Results for “stereo camera” — Page 4

DOE OSTI2017

stereocambmovie (a1)

STEREOCAM consists of three pairs of stereo camera setups that aim to provide synchronized and stereo-calibrated time series of images that can be used for 3D cloud mask reconstruction. Each camera pair is positioned at approximately 120 degrees from the other pair, with a 17°-19° pitch angle from the ground, and at 5-6 km distance from the ARM Southern Great Plains observatory to cover the region from northeast, northwest, and southern views. Images from both cameras of the same stereo setup can be paired together to obtain 3D reconstruction by triangulation. 3D reconstructions from the ring of three stereo pairs can be combined together to generate a 3D mask from surrounding views. A pair of ARM cloud digital cameras is being used for mobile deployments.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

stereocamb (a1)

STEREOCAM consists of three pairs of stereo camera setups that aim to provide synchronized and stereo-calibrated time series of images that can be used for 3D cloud mask reconstruction. Each camera pair is positioned at approximately 120 degrees from the other pair, with a 17°-19° pitch angle from the ground, and at 5-6 km distance from the ARM Southern Great Plains observatory to cover the region from northeast, northwest, and southern views. Images from both cameras of the same stereo setup can be paired together to obtain 3D reconstruction by triangulation. 3D reconstructions from the ring of three stereo pairs can be combined together to generate a 3D mask from surrounding views. A pair of ARM cloud digital cameras is being used for mobile deployments.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

stereocamamovie (a1)

STEREOCAM consists of three pairs of stereo camera setups that aim to provide synchronized and stereo-calibrated time series of images that can be used for 3D cloud mask reconstruction. Each camera pair is positioned at approximately 120 degrees from the other pair, with a 17°-19° pitch angle from the ground, and at 5-6 km distance from the ARM Southern Great Plains observatory to cover the region from northeast, northwest, and southern views. Images from both cameras of the same stereo setup can be paired together to obtain 3D reconstruction by triangulation. 3D reconstructions from the ring of three stereo pairs can be combined together to generate a 3D mask from surrounding views. A pair of ARM cloud digital cameras is being used for mobile deployments.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

stereocama (a1)

STEREOCAM consists of three pairs of stereo camera setups that aim to provide synchronized and stereo-calibrated time series of images that can be used for 3D cloud mask reconstruction. Each camera pair is positioned at approximately 120 degrees from the other pair, with a 17°-19° pitch angle from the ground, and at 5-6 km distance from the ARM Southern Great Plains observatory to cover the region from northeast, northwest, and southern views. Images from both cameras of the same stereo setup can be paired together to obtain 3D reconstruction by triangulation. 3D reconstructions from the ring of three stereo pairs can be combined together to generate a 3D mask from surrounding views. A pair of ARM cloud digital cameras is being used for mobile deployments.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Predicting 3D Motions from Single-Camera Optical Test Data

In a typical optical test, a stereo camera pair is required to measure the three-dimensional motion of a test article; one camera typically only measures motions in the image plane of the camera, and measurements in the out-of-plane direction are missing. Finite element expansion techniques provide a path to estimate responses from a test at unmeasured degrees of freedom. Treating the case of a single camera as a measurement with unmeasured degrees of freedom, a finite element model is used to expand to the missing third dimension of the image data, allowing a full-field, three-dimensional measurement to be obtained from a set of images from a single camera. The key to this technique relies on the mapping of finite element deformations to image deformations, creating a set of mode shape images that are used to filter the response in the image into modal responses. These modal responses are then applied to the finite element model to estimate physical responses at all finite element model degrees of freedom. The mapping from finite element model to image is achieved using synthetic images produced by a rendering software. Finally, the technique is applied first to a synthetic deformation image, and then is validated using an experimental set of images.

