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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Comparison of Visual and LiDAR SLAM Algorithms using NASA Flight Test Data

Simultaneous Localization and Mapping (SLAM) is a promising technique that provides localization information and precise mapping of the physical environment without having much prior knowledge of the surroundings. SLAM may have a vital role in aeronautics and aerospace, where vehicles and aircraft must operate in complex environments with traditional localization services that may be degraded or unavailable. This paper compares several pre-canned 3D SLAM algorithms based on vision and LiDAR, namely ORB-SLAM, ORB-SLAM2, LOAM, A-LOAM, and F-LOAM on NASA UAS (Unmanned Aircraft System) flight test data. The NASA ARC UAS flight test demonstrates preliminary SLAM algorithm results, which serve as a stepping stone to simulated AAM (Advanced Air Mobility) concepts. Conducting AFRC UAS flight test for simulated AAM approach and landing with SLAM algorithms provides an Alternative Precision Navigation and Timing solution based on distributed landmarks and fiducials in the landing zone. These algorithms use the telemetry data as ground truth for a baseline comparison. The criteria of the performance comparison include robustness, accuracy, re-localization, response to environmental changes, and real-time effectiveness, which are currently qualitative but to be quantitative in the future.

computer vision↗
NASA NTRSDate not supplied

Comparison of Visual and LiDAR SLAM Algorithms using NASA Flight Test Data

Simultaneous Localization and Mapping (SLAM) is a promising technique that provides localization information and precise mapping of the physical environment without having much prior knowledge of the surroundings. SLAM may have a vital role in aeronautics and aerospace, where vehicles and aircraft must operate in complex environments with traditional localization services that may be degraded or unavailable. This paper compares several pre-canned 3D SLAM algorithms based on vision and LiDAR, namely ORB-SLAM, ORB-SLAM2, LOAM, A-LOAM, and F-LOAM on NASA UAS (Unmanned Aircraft System) flight test data. The NASA ARC UAS flight test demonstrates preliminary SLAM algorithm results, which serve as a stepping stone to simulated AAM (Advanced Air Mobility) concepts. Conducting AFRC UAS flight test for simulated AAM approach and landing with SLAM algorithms provides an Alternative Precision Navigation and Timing solution based on distributed landmarks and fiducials in the landing zone. These algorithms use the telemetry data as ground truth for a baseline comparison. The criteria of the performance comparison include robustness, accuracy, re-localization, response to environmental changes, and real-time effectiveness, which are currently qualitative but to be quantitative in the future.

computer vision↗
NASA NTRS1995

Effects of ATC automation on precision approaches to closely space parallel runways

Improved navigational technology (such as the Microwave Landing System and the Global Positioning System) installed in modern aircraft will enable air traffic controllers to better utilize available airspace. Consequently, arrival traffic can fly approaches to parallel runways separated by smaller distances than are currently allowed. Previous simulation studies of advanced navigation approaches have found that controller workload is increased when there is a combination of aircraft that are capable of following advanced navigation routes and aircraft that are not. Research into Air Traffic Control automation at Ames Research Center has led to the development of the Center-TRACON Automation System (CTAS). The Final Approach Spacing Tool (FAST) is the component of the CTAS used in the TRACON area. The work in this paper examines, via simulation, the effects of FAST used for aircraft landing on closely spaced parallel runways. The simulation contained various combinations of aircraft, equipped and unequipped with advanced navigation systems. A set of simulations was run both manually and with an augmented set of FAST advisories to sequence aircraft, assign runways, and avoid conflicts. The results of the simulations are analyzed, measuring the airport throughput, aircraft delay, loss of separation, and controller workload.

Slattery, R.↗
NASA NTRSDate not supplied

Doppler Lidar for Precision Landing on Planetary Bodies with and without Atmosphere

Global Positioning System (GPS) is commonly used in terrestrial navigation for vehicle position and velocity knowledge. In the absence of a GPS signal, past landing missions to planetary bodies primarily relied on radar to provide the necessary data to execute descent and landing maneuvers. We have developed a coherent Doppler lidar, called Navigation Doppler Lidar (NDL), that offers several critical advantages com-pared to radar, including significantly higher precision with reduced size, mass, and power.

Doppler lidar↗
NASA NTRS1978

Inertially-aided, all-weather landing systems for C/TOL

Ways to improve significantly all-weather landing systems technology for conventional take-off and landing vehicles, primarily, the large commercial jets, were studied. It was concluded that there is a great deal to be gained by extensive use of inertial navigation system derived information, primarily, the translational information inherent in an inertial navigator, for improving all-weather landing system performance.

