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At least 19 records

Robot vision.

The work reported had been undertaken to develop hardware that would guide an automatic vehicle in the exploration of the surface of Mars, recognize objects, and report the findings to earth. Approaches for automatically determining the range and shape of objects are discussed, giving attention to the automatic comparison of one scan line of the left with one scan line of the right TV image. Methods of mapping binocular space into match space are considered together with the use of a model in match space, rules for processing random-dot stereograms, the elimination of spurious matches, random-square stereograms, questions of the processing of a real scene, and aspects of range accuracy. Methods of computation for extracting other features are also discussed along with stereo TV cameras and approaches for reconstructing the appearance of a scene.

Sutro, L. L.↗

Dig Hazard Assessment Using a Stereo Pair of Cameras

This software evaluates the terrain within reach of a lander s robotic arm for dig hazards using a stereo pair of cameras that are part of the lander s sensor system. A relative level of risk is calculated for a set of dig sectors. There are two versions of this software; one is designed to run onboard a lander as part of the flight software, and the other runs on a PC under Linux as a ground tool that produces the same results generated on the lander, given stereo images acquired by the lander and downlinked to Earth. Onboard dig hazard assessment is accomplished by executing a workspace panorama command sequence. This sequence acquires a set of stereo pairs of images of the terrain the arm can reach, generates a set of candidate dig sectors, and assesses the dig hazard of each candidate dig sector. The 3D perimeter points of candidate dig sectors are generated using configurable parameters. A 3D reconstruction of the terrain in front of the lander is generated using a set of stereo images acquired from the mast cameras. The 3D reconstruction is used to evaluate the dig goodness of each candidate dig sector based on a set of eight metrics. The eight metrics are: 1. The maximum change in elevation in each sector, 2. The elevation standard deviation in each sector, 3. The forward tilt of each sector with respect to the payload frame, 4. The side tilt of each sector with respect to the payload frame, 5. The maximum size of missing data regions in each sector, 6. The percentage of a sector that has missing data, 7. The roughness of each sector, and 8. Monochrome intensity standard deviation of each sector. Each of the eight metrics forms a goodness image layer where the goodness value of each sector ranges from 0 to 1. Goodness values of 0 and 1 correspond to high and low risk, respectively. For each dig sector, the eight goodness values are merged by selecting the lowest one. Including the merged goodness image layer, there are nine goodness image layers for each stereo pair of mast images.

Rankin, Arturo L.↗

Systematic Errors in Stereo PIV When Imaging through a Glass Window

This document assesses the magnitude of velocity measurement errors that may arise when performing stereo particle image velocimetry (PIV) with cameras viewing through thick, refractive window and where the calibration is performed in one plane only. The effect of the window is to introduce a refractive error that increases with window thickness and the camera angle of incidence. The calibration should be performed while viewing through the test section window, otherwise a potentially significant error may be introduced that affects each velocity component differently. However, even when the calibration is performed correctly, another error may arise during the stereo reconstruction if the perspective angle determined for each camera does not account for the displacement of the light rays as they refract through the thick window. Care should be exercised when applying in a single-plane calibration since certain implicit assumptions may in fact require conditions that are extremely difficult to meet in a practical laboratory environment. It is suggested that the effort expended to ensure this accuracy may be better expended in performing a more lengthy volumetric calibration procedure, which does not rely upon the assumptions implicit in the single plane method and avoids the need for the perspective angle to be calculated.

Green, Richard↗

Moments applied in the manual assembly of space structures - Ease biomechanics results from STS-61B

Measurements of the level and pattern of moments applied in the manual assembly of a space structure were made in extravehicular activity (EVA) and neutral buoyancy simulation (NBS). The Experimental Assembly of Structures in EVA program included the repeated assembly of a 3.6 m tetrahedral truss structure in EVA on STS-61B after extensive neutral buoyancy crew training. The flight and training structures were of equivalent mass and geometry to allow a direct correlation between EVA and NBS performance. A stereo photographic motion camera system was used to reconstruct in three dimensions rotational movements of structural beams during assembly. Moments applied in these manual handling tasks were calculated on the basis of the reconstructed movements taking into account effects of inertia, drag and virtual mass. Applied moments of 2.0 Nm were typical for beam rotations in EVA. Corresponding applied moments in NBS were typically up to five times greater. Moments were applied as impulses separated by several seconds of coasting in both EVA and NBS. Decelerating impulses were only infrequently observed in NBS.

Cousins, D.↗

Lensless Particle Image Velocimetry

The application of lensless imaging to particle image velocimetry (PIV) is demonstrated. Lensless PIV eliminates the need for imaging lenses to measure flow fields near a surface. Only the camera sensor, a thin mask, and computations are required to image particles in a flow field and to compute the velocity field. The small form factor could enable embedded sensors for near-wall measurements. Flow field measurements are obtained simultaneously for a lensless system and lens-based 2D PIV system, and several different reconstruction techniques are demonstrated. The reconstructed particle images and computed velocity fields compare well for both a uniform and shear flow. The potential for stereo and 3D volumetric PIV with a single camera sensor is demonstrated through different image reconstruction approaches.