47 OTHER INSTRUMENTATION↗

NASA NTRSDate not supplied

Investigating Photogrammetric Accuracy of a Lunar-lander-induced Crater Measurement System

Laboratory measurements have been made to validate the performance of the Stereo CAmeras for Lunar Plume-Surface Studies (SCALPSS) stereo photogrammetry systems which will be flying to the moon on two of NASA’s upcoming Commercial Lunar Payload Services (CLPS) missions. Until recently, the system’s accuracy had only been studied using idealized geometric shapes as measurement targets. A realistic crater model of representative scale and an idealized ‘staircase’ target have been used to compare measurement accuracy of ideal versus lunar-like objects, with the commercial V-STARS® system being used to provide the known reference values for comparison. In a parametric study, altitude, lens focal length, and camera separation are varied to assess each parameter’s impact on photogrammetric accuracy in relation to the scaling law prediction developed previously. The SCALPSS 1.0 and 1.1 configurations have been validated on the crater model within acceptable accuracy for the missions, performing significantly better than the scaling law prediction in some cases. A semi-automated post-processing routine was developed in MATLAB® and proved successful for the cross-correlation of features between two stereo images. For some cases of extreme convergence angles between a camera pair, manual feature detection and matching was required. By using this manual process, the crater depth map was reconstructed but with worse accuracy than the idealized staircase measurements; refinements to the processing algorithm are expected to improve future results. Also examined in this work is the impact of illumination environments, both natural (e.g., Sun angles) and artificial (diffuse or structured illumination sources), on the camera system’s ability to measure the erosion of the lunar terrain.

Plume-surface interaction↗

NASA NTRSDate not supplied

Investigating Photogrammetric Accuracy of a Lunar-lander-induced Crater Measurement System

Laboratory measurements have been made to validate the performance of the Stereo CAmeras for Lunar Plume-Surface Studies (SCALPSS) stereo photogrammetry systems which will be flying to the moon on two of NASA’s upcoming Commercial Lunar Payload Services (CLPS) missions. Until recently, the system’s accuracy had only been studied using idealized geometric shapes as measurement targets. A realistic crater model of representative scale and an idealized ‘staircase’ target have been used to compare measurement accuracy of ideal versus lunar-like objects, with the commercial V-STARS® system being used to provide the known reference values for comparison. In a parametric study, altitude, lens focal length, and camera separation are varied to assess each parameter’s impact on photogrammetric accuracy in relation to the scaling law prediction developed previously. The SCALPSS 1.0 and 1.1 configurations have been validated on the crater model within acceptable accuracy for the missions, performing significantly better than the scaling law prediction in some cases. A semi-automated post-processing routine was developed in MATLAB® and proved successful for the cross-correlation of features between two stereo images. For some cases of extreme convergence angles between a camera pair, manual feature detection and matching was required. By using this manual process, the crater depth map was reconstructed but with worse accuracy than the idealized staircase measurements; refinements to the processing algorithm are expected to improve future results. Also examined in this work is the impact of illumination environments, both natural (e.g., Sun angles) and artificial (diffuse or structured illumination sources), on the camera system’s ability to measure the erosion of the lunar terrain.

Plume-surface interaction↗

NASA NTRS2012

Vehicle Detection for RCTA/ANS (Autonomous Navigation System)

Using a stereo camera pair, imagery is acquired and processed through the JPLV stereo processing pipeline. From this stereo data, large 3D blobs are found. These blobs are then described and classified by their shape to determine which are vehicles and which are not. Prior vehicle detection algorithms are either targeted to specific domains, such as following lead cars, or are intensity- based methods that involve learning typical vehicle appearances from a large corpus of training data. In order to detect vehicles, the JPL Vehicle Detection (JVD) algorithm goes through the following steps: 1. Take as input a left disparity image and left rectified image from JPLV stereo. 2. Project the disparity data onto a two-dimensional Cartesian map. 3. Perform some post-processing of the map built in the previous step in order to clean it up. 4. Take the processed map and find peaks. For each peak, grow it out into a map blob. These map blobs represent large, roughly vehicle-sized objects in the scene. 5. Take these map blobs and reject those that do not meet certain criteria. Build descriptors for the ones that remain. Pass these descriptors onto a classifier, which determines if the blob is a vehicle or not. The probability of detection is the probability that if a vehicle is present in the image, is visible, and un-occluded, then it will be detected by the JVD algorithm. In order to estimate this probability, eight sequences were ground-truthed from the RCTA (Robotics Collaborative Technology Alliances) program, totaling over 4,000 frames with 15 unique vehicles. Since these vehicles were observed at varying ranges, one is able to find the probability of detection as a function of range. At the time of this reporting, the JVD algorithm was tuned to perform best at cars seen from the front, rear, or either side, and perform poorly on vehicles seen from oblique angles.

