navigation and landing regardless of lighting conditions, an especially valuable capability for lunar polar exploration where long shadows complicate terrain relative nagivation using imaging methods.

Daniel R. Cremons↗
NASA NTRS1993

Expansion-based passive ranging

This paper describes a new technique of passive ranging which is based on utilizing the image-plane expansion experienced by every object as its distance from the sensor decreases. This technique belongs in the feature/object-based family. The motion and shape of a small window, assumed to be fully contained inside the boundaries of some object, is approximated by an affine transformation. The parameters of the transformation matrix are derived by initially comparing successive images, and progressively increasing the image time separation so as to achieve much larger triangulation baseline than currently possible. Depth is directly derived from the expansion part of the transformation. To a first approximation, image-plane expansion is independent of image-plane location with respect to the focus of expansion (FOE) and of platform maneuvers. Thus, an expansion-based method has the potential of providing a reliable range in the difficult image area around the FOE. In areas far from the FOE the shift parameters of the affine transformation can provide more accurate depth information than the expansion alone, and can thus be used similarly to the way they have been used in conjunction with the Inertial Navigation Unit (INU) and Kalman filtering. However, the performance of a shift-based algorithm, when the shifts are derived from the affine transformation, would be much improved compared to current algorithms because the shifts--as well as the other parameters--can be obtained between widely separated images. Thus, the main advantage of this new approach is that, allowing the tracked window to expand and rotate, in addition to moving laterally, enables one to correlate images over a very long time span which, in turn, translates into a large spatial baseline resulting in a proportionately higher depth accuracy.

Barniv, Yair↗
NASA NTRS2019

Near Earth Asteroid Scout: Exploring Asteroid 1991VG Using A Smallsat

After its deployment from NASA’s Space Launch System (SLS) in 2020, the Near Earth Asteroid (NEA) Scout mission will image an asteroid on a close flyby using an 86m2 solar sail as its primary propulsion. NEA Scout, with a 6U CubeSat form factor, is one of several secondary CubeSat payloads to be deployed from the SLS on its maiden flight. The NEA Scout will be ejected from the SLS on a trajectory toward the moon and will use its onboard cold gas propulsion system to attain an elliptical lunar orbit. Once the spacecraft is in orbit, the solar sail will deploy and spacecraft checkout will begin. The NEA Scout will remain in the lunar vicinity until the low-thrust trajectory to the destination asteroid, 1991VG, or another NEA of interest, can be attained. The spacecraft will then begin its 2.0 – 2.5 year journey to the asteroid. About one month before the asteroid flyby, NEA Scout will search for the target and start its Approach Phase, using a combination of radio tracking and optical navigation. The solar sail will provide continuous low thrust to enable a relatively slow flyby (10-20 m/s) of the target asteroid under lighting conditions favorable to geological imaging (<50 degree phase angle). Once the flyby is complete, and if the system is still fully functioning, an extended mission will be considered – the reconnaissance of another asteroid or a re-flyby of the first asteroid several months later are both options. NEA Scout is funded by the NASA Human Exploration and Operations Mission Directorate.

In-Space Propulsion↗
NASA NTRS1996

Detection of obstacles on runway using Ego-Motion compensation and tracking of significant features

This report describes a method for obstacle detection on a runway for autonomous navigation and landing of an aircraft. Detection is done in the presence of extraneous features such as tiremarks. Suitable features are extracted from the image and warping using approximately known camera and plane parameters is performed in order to compensate ego-motion as far as possible. Residual disparity after warping is estimated using an optical flow algorithm. Features are tracked from frame to frame so as to obtain more reliable estimates of their motion. Corrections are made to motion parameters with the residual disparities using a robust method, and features having large residual disparities are signaled as obstacles. Sensitivity analysis of the procedure is also studied. Nelson's optical flow constraint is proposed to separate moving obstacles from stationary ones. A Bayesian framework is used at every stage so that the confidence in the estimates can be determined.

