16,831 research outputs found
Overcoming the Challenges Associated with Image-based Mapping of Small Bodies in Preparation for the OSIRIS-REx Mission to (101955) Bennu
The OSIRIS-REx Asteroid Sample Return Mission is the third mission in NASA's
New Frontiers Program and is the first U.S. mission to return samples from an
asteroid to Earth. The most important decision ahead of the OSIRIS-REx team is
the selection of a prime sample-site on the surface of asteroid (101955) Bennu.
Mission success hinges on identifying a site that is safe and has regolith that
can readily be ingested by the spacecraft's sampling mechanism. To inform this
mission-critical decision, the surface of Bennu is mapped using the OSIRIS-REx
Camera Suite and the images are used to develop several foundational data
products. Acquiring the necessary inputs to these data products requires
observational strategies that are defined specifically to overcome the
challenges associated with mapping a small irregular body. We present these
strategies in the context of assessing candidate sample-sites at Bennu
according to a framework of decisions regarding the relative safety,
sampleability, and scientific value across the asteroid's surface. To create
data products that aid these assessments, we describe the best practices
developed by the OSIRIS-REx team for image-based mapping of irregular small
bodies. We emphasize the importance of using 3D shape models and the ability to
work in body-fixed rectangular coordinates when dealing with planetary surfaces
that cannot be uniquely addressed by body-fixed latitude and longitude.Comment: 31 pages, 10 figures, 2 table
Learning Ground Traversability from Simulations
Mobile ground robots operating on unstructured terrain must predict which
areas of the environment they are able to pass in order to plan feasible paths.
We address traversability estimation as a heightmap classification problem: we
build a convolutional neural network that, given an image representing the
heightmap of a terrain patch, predicts whether the robot will be able to
traverse such patch from left to right. The classifier is trained for a
specific robot model (wheeled, tracked, legged, snake-like) using simulation
data on procedurally generated training terrains; the trained classifier can be
applied to unseen large heightmaps to yield oriented traversability maps, and
then plan traversable paths. We extensively evaluate the approach in simulation
on six real-world elevation datasets, and run a real-robot validation in one
indoor and one outdoor environment.Comment: Webpage: http://romarcg.xyz/traversability_estimation
Radar shadow detection in SAR images using DEM and projections
Synthetic aperture radar (SAR) images are widely used in target recognition
tasks nowadays. In this letter, we propose an automatic approach for radar
shadow detection and extraction from SAR images utilizing geometric projections
along with the digital elevation model (DEM) which corresponds to the given
geo-referenced SAR image. First, the DEM is rotated into the radar geometry so
that each row would match that of a radar line of sight. Next, we extract the
shadow regions by processing row by row until the image is covered fully. We
test the proposed shadow detection approach on different DEMs and a simulated
1D signals and 2D hills and volleys modeled by various variance based Gaussian
functions. Experimental results indicate the proposed algorithm produces good
results in detecting shadows in SAR images with high resolution.Comment: 10 pages, 6 figure
Ground Profile Recovery from Aerial 3D LiDAR-based Maps
The paper presents the study and implementation of the ground detection
methodology with filtration and removal of forest points from LiDAR-based 3D
point cloud using the Cloth Simulation Filtering (CSF) algorithm. The
methodology allows to recover a terrestrial relief and create a landscape map
of a forestry region. As the proof-of-concept, we provided the outdoor flight
experiment, launching a hexacopter under a mixed forestry region with sharp
ground changes nearby Innopolis city (Russia), which demonstrated the
encouraging results for both ground detection and methodology robustness.Comment: 8 pages, FRUCT-2019 conferenc
Numerical simulation of the stress-strain state of the dental system
We present mathematical models, computational algorithms and software, which
can be used for prediction of results of prosthetic treatment. More interest
issue is biomechanics of the periodontal complex because any prosthesis is
accompanied by a risk of overloading the supporting elements. Such risk can be
avoided by the proper load distribution and prediction of stresses that occur
during the use of dentures. We developed the mathematical model of the
periodontal complex and its software implementation. This model is based on
linear elasticity theory and allows to calculate the stress and strain fields
in periodontal ligament and jawbone. The input parameters for the developed
model can be divided into two groups. The first group of parameters describes
the mechanical properties of periodontal ligament, teeth and jawbone (for
example, elasticity of periodontal ligament etc.). The second group
characterized the geometric properties of objects: the size of the teeth, their
spatial coordinates, the size of periodontal ligament etc. The mechanical
properties are the same for almost all, but the input of geometrical data is
complicated because of their individual characteristics. In this connection, we
develop algorithms and software for processing of images obtained by computed
tomography (CT) scanner and for constructing individual digital model of the
tooth-periodontal ligament-jawbone system of the patient. Integration of models
and algorithms described allows to carry out biomechanical analysis on
three-dimensional digital model and to select prosthesis design.Comment: 19 pages, 9 figure
Canopy height estimation from lidar data using open source software compared with commercial software
The goal of this study is to analyze the performance of Open Source Software (OSS) towards the generation of Digital Terrain Model (DTM) and Digital Surface Model (DSM), further on estimates the canopy height by using Light Detection and Ranging (LIDAR) data. Generation of DTM and DSM are very important in this research to ensure that better canopy height can be modeled. DTM and DSM commonly known as a digital representation of earth surface topography where DTM only represent the ground surface while DSM represent all the features including buildings and trees. Many software that have a function to generate DTM and DSM were developed recently. However, most software has been commercialized; therefore it requires a high expenditure to own the software. Advanced technology has lead to the emergence of the growing OSS. OSS is software that can be downloaded for free via the internet. By taking the forestry area of Pekan, Pahang for this research, LIDAR data for that particular area is processed by using the OSS Geographic Resources Analysis Support System (GRASS). To determine the effectiveness and capability of GRASS in the DTM and DSM generation, the same data were processed using commercial software which is TerraScan so that the result can be compared, further on better canopy height can be modele
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