Brennan, Shane↗

NASA NTRS2017

Plateaus and Sinuous Ridges as the Fingerprints of Lava Flow Inflation in the Eastern Tharsis Plains of Mars

The Tharsis Montes rift aprons are composed of outpourings of lava from chaotic terrains to the northeast and southwest flank of each volcano. Sinuous and branching channel networks that are present on the rift aprons suggest the possibility of fluvial processes in their development, or erosion by rapidly emplaced lavas, but the style of lava flow emplacement throughout rift apron development is not clearly understood. To better characterize the style of lava emplacement and role of fluvial processes in rift apron development, we conducted morphological mapping of the Pavonis Mons southwest rift apron and the eastern Tharsis plains using images from the High Resolution Imaging Science Experiment (HiRISE), Mars Orbiter Camera (MOC), Context Camera (CTX), Thermal Emission Imaging System (THEMIS), and High Resolution Stereo Camera (HRSC) along with the Mars Orbiter Laser Altimeter (MOLA) Precision Experiment Data Records (PEDRs) and gridded data. Our approach was to: (1) search for depositional fans at the slope break between the rift apron and adjacent low slope plains; (2) determine if there is evidence that previously formed deposits might have been buried by plains units; (3) characterize the Tharsis plains morphologies east of Pavonis Mons; and (4) assess their relationship to the rift apron units. We have not identified topographically significant depositional fans, nor did we observe evidence to suggest that plains units have buried older rift apron units. Flow features associated with the rift apron are observed to continue across the slope break onto the plains. In this area, the plains are composed of a variety of small fissures and low shield vents around which broad channel-fed and tube-fed flows have been identified. We also find broad, flat-topped plateaus and sinuous ridges mixed among the channels, tubes and vents. Flat-topped plateaus and sinuous ridges are morphologies that are analogous to those observed on the coastal plain of Hawai'i, where lava flows have advanced from the volcano's several degree flank onto the nearly zero degree coastal plain. When local volumetric flow rates are low, flow fronts tend to spread laterally and often thicken via endogenous growth, or inflation, of the sheet-like flow units. If flow advance is restricted by existing topography into narrow pathways, inflation can be focused into sinuous, elongate ridges. The presence of plateaus and ridges-emplaced from the rift zones, across the plains to the east of Pavonis Mons-and a lack of fan-like features, or evidence for their burial, are consistent with rift apron lavas crossing a slope break with low local volumetric flow rates that led to inflation of sheet-like and tube-fed lava flows.