Kasturi, Rangachar↗
DOE OSTI2015

SU-E-J-111: Finite Element-Based Deformable Image Registration of Pleural Cavity for Photodynamic Therapy

Purpose: The pleural volumes will deform during surgery portion of the pleural photodynamic therapy (PDT) of lung cancer when the pleural cavity is opened. This impact the delivered dose when using highly conformal treatment techniques. In this study, a finite element-based (FEM) deformable image registration is used to quantify the anatomical variation between the contours for the pleural cavities obtained in the operating room and those determined from pre-surgery computed tomography (CT) scans. Methods: An infrared camera-based navigation system (NDI) is used during PDT to track the anatomical changes and contour the lung and chest cavity. A series of CTs of the lungs, in the same patient, are also acquired before the surgery. The structure contour of lung and the CTs are processed and contoured in Matlab and MeshLab. Then, the contours are imported into COMSOL Multiphysics 5.0, where the FEM-based deformable image registration is obtained using the deformed mesh - moving mesh (ALE) model. The NDI acquired lung contour is considered as the reference contour, and the CT contour is used as the target one, which will be deformed. Results: The reconstructed three-dimensional contours from both NDI and CT can be converted to COMSOL so that a three-dimensional ALE model can be developed. The contours can be registered using COMSOL ALE moving mesh model, which takes into account the deformation along x, y and z-axes. The deformed contour has good matches to the reference contour after the dynamic matching process. The resulting 3D deformation map can be used to obtain the locations of other critical anatomic structures, e.g., heart, during surgery. Conclusion: Deformable image registration can fuse images acquired by different modalities. It provides insights into the development of phenomenon and variation in normal anatomical structures over time. The initial assessments of three-dimensional registration show good agreement.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1975

An operational all-weather Great Lakes ice information system

A description is given of the NASA developed all-weather ice information system for the Great Lakes winter navigation program. The system utilizes an X-band side looking airborne radar (SLAR) for determining type, location, and areal distribution of the ice cover in the Great Lakes and an airborne, S band, down looking short pulse radar for obtaining ice thickness. Digitized SLAR data are relayed in real time via the NOAA-GOES satellite in geosynchronous orbit. The SLAR images along with hand drawn interpretative ice charts for various Great Lakes winter shipping areas are broadcast to facsimile recorders aboard vessles is the area via the MARAD marine VHF-FM radio network. These data assist such vessels in navigating both through and around the ice.

Gedney, R. T.↗
DOE OSTI2016

SU-F-I-50: Finite Element-Based Deformable Image Registration of Lung and Heart

Purpose: Photodynamic therapy (PDT) is used after surgical resection to treat the microscopic disease for malignant pleural mesothelioma and to increase survival rates. Although accurate light delivery is imperative to PDT efficacy, the deformation of the pleural volume during the surgery impacts the delivered light dose. To facilitate treatment planning, we use a finite-element-based (FEM) deformable image registration to quantify the anatomical variation of lung and heart volumes between CT pre-(or post-) surgery and surface contours obtained during PDT using an infrared camera-based navigation system (NDI). Methods: NDI is used during PDT to obtain the information of the cumulative light fluence on every cavity surface point that is being treated. A wand, comprised of a modified endotrachial tube filled with Intralipid and an optical fiber inside the tube, is used to deliver the light during PDT. The position of the treatment is tracked using an attachment with nine reflective passive markers that are seen by the NDI system. Then, the position points are plotted as three-dimensional volume of the pleural cavity using Matlab and Meshlab. A series of computed tomography (CT) scans of the lungs and heart, in the same patient, are also acquired before and after the surgery. The NDI and CT contours are imported into COMSOL Multiphysics, where the FEM-based deformable image registration is obtained. The NDI and CT contours acquired during and post-PDT are considered as the reference, and the Pre-PDT CT contours are used as the target, which will be deformed. Results: Anatomical variation of the lung and heart volumes, taken at different times from different imaging devices, was determined by using our model. The resulting three-dimensional deformation map along x, y and z-axes was obtained. Conclusion: Our model fuses images acquired by different modalities and provides insights into the variation in anatomical structures over time.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2017

