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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

The Kinematic Navigation and Cartography Knapsack (KNaCK): Demonstrating SLAM (Simultaneous Localization and Mapping) LiDAR as a Tool for Exploration and Mapping of Lunar Pits and Caves.

Renewed interest in deep space exploration has made establishing a persistent human presence on the Moon and eventually Mars a priority. Sustained habitation of the Moon will require in-situ resource utilization (ISRU) and protection from radiation at the lunar surface. Lunar caves are of interest to the space community because they could provide shelter from radiation, access to water deposits, and a space for habitation, as well as hold information about the geology, volcanology, and evolution of the Moon. Developing the tools to explore, map, and characterize these voids is key to understanding the Moon as a planetary body and to establishing a permanent human presence there. Our team is currently developing tools that enable ultra-high resolution terrain mapping and navigation using mobile light detection and ranging (LIDAR) technology and simultaneous localization and mapping (SLAM) algorithms in fully GPS-denied and no-light environments. 3D mapping with LiDAR and SLAM is relatively under-used, particularly in the context of planetary exploration and planetary analog environments. The backpack mounted LiDAR instrument currently under development by the KNaCK (Kinematic Navigation and Cartography Knapsack) team has demonstrated the potential of mobile SLAM LiDAR for lunar, planetary, and terrestrial cave exploration, study, and utilization. A description of the instrument and associated SLAM algorithms used for mapping in GPS-denied environments are referenced here.

LiDAR↗
NASA NTRSDate not supplied

The Kinematic Navigation and Cartography Knapsack (KNaCK): Demonstrating SlLAM (Simultaneous Localization and Mapping) LiDAR as a Tool for Exploration and Mapping of Lunar Pits and Caves

KNaCK (Kinematic Navigation and Cartography Knapsack) is a backpack-mounted mobile LiDAR (Light Detection and Ranging) system. It can map its surroundings in 3 dimensions and localize itself in space. The project is exploring how LiDAR can advance terrain mapping and navigation at the lunar south pole. KNaCK is lead by Dr. Michael Zanetti of NASA MSFC’s Heliophysics and Planetary Science Branch. - KNaCK serves as - A test article for GPS denied mapping and navigation. - A test bed for SLAM (Simultaneous Localization and Mapping) algorithms. - A test bed for commercial LiDAR units. - A tool for terrestrial science.

LiDAR↗
NASA NTRSDate not supplied

Caves as Planetary Analogs for GPS Denied, Low-Light Mapping and Navigation in Rugged Environments

KNaCK (Kinematic Navigation and Cartography Knapsack) is a backpack-mounted mobile mapping system. It can map its surroundings in 3 dimensions and localize itself in space using a LiDAR (Light Detection and Ranging) sensor and SLAM (Simultaneous Localization and Mapping) algorithm. The KNaCK team is leveraging caves as a proving ground to refine technology for mapping and navigation on other worlds while simultaneously advancing the State of the Art for terrestrial cave exploration and study.

LiDAR↗
NASA NTRSDate not supplied

Caves as Planetary Analogs for GPS Denied, Low-Light Mapping and Navigation in Rugged Environments

KNaCK (Kinematic Navigation and Cartography Knapsack) is a backpack-mounted mobile mapping system. It can map its surroundings in 3 dimensions and localize itself in space using a LiDAR (Light Detection and Ranging) sensor and SLAM (Simultaneous Localization and Mapping) algorithm. The KNaCK team is leveraging caves as a proving ground to refine technology for mapping and navigation on other worlds while simultaneously advancing the State of the Art for terrestrial cave exploration and study.

Relevant environment testing↗
NASA NTRSDate not supplied

Mobile LiDAR as a Tool for Terrestrial and Planetary Cave Exploration and Mapping

KNaCK (Kinematic Navigation and Cartography Knapsack) is a backpack-mounted mobile mapping system. It can map its surroundings in 3 dimensions and localize itself in space using a LiDAR (Light Detection and Ranging) sensor and SLAM (Simultaneous Localization and Mapping) algorithm. The KNaCK team is leveraging caves as a proving ground to refine technology for mapping and navigation on other worlds while simultaneously advancing the State of the Art for terrestrial cave exploration and study.

LiDAR↗
NASA NTRSDate not supplied

Caves as Planetary Analogs for GPS Denied, Low-Light Mapping and Navigation in Rugged Environments. Lightning Talk. LSIC 2023 Fall Meeting.

KNaCK (Kinematic Navigation and Cartography Knapsack) is a backpack-mounted mobile mapping system. It can map its surroundings in 3 dimensions and localize itself in space using a LiDAR (Light Detection and Ranging) sensor and SLAM (Simultaneous Localization and Mapping) algorithm. The KNaCK team is leveraging caves as a proving ground to refine technology for mapping and navigation on other worlds while simultaneously advancing the State of the Art for terrestrial cave exploration and study.