Bleacher, Jacob E.↗

NASA NTRS1997

Registration assisted mosaic generation

This paper presents a general strategy for assembling mosaics from numerous individual images where uncertainty exists in the position and orientation of those images. Both of the presented applications relate to remotely operated camera platforms, the first being the Galileo solid state imaging (SSI) camera presently in orbit around Jupiter, and the second being the Imager for Mars Pathfinder (IMP) stereo camera on Mars. A basic strategy in both applications is to determine the correct relative camera pointing followed by direct map projection of the images. It is assumed that approximate camera pointing exists sufficient to locate adjacent images and to place initial tiepoints within reach of the correlator. Spatial correlation is used to fix tiepoints whose initial locations are predicted by the camera pointing. We use either an fast fourier transform (fft) algorithm or a variant of Gruen's scheme permitting limited image rotation and skew. The Gruen correlator has three hierarchical modes: 1) A classical spatial least squares correlation on integral pixel boundaries used when rotation is small. 2) An annealing non-deterministic search used when rotations are unknown. A simplex deterministic search used for the end game. The correlation operation can be performed either interactively or autonomously. The final camera pointing solution relies upon a simplex downhill search in 2n or 3n dimensions where n is the number of images comprising the mosaic and the objective function to be minimized is the disagreement between tiepoint locations predicted from the camera pointing with those observed by the correlator. For Galileo the 3n unknowns are euler angles defining camera pointing in planet coordinates, and for Mars Pathfinder they are 2n unknowns representing commanded azimuth and elevation in the Lander coordinate system.

Lorre, Jean J.↗

DOE OSTI2018

Observing clouds in 4D with multi-view stereo photogrammetry

We report that newly installed stereo cameras ringing the Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site in Oklahoma are providing a 4D gridded view of shallow clouds. Six digital cameras have been installed in pairs at a distance of 6 kilometers from the site and with a spacing of 500 meters between cameras in a pair. These pairs of cameras provide stereoscopic views of shallow clouds from all sides; when these data are combined, they allow for a complete stereo reconstruction. The result – the Clouds Optically Gridded by Stereo (COGS) product – is a 4D grid of cloudiness covering a 6 km × 6 km × 6 km cube at a spatial resolution of 50 meters and a temporal resolution of 20 seconds. This provides an unprecedented set of data on the sizes, lifetimes, and lifecycles of shallow clouds. Lastly, this type of information is critical for developing cloud macrophysical schemes for the next generation of weather and climate models.

47 OTHER INSTRUMENTATION↗

NASA NTRS2022

Lunar Rover Localization Using Craters as Landmarks

Onboard localization capabilities for planetary rovers to date have used relative navigation, by integrating combinations of wheel odometry, visual odometry, and inertial measurements during each drive to track position relative to the start of each drive. At the end of each drive, a “ground-in-the-loop” (GITL) interaction is used to get a position update from human operators in a more global reference frame, such as a map frame defined by orbital reconnaissance imaging of a large region around the rover’s current position. For Mars rovers, this typically has involved downlinking imagery from the rover mast cameras and using interactive visualization tools on Earth to register such images to the orbital reconnaissance images. For safety purposes, rover mission operations typically specify “keep out zones”, which human operators recognize as being unsafe in the orbital images. Autonomous rover drives are limited in distance so that accumulated relative navigation error does not risk the possibility of the rover driving into a keep out zone. The allowable autonomous drive distance in this mode of operation depends on the distribution of keep out zones and the accuracy of relative navigation; in practice, drive limits of a few hundred meters between GITL cycles are to be expected. Several rover mission concepts have recently been studied that require much longer drives between GITL cycles, particularly for the Moon. This includes lunar rover mission concepts that involve (1) driving mostly in sunlight at low latitudes, (2) driving in permanently shadowed regions near the south pole, and (3) a mixture of day and night driving in mid-latitudes. These concepts include total traverse distance requirements of up to 1,800 km in 4 Earth years, with individual drives of several kilometers between stops for downlink. These concepts require greater autonomy to minimize GITL cycles to enable such large range; onboard global localization is a key element of such autonomy. Multiple techniques have been studied in the past for onboard rover global localization, including radio navigation aiding from an orbiter, recognizing horizon landmarks that are known in a regional elevation map, and correlating a local elevation map created onboard the rover with a regional elevation map. These techniques all have drawbacks, including requiring an expensive extra mission element (navigation orbiter), unavailability of sufficient regional elevation map data, or limited accuracy in resulting position estimates (e.g. a few hundred meters with horizon landmarks). For the Moon, the ubiquitous craters offer another possibility, which involves mapping craters from orbit, then recognizing crater landmarks with cameras and/or a lidar onboard the rover. This approach is applicable everywhere on the Moon, does not require high resolution stereo imaging from orbit as some other approaches do, and has potential to enable position knowledge with order of 10 m accuracy at all times. This paper will provide more detail on our technical approach to crater-based lunar rover localization and will present initial results on crater detection using 3-D point cloud data from onboard lidar or stereo cameras and using shading cues in monocular onboard imagery.