Near Earth Asteroid (NEA) Scout

NASA is developing solar sail propulsion for a near-term Near Earth Asteroid (NEA) reconnaissance mission that will lay the groundwork for the future use of solar sails. The NEA Scout mission will use the sail as primary propulsion allowing it to survey and image one NEA's of interest for future human exploration. NEA Scout will launch on the first mission of the Space Launch System (SLS) in 2018. After its first encounter with the Moon, NEA Scout will enter the sail characterization phase by the 86 square meter sail deployment. A mechanical Active Mass Translation (AMT) system, combined with the remaining ACS propellant, will be used for sail momentum management. The spacecraft will perform a series of lunar flybys to achieve optimum departure trajectory before beginning its two year-long cruise. About one month before the asteroid flyby, NEA Scout will start its approach phase using optical navigation on top of radio tracking. The solar sail will provide NEA Scout continuous low thrust to enable a relatively slow flyby of the target asteroid under lighting conditions favorable to geological imaging. Once complete, NASA will have demonstrated the capability to fly low-cost, high delta V CubeSats to perform interplanetary missions.

Johnson, Les↗
NASA NTRS2011

Lidar Systems for Precision Navigation and Safe Landing on Planetary Bodies

The ability of lidar technology to provide three-dimensional elevation maps of the terrain, high precision distance to the ground, and approach velocity can enable safe landing of robotic and manned vehicles with a high degree of precision. Currently, NASA is developing novel lidar sensors aimed at needs of future planetary landing missions. These lidar sensors are a 3-Dimensional Imaging Flash Lidar, a Doppler Lidar, and a Laser Altimeter. The Flash Lidar is capable of generating elevation maps of the terrain that indicate hazardous features such as rocks, craters, and steep slopes. The elevation maps collected during the approach phase of a landing vehicle, at about 1 km above the ground, can be used to determine the most suitable safe landing site. The Doppler Lidar provides highly accurate ground relative velocity and distance data allowing for precision navigation to the landing site. Our Doppler lidar utilizes three laser beams pointed to different directions to measure line of sight velocities and ranges to the ground from altitudes of over 2 km. Throughout the landing trajectory starting at altitudes of about 20 km, the Laser Altimeter can provide very accurate ground relative altitude measurements that are used to improve the vehicle position knowledge obtained from the vehicle navigation system. At altitudes from approximately 15 km to 10 km, either the Laser Altimeter or the Flash Lidar can be used to generate contour maps of the terrain, identifying known surface features such as craters, to perform Terrain relative Navigation thus further reducing the vehicle s relative position error. This paper describes the operational capabilities of each lidar sensor and provides a status of their development. Keywords: Laser Remote Sensing, Laser Radar, Doppler Lidar, Flash Lidar, 3-D Imaging, Laser Altimeter, Precession Landing, Hazard Detection

Amzajerdian, Farzin↗
NASA NTRS1979

Spectral feature classification and spatial pattern recognition

This paper introduces a spatial pattern recognition processing concept involving the use of spectral feature classification technology and coherent optical correlation. The concept defines a hybrid image processing system incorporating both digital and optical technology. The hybrid instrument provides simplified pseudopattern images as functions of pixel classification from information embedded within a real-scene image. These pseudoimages become simplified inputs to an optical correlator for use in a subsequent pattern identification decision useful in executing landmark pointing, tracking, or navigating functions. Real-time classification is proposed as a research tool for exploring ways to enhance input signal-to-noise ratio as an aid in improving optical correlation. The approach can be explored with developing technology, including a current NASA Langley Research Center technology plan that involves a series of related Shuttle-borne experiments. A first-planned experiment, Feature Identification and Location Experiment (FILE), is undergoing final ground testing, and is scheduled for flight on the NASA Shuttle (STS2/flight OSTA-1) in 1980. FILE will evaluate a technique for autonomously classifying earth features into the four categories: bare land; water; vegetation; and clouds, snow, or ice.