Lensless imaging↗

Orthographic Stereo Correlator on the Terrain Model for Apollo Metric Images

A stereo correlation method on the object domain is proposed to generate the accurate and dense Digital Elevation Models (DEMs) from lunar orbital imagery. The NASA Ames Intelligent Robotics Group (IRG) aims to produce high-quality terrain reconstructions of the Moon from Apollo Metric Camera (AMC) data. In particular, IRG makes use of a stereo vision process, the Ames Stereo Pipeline (ASP), to automatically generate DEMs from consecutive AMC image pairs. Given camera parameters of an image pair from bundle adjustment in ASP, a correlation window is defined on the terrain with the predefined surface normal of a post rather than image domain. The squared error of back-projected images on the local terrain is minimized with respect to the post elevation. This single dimensional optimization is solved efficiently and improves the accuracy of the elevation estimate.

Terrain Model↗

(Almost) Featureless Stereo: Calibration and Dense 3D Reconstruction Using Whole Image Operations

The conventional approach to shape from stereo is via feature extraction and correspondences. This results in estimates of the camera parameters and a typically spare estimate of the surface. Given a set of calibrated images, a dense surface reconstruction is possible by minimizing the error between the observed image and the image rendered from the estimated surface with respect to the surface model parameters. Given an uncalibrated image and an estimated surface, the camera parameters can be estimated by minimizing the error between the observed and rendered images a function of the camera parameters. We use a very small dense set of matched features to provide camera parameter estimates for the initial dense surface estimate. We then re-estimate the camera parameters as described above, and then re-estimate the surface. This process is iterated. Whilst it can not be proven to converge, we have found that around three iterations results in excellent surface and camera parameters estimates.

Smelyanskiy, V. N.↗

Dense 3D-Reconstruction from Monocular Image Sequences for Computationally Constrained UAS

The ability to find safe landing sites over complex 3D terrain is an essential safety feature for fully autonomous small unmanned aerial systems (UAS), which requires on-board perception for 3D reconstruction and terrain analysis if the overflown terrain is unknown. This is a challenge for UAS that are limited in size, weight and computational power, such as small rotorcrafts executing autonomous missions on Earth, or in planetary applications such as the Mars Helicopter. For such a computationally constraint system, we propose a structure from motion approach that uses inputs from a single downward facing camera to produce dense point clouds of the overflown terrain in real time. In contrast to existing approaches, our method uses metric pose information from a visual-inertial odometry algorithm as camera pose priors, which allows deploying a fast pose refinement step to align camera frames such that a conventional stereo algorithm can be used for dense 3D reconstruction. We validate the performance of our approach with extensive evaluations in simulation, and demonstrate the feasibility with data from UAS flights.

Brockers, Roland↗

Three Dimensional Instantaneous Spray Measurements of Additively Manufactured Candidate Injector Schemes at Varying Pressure Drops

Additively manufactured (AM) injectors have the potential to improve upon the combustion performance achieved using traditionally manufactured (TM) injectors. Traditionally manufactured injector combustion performance decreases greatly in off-design conditions. Additively manufactured injectors hold the potential to sustain high combustion performance over a broader range of operating conditions than currently seen in TM injectors. Additively manufactured injectors promise to offer higher resistances to instability and achieve better overall propellant mixing and atomization for all types of combustion devices. This study expands upon previous studies that used 2-D imaging techniques to characterize the injector spray pattern of candidate AM injector elements. In this study, 3-D instantaneous measurements of the injector spray pattern are taken, allowing for deeper insight into the liquid spray breakup, an inherently 3-D phenomena. Stereo imaging is used for three dimensional analysis, which utilizes two cameras at different angles to reconstruct a three dimensional reconstruction. With this information, AM injectors can be designed to improve propellant mixing and atomization and reduce breakup length. As part of this work, a high-pressure, cold flow experimental spray facility was modified to measure each injector’s spray characteristics in terms of 𝑅𝑒 𝐿 and 𝑊𝑒 𝑔 . This facility is operated to capture instantaneous stereo photographic images, mass flow rates, and injector element thrust for pressure drop across the injector face ranging from 100 to 200 psig at a stiffness ratio of 1.0.

Murphy Mitchell↗

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↗

Robust Mosaicking of Stereo Digital Elevation Models from the Ames Stereo Pipeline

Robust estimation method is proposed to combine multiple observations and create consistent, accurate, dense Digital Elevation Models (DEMs) from lunar orbital imagery. The NASA Ames Intelligent Robotics Group (IRG) aims to produce higher-quality terrain reconstructions of the Moon from Apollo Metric Camera (AMC) data than is currently possible. In particular, IRG makes use of a stereo vision process, the Ames Stereo Pipeline (ASP), to automatically generate DEMs from consecutive AMC image pairs. However, the DEMs currently produced by the ASP often contain errors and inconsistencies due to image noise, shadows, etc. The proposed method addresses this problem by making use of multiple observations and by considering their goodness of fit to improve both the accuracy and robustness of the estimate. The stepwise regression method is applied to estimate the relaxed weight of each observation.