Ono, M.↗

NASA NTRSDate not supplied

Advances in Stereo Photogrammetry Capabilities for in-Situ Ejecta Measurements in Lunar Plume-Surface Interactions

Plume-surface interaction is a critical topic of interest as human spaceflight programs establish a renewed presence on the Moon and push onwards to Mars. The erosion of regolith and high-speed ejection of soil and rocks which occurs during a powered spacecraft landing on lunar or terrestrial bodies can pose serious risks to the vehicle during landing and to existing ground assets. Ground testing campaigns have provided data sets in relevant environments (e.g., low pressure) in tandem with predictive computational model validation. To-date, limited in-situ flight data exists to inform the study of the key phenomena of plume-surface interaction: plume-flow physics, soil erosion, and ejecta dynamics. In two upcoming lunar missions, erosion of the lunar regolith will be measured in-situ using the stereo photogrammetry technique as part of NASA’s Commercial Lunar Payload Services (CLPS) Program. The Stereo Cameras for Lunar Plume Surface Studies (SCALPSS) will use a multiple-camera system to measure the erosion of the lunar regolith due to the vehicles’ rocket engine plumes during descent and after landing. The application of stereo photogrammetry to accurately measure a realistic eroded shape has been validated in laboratory work ahead of the scheduled flights. In preparation for future CLPS, Artemis, or other lunar science missions, recent advancements have been made to measure the ejecta structure and particle dynamics in addition to the erosion of regolith using a SCALPSS-like photogrammetry system. The thickness and ejection angle of entrained soil and dust produced during plume-induced erosion can be used to determine how far debris will travel, and thus how it may impact nearby infrastructure or the landing vehicle itself. The present work highlights the development of this new flight instrumentation capability and its value to advancements in the plume-surface interaction measurement topic for lunar or planetary landings.

Olivia K. Tyrrell↗

NASA NTRS2017

Depth from Stereo and Polarization of Opaque Non-Lambertian Surfaces

This paper presents a new approach to depth from stereo in scenes with non-Lambertian surfaces. While these surfaces usually prove to be hard to incorporate in photo-consistency energy minimization, we retrieve additional information about their surface normals from applying a polarization-based approach that computes the degree and angle of polarization at each pixel. Therefore, we set up a stereo camera rig that captures four different rotations of a linear polarizer simultaneously for each camera. While most existing polarization-based approaches to shape reconstruction require a setup with known lighting, our approach uses arbitrary unpolarized illumination. We describe a regularization-based stereo approach that constrains specular surface normals in the scene to lie in the plane of their observed angle of polarization. We derive the mathematical foundations of this approach and present results on virtually generated stereo and real-world stereo imagery.

Berger, Kai↗

NASA NTRS2019

Astrobiology Survey of a Lava Cave at Lava Beds National Monument by a Rover Carrying a Remote Sensing Instrument Payload