Sivertson, W. E., Jr.↗
NASA NTRS1988

Detection of road boundary

Several researchers have proposed and implemented various systems pertaining to the development of autonomous land vehicles (ALVs). One fundamental problem associated with the navigation of an ALV is the ability to efficiently extract the boundaries of the pathway that need to be navigated. In this paper a method is presented that will determine the road boundaries in one pass using a limited search area in the input image. The method employs the statistical information regarding the gray levels present in the images along with geometrical constraints concerning the road. Some examples are given to demonstrate the efficacy of the method.

Sowers, James P.↗
NASA NTRS2000

Passive Night Vision Sensor Comparison for Unmanned Ground Vehicle Stereo Vision Navigation

One goal of the "Demo III" unmanned ground vehicle program is to enable autonomous nighttime navigation at speeds of up to 10 m.p.h. To perform obstacle detection at night with stereo vision will require night vision cameras that produce adequate image quality for the driving speeds, vehicle dynamics, obstacle sizes, and scene conditions that will be encountered. This paper analyzes the suitability of four classes of night vision cameras (3-5 micrometer cooled FLIR, 8-12 micrometer cooled FLIR, 8-12 micrometer uncooled FLIR, and image intensifiers) for night stereo vision, using criteria based on stereo matching quality, image signal to noise ratio, motion blur and synchronization capability. We find that only cooled FLIRs will enable stereo vision performance that meets the goals of the Demo III program for nighttime autonomous mobility.

Owens, Ken↗
NASA NTRS2021

LiDAR-Inertial Based Navigation and Mapping for Precision Landing

Future lander missions will travel to ambitious, scientifically interesting locations near rough and dangerous terrain. They will need to operate with limited prior information about the terrain, and under varying lighting conditions. Landing safely and precisely in the face of these challenges is difficult for existing vision-based landing systems, which require detailed orbital reconnaissance, a priori hazard maps, and impose time-of-day restrictions on landing to ensure similar lighting conditions in orbital and descent imagery. Advanced 3D imaging LiDAR systems currently under development, and originally intended for single-scan hazard detection, have the potential to be operated continuously from altitudes of up to 5 km. Used together with existing inertial measurement units (IMUs), these sensors open a path-to-flight for a full navigation and mapping system, which could replace or augment a traditional landing sensor suite. A landing system based around these sensors can perform accurate altimetry, map-relative localization (MRL), LiDAR-inertial odometry, and map refinement in an illumination-insensitive manner, over unknown or partially known terrain. This paper outlines preliminary work on a LiDAR-inertial landing system that: estimates the spacecraft trajectory during entry, descent, and landing (EDL); and maps the topography of the terrain below, for future use in hazard detection and avoidance. An incremental, factor graph based, smoothing approach is used to solve for the maximum a posteriori trajectory of spacecraft states. Integrated IMU measurements and features tracked in adjacent range and intensity images are used to estimate motion (LiDAR-inertial odometry). LiDAR scans are binned into motion-corrected digital elevation models (DEMs), which are matched to an existing orbital topographic map to provide absolute position information (MRL). The estimated trajectory is then used to project the LiDAR scans into the map frame, creating a variable-resolution quadtree topographic map suitable for hazard detection and avoidance. Existing topographic maps from throughout the solar system (i.e., Earth, the Moon, Mars, Ceres, Vesta, Europa, Enceladus, and Eros) are upsampled for use in EDL simulations. The Mars 2020 Lander Vision System Simulator (LVSS) is extended to simulate LiDAR-inertial data for realistic EDL trajectories. Results of the algorithm operating on the simulated data are presented. Estimated spacecraft trajectory and refined map are compared to ground truth to assess estimation accuracy.

Katake, Anup↗
NASA NTRS2005

Target Tracking, Approach, and Camera Handoff for Automated Instrument Placement

This paper describes the target designation, tracking, approach, and camera handoff technologies required to achieve accurate, single-command autonomous instrument placement for a planetary rover. It focuses on robust tracking integrated with obstacle avoidance during the approach phase, and image-based camera handoff to allow vision-based instrument placement. It also provides initial results from a complete system combining these technologies with rover base placement to maximize arm manipulability and image-based instrument placement.

target tracking↗