Pawlak, R. J.↗
NASA NTRS2013

A Hybrid FPGA/Tilera Compute Element for Autonomous Hazard Detection and Navigation

To increase safety for future missions landing on other planetary or lunar bodies, the Autonomous Landing and Hazard Avoidance Technology (ALHAT) program is developing an integrated sensor for autonomous surface analysis and hazard determination. The ALHAT Hazard Detection System (HDS) consists of a Flash LIDAR for measuring the topography of the landing site, a gimbal to scan across the terrain, and an Inertial Measurement Unit (IMU), along with terrain analysis algorithms to identify the landing site and the local hazards. An FPGA and Manycore processor system was developed to interface all the devices in the HDS, to provide high-resolution timing to accurately measure system state, and to run the surface analysis algorithms quickly and efficiently. In this paper, we will describe how we integrated COTS components such as an FPGA evaluation board, a TILExpress64, and multi-threaded/multi-core aware software to build the HDS Compute Element (HDSCE). The ALHAT program is also working with the NASA Morpheus Project and has integrated the HDS as a sensor on the Morpheus Lander. This paper will also describe how the HDS is integrated with the Morpheus lander and the results of the initial test flights with the HDS installed. We will also describe future improvements to the HDSCE.

Multicore↗
NASA NTRS2013

A hybrid FPGA/Tilera compute element for autonomous hazard detection and navigation

To increase safety for future missions landing on other planetary or lunar bodies, the Autonomous Landing and Hazard Avoidance Technology (ALHAT) program is developing an integrated sensor for autonomous surface analysis and hazard determination. The ALHAT Hazard Detection System (HDS) consists of a Flash LIDAR for measuring the topography of the landing site, a gimbal to scan across the terrain, and an Inertial Measurement Unit (IMU), along with terrain analysis algorithms to identify the landing site and the local hazards. An FPGA and Manycore processor system was developed to interface all the devices in the HDS, to provide high-resolution timing to accurately measure system state, and to run the surface analysis algorithms quickly and efficiently. In this paper, we will describe how we integrated COTS components such as an FPGA evaluation board, a TILExpress64, and multi-threaded/multi-core aware software to build the HDS Compute Element (HDSCE). The ALHAT program is also working with the NASA Morpheus Project and has integrated the HDS as a sensor on the Morpheus Lander. This paper will also describe how the HDS is integrated with the Morpheus lander and the results of the initial test flights with the HDS installed. We will also describe future improvements to the HDSCE.

Trawny, Nikolas↗
NASA NTRS2008

A Self Contained Method for Safe and Precise Lunar Landing

The return of humans to the Moon will require increased capability beyond that of the previous Apollo missions. Longer stay times and a greater flexibility with regards to landing locations are among the many improvements planned. A descent and landing system that can land the vehicle more accurately than Apollo with a greater ability to detect and avoid hazards is essential to the development of a Lunar Outpost, and also for increasing the number of potentially reachable Lunar Sortie locations. This descent and landing system should allow landings in more challenging terrain and provide more flexibility with regards to mission timing and lighting considerations, while maintaining safety as the top priority. The lunar landing system under development by the ALHAT (Autonomous precision Landing and Hazard detection Avoidance Technology) project is addressing this by providing terrain-relative navigation measurements to enhance global-scale precision, an onboard hazard-detection system to select safe landing locations, and an Autonomous GNC (Guidance, Navigation, and Control) capability to process these measurements and safely direct the vehicle to this landing location. This ALHAT landing system will enable safe and precise lunar landings without requiring lunar infrastructure in the form of navigation aids or a priori identified hazard-free landing locations. The safe landing capability provided by ALHAT uses onboard active sensing to detect hazards that are large enough to be a danger to the vehicle but too small to be detected from orbit, given currently planned orbital terrain resolution limits. Algorithms to interpret raw active sensor terrain data and generate hazard maps as well as identify safe sites and recalculate new trajectories to those sites are included as part of the ALHAT System. These improvements to descent and landing will help contribute to repeated safe and precise landings for a wide variety of terrain on the Moon.

Paschall, Stephen C., II↗
NASA NTRS2004

Systems for pinpoint landing at Mars

Mars landers have been able to land only within tens to hundreds of km of a target site due to uncertainties in approach navigation, atmospheric modeling, and vehichle aerodynamics; as well as due to map-tie error and wind drift. The Mars Science Laboratory mission will improve this to 5-10 km using optical navigation and entry guidance. To achieve "pinpoint landing" (within 100m) for future missions, ways of addressing the remaining error sources must be found.

Johnson, Wyatt↗
NASA NTRS2004

Mars Exploration Rover - a new standard for interplanetary navigation

The twin Mars Exploration Rovers, Spirit and Opportunity, arrived at Mars for landings respectively at Gusev Crater (on January 4, 2004) and Meridiani Planum (on January 25, 2004). During the development of the mission, the capability of the navigation system to deliver the landers within a particular accuracy played a major role in landing site selection. This process ultimately resulted in commitments to deliver each lander within a specified landing ellipse (about 70 km x 5 km) determined to be safe for landing and also judged to be scientifically interesting. Achieving atmospheric entry delivery accuracies consistent with this landing requirement necessitated significant improvements to the interplanetary navigation system used for MER. These improvements included new processes and software for orbit determination, aggressive, mission-critical use of interferometric ADOR tracking data, propulsive maneuver design, and entry, descent, and landing (EDL) trajectory simulation. Because these advances pressed the state -of -the art, innovative methods to verify the assumptions in the pre-launch covariance analyses were also developed. The actual achieved atmospheric entry accuracies for Spirit and Opportunity significantly bettered the requirements.