We report here on a survey of a lava tube cave by a rover that is instrumented for astrobiology missions. The NASA Ames testbed rover, CaveR, was deployed in Valentine Cave in Lava Beds National Monument (N. CA, USA) during August of 2018. The rover carried an instrument package consisting of Near Infrared and Visible Spectrometer System (NIRVSS) a point spectrometer operating in 1590-3400 nm range, sensitive to H2O and -OH bearing minerals, pyroxenes, and carbonates (Roush, et al 2018); the bore sighted Drill Operations Camera (DOC), a monochrome imager illuminated by LEDs at 410, 540, 640, 740, 905 and 940 nm; a Realsense ™ depth sensor system for 3D model generation; and a high resolution DSLR stereo camera. The payload was mounted on a tiltable instrument platform attached to the left side of the rover. The rover was driven manually in the cave by field operators, following instructions from a remote science operations team, and simulating a mission concept with science-guided autonomy. A simulated mission took place for 3 days with a team of 3 scientists selecting targets and interpreting data from the payload. To begin the mission, the rover drove along one wall of the cave imaging continuously with the Realsense in 20 m cave segments, three total. At the start of each day, the images from a 20m segment and a panorama stitched from them were provided to the science team to examine. The science team used these data to prioritize specific points along the cave wall for the collection of NIRVSS, DOC, and DSLR data. The objective of the data collection was to identify and study putative biological and mineralogical features in the cave. The data were delivered in xGDS, a customized mapping, planning, and data base management software developed at NASA Ames (Lee, et al 2013). Once the targets for further observations were selected, a plan for collecting the observations (positions in the cave and pointing for each requested observation) was constructed using xGDS and delivered to a rover team to execute the science data collection plan. Acquired data were delivered back to the science team for analysis. Preliminary results from the experiment illustrate the utility of the system (rover plus payload) to study the cave geology and mineralogy and its potential for identifying biomineral features.

Wong, Uland↗

NASA NTRSDate not supplied

Development of a Terrain Mapping/Crater Evolution Measurement using Diffractive Optical Elements

When landing on the moon, understanding the interaction of the engine exhaust plume with the lunar surface is critical for the success of the descent and landing flight phases. Two evaluation tools currently used are computational simulations and ground test measurements. Computational simulations require experimental measurements for comparison/validation, but ground test measurements cannot accurately emulate all aspects of an actual lunar landing; flight tests remain the only method of obtaining fully representative data. A terrain mapping/crater evolution measurement system was developed for potential inclusion on a future lander mission. This system uses two stereo cameras viewing a laser dot grid pattern projected on the ground, where the grid is created by shining a laser through one or two diffractive optical elements. CAD simulations of the stereo imaging system are first used to validate the proposed design. Laboratory testing of the system using both a large-scale fixed-geometry crater and a small-scale evolving-geometry crater validate the use of the system for terrain mapping measurements, and for its potential inclusion on a future lander mission.

Joshua M Weisberger↗

NASA NTRSDate not supplied

Development of a Terrain Mapping/Crater Evolution Measurement using Diffractive Optical Elements

When landing on the moon, understanding the interaction of the engine exhaust plume with the lunar surface is critical for the success of the descent and landing flight phases. Two evaluation tools currently used are computational simulations and ground test measurements. Computational simulations require experimental measurements for comparison/validation, but ground test measurements cannot accurately emulate all aspects of an actual lunar landing; flight tests remain the only method of obtaining fully representative data. A terrain mapping/crater evolution measurement system was developed for potential inclusion on a future lander mission. This system uses two stereo cameras viewing a laser dot grid pattern projected on the ground, where the grid is created by shining a laser through one or two diffractive optical elements. CAD simulations of the stereo imaging system are first used to validate the proposed design. Laboratory testing of the system using both a large-scale fixed-geometry crater and a small-scale evolving-geometry crater validate the use of the system for terrain mapping measurements. High-speed, front-illumination shadow particle tracking of particles ejected from the evolving geometry crater is also performed, demonstrating another diagnostic that can be used to further the understanding of plume-surface interactions.

Joshua M Weisberger↗

NASA NTRSDate not supplied

Applications and Development Work for Digital Image Correlation Using High Speed Cameras

NASA, Army, and industry partners are working to advance optical measurement techniques used in highly dynamic rocket engine and missile test environments. This allows for direct component data collection during test and flight environments, significantly reduced analysis time, and associated cost savings. Digital Image Correlation (DIC) uses calibrated stereo cameras to collect three-dimensional (3-D) displacements, strains, and acceleration data by referencing a stochastic speckle pattern applied to the test object. These optical measurement techniques provide significantly improved data resulting in better performance predictions, model validation, and information about components during hot-fire tests and test flights.

Rachel Paden↗