Relevant environment testing↗
NASA NTRSDate not supplied

Mobile Lidar as A Tool for Terrestrial and Planetary Cave Exploration and Mapping

The Kinematic Navigation and Cartography Knapsack (KNaCK) team at NASA’s Marshall Space Flight Center in Huntsville, Alabama is developing tools that enable ultra-high resolution terrain mapping and navigation using mobile LiDAR (Light Detection and Ranging) and SLAM (Simultaneous Localization and Mapping) algorithms in fully GPS-denied and unilluminated environments [1,2]. The backpack mounted LiDAR instrument under development by our team demonstrates the potential of mobile SLAM LiDAR for use in challenging lunar and planetary surface environments as well as for lunar, planetary, and terrestrial cave exploration, study, and utilization.

Lunar Skylight↗
NASA NTRSDate not supplied

Caves as Terrestrial Analogs for Mapping and Exploration in Planetary Surface and Subsurface Environments.

The Kinematic Navigation and Cartography Knapsack (KNaCK) team is developing tools that will enable ultra-high resolution terrain mapping and navigation at the lunar surface. KNaCK uses mobile light detection and ranging (LiDAR) and simultaneous localization and mapping (SLAM) algorithms to operate in fully GPS-denied and unilluminated environments. Testing in relevant analogs is key to perfecting this technology for planetary applications. After utilizing desert and volcanic environments for multiple tests, the team is now using caves as an additional proving ground. Tests in terrestrial caves have demonstrated the potential of mobile SLAM LiDAR for use in challenging surface environments such as steep walled craters and permanently shadowed regions as well as for lunar, planetary, and terrestrial cave exploration, study, and utilization.

LiDAR↗
NASA NTRSDate not supplied

Caves as Planetary Analogs for GPS Denied, Low-Light Mapping and Navigation in Rugged Environments

KNaCK (Kinematic Navigation and Cartography Knapsack) is a backpack-mounted mobile mapping system. It can map its surroundings in 3 dimensions and localize itself in space using a LiDAR (Light Detection and Ranging) sensor and SLAM (Simultaneous Localization and Mapping) algorithm. The KNaCK team is leveraging caves as a proving ground to refine technology for mapping and navigation on other worlds while simultaneously advancing the State of the Art for terrestrial cave exploration and study.

LiDAR↗
NASA NTRSDate not supplied

Mobile LiDAR as A Tool for Terrestrial and Planetary Cave Exploration and Mapping

The Kinematic Navigation and Cartography Knapsack (KNaCK) team at NASA’s Marshall Space Flight Center in Huntsville, Alabama is developing tools that enable ultra-high resolution terrain mapping and navigation using mobile LiDAR (Light Detection and Ranging) and SLAM (Simultaneous Localization and Mapping) algorithms in fully GPS-denied and unilluminated environments. The backpack mounted LiDAR instrument under development by our team demonstrates the potential of mobile SLAM LiDAR for use in challenging lunar and planetary surface environments as well as for lunar, planetary, and terrestrial cave exploration, study, and utilization.

LiDAR↗
DOE OSTI2017

DIC Challenge: Developing Images and Guidelines for Evaluating Accuracy and Resolution of 2D Analyses

With the rapid spread in use of Digital Image Correlation (DIC) globally, it is important there be some standard methods of verifying and validating DIC codes. To this end, the DIC Challenge board was formed and is maintained under the auspices of the Society for Experimental Mechanics (SEM) and the international DIC society (iDICs). The goal of the DIC Board and the 2D–DIC Challenge is to supply a set of well-vetted sample images and a set of analysis guidelines for standardized reporting of 2D–DIC results from these sample images, as well as for comparing the inherent accuracy of different approaches and for providing users with a means of assessing their proper implementation. This document will outline the goals of the challenge, describe the image sets that are available, and give a comparison between 12 commercial and academic 2D–DIC codes using two of the challenge image sets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Stereo-DIC Challenge 1.0 – Rigid Body Motion of a Complex Shape

Background Stereo-DIC is a widely used optical measurement technique that provides a dense full-field 3D measurement of the shape, displacement, and strain of a solid sample. When compared with 2D-DIC, Stereo-DIC provides greater flexibility and expands its use beyond flat, planar specimens. Furthermore, the widespread availability of commercial systems has led to the adoption of the technique throughout industry, academia, and government research labs. Objective Even though some research has been done to understand the effects of different experimental and stereo-DIC parameters, no reference is available to benchmark and compare the performance of current stereo-DIC algorithms to each other. Methods This paper provides the description and analysis of a carefully controlled 3D experiment and associated images used to compare the results from five subset based DIC software packages. Both the images and analysis codes used in this paper to compare the results are described here and are available for download and use for continued research. Results We show that over a very large range of motion, the 3D errors are very small, less than 80μm over a travel of ±20 mm out-of-plane and ±20 mm in-plane. While all codes performed similarly, there are important differences noted in the paper. Conclusion The image sets and results comparison software are hosted by the International DIC Society (www.iDICs.org) and are freely available for download and analysis for comparison with results in this paper. Furthermore, it is hoped that this set of images can be used for future research in improving stereo-DIC by future authors.