navigation↗
NASA NTRS2018

Orion Optical Navigation Progress Toward Exploration: Mission 1

Optical navigation of human spacecraft was proposed on Gemini and implemented successfully on Apollo as a means of autonomously operating the vehicle in the event of lost communication with controllers on Earth. It shares a history with the "method of lunar distances" that was used in the 18th century and gained some notoriety after its use by Captain James Cook during his 1768 Pacific voyage of the HMS Endeavor. The Orion emergency return system utilizing optical navigation has matured in design over the last several years, and is currently undergoing the final implementation and test phase in preparation for Exploration Mission 1 (EM-1) in 2019. The software development is being worked as a Government Furnished Equipment (GFE) project delivered as an application within the Core Flight Software of the Orion camera controller module. The mathematical formulation behind the initial ellipse fit in the image processing is detailed in Christian. The non-linear least squares refinement then follows the technique of Mortari as an estimation process of the planetary limb using the sigmoid function. The Orion optical navigation system uses a body fixed camera, a decision that was driven by mass and mechanism constraints. The general concept of operations involves a 2-hour pass once every 24 hours, with passes specifically placed before all maneuvers to supply accurate navigation information to guidance and targeting. The pass lengths are limited by thermal constraints on the vehicle since the OpNav attitude generally deviates from the thermally stable tail-to-sun attitude maintained during the rest of the orbit coast phase. Calibration is scheduled prior to every pass due to the unknown nature of thermal effects on the lens distortion and the mounting platform deformations between the camera and star trackers. The calibration technique is described in detail by Christian, et al. and simultaneously estimates the Brown-Conrady coefficients and the Star Tracker/Camera interlock angles. Accurate attitude information is provided by the star trackers during each pass. Figure 1 shows the various phases of lunar return navigation when the vehicle is in autonomous operation with lost ground communication. The midcourse maneuvers are placed to control the entry interface conditions to the desired corridor for safe landing. The general form of optical navigation on Orion is where still images of the Moon or Earth are processed to find the apparent angular diameter and centroid in the camera focal plane. This raw data is transformed into range and bearing angle measurements using planetary data and precise star tracker inertial attitude. The measurements are then sent to the main flight computer's Kalman filter to update the onboard state vector. The images are, of course, collected over an arc to converge the state and estimate velocity. The same basic technique was used by Apollo to satisfy loss-of-comm, but Apollo used manual crew sightings with a vehicle-integral sextant instead of autonomously processing optical imagery. The software development is past its Critical Design Review, and is progressing through test and certification for human rating. In support of this, a hardware-in-the-loop test rig was developed in the Johnson Space Center Electro-Optics Lab to exercise the OpNav system prior to integrated testing on the Orion vehicle. Figure 2 shows the rig, which the test team has dubbed OCILOT (Orion Camera In the Loop Optical Testbed). Analysis performed to date shows a delivery that satisfies an allowable entry corridor as shown in Figure 3.

Holt, Greg N.↗
NASA NTRS2018

Development of a Coherent Doppler Lidar for Precision Maneuvering and Landing of Space Vehicles

A coherent Doppler lidar has been developed to address NASA’s need for a high-performance, compact, and cost-effective velocity and altitude sensor onboard its landing vehicles. Future robotic and manned missions to planetary bodies require precise ground-relative velocity vector and altitude data to execute complex descent maneuvers and safe, soft landing at a pre-designated site. This lidar sensor, referred to as a Navigation Doppler Lidar, meets the required performance of landing missions while complying with vehicle size, mass, and power constraints. Operating from over five kilometers altitude, the lidar obtains velocity and range precision measurements with 2 cm/sec and 2 meters, respectively, dominated by the vehicle motion. After a series of flight tests onboard helicopters and rocket-powered free-flyer vehicles, the Navigation Doppler Lidar is now being ruggedized for future missions to various destinations in the solar system.

Amzaherdian, Farzin↗
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 NTRS1973

Correlation of ERTS-1 and aircraft optical data with water quality parameters of Charlotte Amalie Harbor, St. Thomas, Virgin Islands

The author has identified the following significant results. Attempts to correlate optical aircraft remote sensing of water quality with the optical data from the ERTS-1 satellite using calibrated imagery of Charlotte Amalie harbor, St. Thomas, Virgin Islands are reported. The harbor at Charlotte Amalie has a concentration of a number of factors affecting water quality: untreated sewage, land runoff, and sediment from navigation and dredging operations. Calibration procedures have been originated and applied to ERTS-1 and I2S camera imagery. The results indicate that the ERTS-1 and I2S imagery are correlated with optical in situ measurements of the harbor water. The aircraft green photographic and ERTS-1 MSS-4 bands have been found most suitable for monitoring the scattered light levels under the conditions of the investigation. The chemical parameters of the harbor water were found to be correlated to the optical properties for two stations investigated in detail. The biological properties of the harbor water (chlorophyll and carotenoids), correlate inversely with the optical data near the pollution sources compared to further away. Calibration procedures developed in this investigation were essential to the interpretation of the photographic and ERTS-1 photometric responses.

Coulbourn, W. C.↗