Kim, Tae Min↗

The Ames MER Microscopic Imager Toolkit

The Mars Exploration Rovers, Spirit and Opportunity, have spent several successful months on Mars, returning gigabytes of images and spectral data to scientists on Earth. One of the instruments on the MER rovers, the Athena Microscopic Imager (MI), is a fixed focus, megapixel camera providing a plus or minus mm depth of field and a 3lx31mm field of view at a working distance of 63 mm from the lens to the object being imaged. In order to maximize the science return from this instrument, we developed the Ames MI Toolkit and supported its use during the primary mission. The MI Toolkit is a set of programs that operate on collections of MI images, with the goal of making the data more understandable to the scientists on the ground. Because of the limited depth of field of the camera, and the often highly variable topography of the terrain being imaged, MI images of a given rock are often taken as a stack, with the Instrument Deployment Device (IDD) moving along a computed normal vector, pausing every few millimeters for the MI to acquire an image. The MI Toolkit provides image registration and focal section merging, which combine these images to form a single, maximally in-focus image, while compensating for changes in lighting as well as parallax due to the motion of the camera. The MI Toolkit also provides a 3-D reconstruction of the surface being imaged using stereo and can embed 2-D MI images as texture maps into 3-D meshes produced by other imagers on board the rover to provide context. The 2-D images and 3-D meshes output from the Toolkit are easily viewed by scientists using other mission tools, such as Viz or the MI Browser. This paper describes the MI Toolkit in detail, as well as our experience using it with scientists at JPL during the primary MER mission.

Sargent, Randy↗

New Geologic Map of the Scandia Region of Mars

We have begun work on a sophisti-cated digital geologic map of the Scandia region (Fig. 1) at 1:3,000,000 scale based on post-Viking image and to-pographic datasets. Through application of GIS tools, we will produce a map product that will consist of (1) a printed photogeologic map displaying geologic units and relevant modificational landforms produced by tectonism, erosion, and collapse/mass wasting; (2) a landform geoda-tabase including sublayers of key landform types, attributed with direct measurements of their planform and to-pography using Mars Orbiter Laser Altimeter (MOLA) altimetry data and High-Resolution Stereo Camera (HRSC) digital elevation models (DEMs) and various image datasets; and (3) a series of digital, reconstructed paleostratigraphic and paleotopographic maps showing the inferred distribution and topographic form of materi-als and features during past ages

Tanaka, K. L.↗

Surface Reconstruction of a Challenging Region with Permanent Shadows on the Moon

As the Earth is orbiting the Sun, there is the region a sunlight can't be reached on the Moon, a satellite of the Earth. Usually, the permanent shadows are located near a pole area and the surface reconstruction in the permanent shadows region is challenging because of the lack of sunlight.In this research, the reconstruction method containing the permanent shadows is suggested. To apply this method, the time-varying shadow region and a permanently shadowed region are needed to be separated. In the time-varying shadow region, the pixel intensity of the image can be composed of the albedo and the reflectance model. Using the light source direction from ISIS3 of USGS, the shape of the region can be extracted from the reflectance model. Though this region is visible in the camera, the change of illumination is quite large in this region, it is hard to reconstruct the shape using stereo-photogrammetry or SfS. So, it is needed of collecting more surface normal information from several pixel level-aligned images. In this process, the albedo information can be initialized and enhanced easily from many images.In the middle of permanent shadows, the high-resolution DEM is generated by LOLA DEM. The LOLA DEM is generated by interpolation between measured data point strips, the actual scene of the permanent shadows. Using the sensor like DIVINER, the Imaginary scene generation via a trained network between the sunlight sensor and other kinds of a sensor is suggested.

Moon, Sunghyun↗

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↗

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↗

Dramatic Improvements to Feature Based Stereo

The camera registration extracted from feature based stereo is usually considered sufficient to accurately localize the 3D points. However, for natural scenes the feature localization is not as precise as in man-made environments. This results in small camera registration errors. We show that even very small registration errors result in large errors in dense surface reconstruction. We describe a method for registering entire images to the inaccurate surface model. This gives small, but crucially important improvements to the camera parameters. The new registration gives dramatically better dense surface reconstruction.

Smelyansky, V. N.↗

Image Compression Algorithm Altered to Improve Stereo Ranging

A report discusses a modification of the ICER image-data-compression algorithm to increase the accuracy of ranging computations performed on compressed stereoscopic image pairs captured by cameras aboard the Mars Exploration Rovers. (ICER and variants thereof were discussed in several prior NASA Tech Briefs articles.) Like many image compressors, ICER was designed to minimize a mean-square-error measure of distortion in reconstructed images as a function of the compressed data volume. The present modification of ICER was preceded by formulation of an alternative error measure, an image-quality metric that focuses on stereoscopic-ranging quality and takes account of image-processing steps in the stereoscopic-ranging process. This metric was used in empirical evaluation of bit planes of wavelet-transform subbands that are generated in ICER. The present modification, which is a change in a bit-plane prioritization rule in ICER, was adopted on the basis of this evaluation. This modification changes the order in which image data are encoded, such that when ICER is used for lossy compression, better stereoscopic-ranging results are obtained as a function of the compressed data volume.

Kiely, Aaron↗