Algorithms comparison↗
DOE OSTI2022

Chromosome evolution and the genetic basis of agronomically important traits in greater yam

The nutrient-rich tubers of the greater yam, Dioscorea alata L., provide food and income security for millions of people around the world. Despite its global importance, however, greater yam remains an orphan crop. Here, we address this resource gap by presenting a highly contiguous chromosome-scale genome assembly of D. alata combined with a dense genetic map derived from African breeding populations. The genome sequence reveals an ancient allotetraploidization in the Dioscorea lineage, followed by extensive genome-wide reorganization. Using the genomic tools, we find quantitative trait loci for resistance to anthracnose, a damaging fungal pathogen of yam, and several tuber quality traits. Genomic analysis of breeding lines reveals both extensive inbreeding as well as regions of extensive heterozygosity that may represent interspecific introgression during domestication. These tools and insights will enable yam breeders to unlock the potential of this staple crop and take full advantage of its adaptability to varied environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Theoretical analysis on the measurement errors of local 2D DIC: Part I temporal and spatial uncertainty quantification of displacement measurements

This study presents a theoretical uncertainty quantification of displacement measurements by subset-based 2D-digital image correlation. A generalized solution to estimate the random error of displacement measurement is presented. The obtained solution suggests that the random error of displacement measurements is determined by the image noise, the summation of the intensity gradient in a subset, the subpixel part of displacement, and the interpolation scheme. The proposed method is validated with virtual digital image correlation tests.

2D-DIC↗
DOE OSTI2020

Validation of finite-element models using full-field experimental data: Levelling finite-element analysis data through a digital image correlation engine

Full-field data from digital image correlation (DIC) provide rich information for finite-element analysis (FEA) validation. However, there are several inherent inconsistencies between FEA and DIC data that must be rectified before meaningful, quantitative comparisons can be made, including strain formulations, coordinate systems, data locations, strain calculation algorithms, spatial resolutions and data filtering. As such, in this paper, we investigate two full-field validation approaches: (1) the direct interpolation approach, which addresses the first three inconsistencies by interpolating the quantity of interest from one mesh to the other, and (2) the proposed DIC-levelling approach, which addresses all six inconsistencies simultaneously by processing the FEA data through a stereo-DIC simulator to ‘level’ the FEA data to the DIC data in a regularisation sense. Synthetic ‘experimental’ DIC data were generated based on a reference FEA of an exemplar test specimen. The direct interpolation approach was applied, and significant strain errorswere computed, even though therewas no model form error, because the filtering effect of theDIC enginewas neglected. In contrast, the levelling approach provided accurate validation results, with no strain error when no model form error was present. Next, model form error was purposefully introduced via a mismatch of boundary conditions. With the direct interpolation approach, the mismatch in boundary conditions was completely obfuscated, while with the levelling approach, it was clearly observed. Finally, the ‘experimental’ DIC datawere purposefully misaligned slightly fromthe FEA data. Both validation techniques suffered from the misalignment, thus motivating continued efforts to develop a robust alignment process. In conclusion, direct interpolation is insufficient, and the proposed levelling approach is required to ensure that the FEA and the DIC data have the same spatial resolution and data filtering. Only after the FEA data have been ‘levelled’ to the DIC data can meaningful, quantitative error maps be computed.

42 ENGINEERING↗
DOE OSTI2017

Genome sequencing of the staple food crop white Guinea yam enables the development of a molecular marker for sex determination

Background: Root and tuber crops are a major food source in tropical Africa. Among these crops are several species in the monocotyledonous genus Dioscorea collectively known as yam, a staple tuber crop that contributes enormously to the subsistence and socio-cultural lives of millions of people, principally in West and Central Africa. Yam cultivation is constrained by several factors, and yam can be considered a neglected “orphan” crop that would benefit from crop improvement efforts. However, the lack of genetic and genomic tools has impeded the improvement of this staple crop. Results: To accelerate marker-assisted breeding of yam, we performed genome analysis of white Guinea yam (Dioscorea rotundata) and assembled a 594-Mb genome, 76.4% of which was distributed among 21 linkage groups. In total, we predicted 26,198 genes. Phylogenetic analyses with 2381 conserved genes revealed that Dioscorea is a unique lineage of monocotyledons distinct from the Poales (rice), Arecales (palm), and Zingiberales (banana). The entire Dioscorea genus is characterized by the occurrence of separate male and female plants (dioecy), a feature that has limited efficient yam breeding. To infer the genetics of sex determination, we performed whole-genome resequencing of bulked segregants (quantitative trait locus sequencing [QTL-seq]) in F1 progeny segregating for male and female plants and identified a genomic region associated with female heterogametic (male = ZZ, female = ZW) sex determination. We further delineated the W locus and used it to develop a molecular marker for sex identification of Guinea yam plants at the seedling stage. Conclusions: Guinea yam belongs to a unique and highly differentiated clade of monocotyledons. The genome analyses and sex-linked marker development performed in this study should greatly accelerate marker-assisted breeding of Guinea yam. In addition, our QTL-seq approach can be utilized in genetic studies of other outcrossing crops and organisms with highly heterozygous genomes. Genomic analysis of orphan crops such as yam promotes efforts to improve food security and the sustainability of tropical agriculture.

59 BASIC BIOLOGICAL SCIENCES↗