Search NASA⌕ Search

SEARCH · Search NASA

Results for “camera”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Situational Awareness from a Low-Cost Camera System

A method gathers scene information from a low-cost camera system. Existing surveillance systems using sufficient cameras for continuous coverage of a large field necessarily generate enormous amounts of raw data. Digitizing and channeling that data to a central computer and processing it in real time is difficult when using low-cost, commercially available components. A newly developed system is located on a combined power and data wire to form a string-of-lights camera system. Each camera is accessible through this network interface using standard TCP/IP networking protocols. The cameras more closely resemble cell-phone cameras than traditional security camera systems. Processing capabilities are built directly onto the camera backplane, which helps maintain a low cost. The low power requirements of each camera allow the creation of a single imaging system comprising over 100 cameras. Each camera has built-in processing capabilities to detect events and cooperatively share this information with neighboring cameras. The location of the event is reported to the host computer in Cartesian coordinates computed from data correlation across multiple cameras. In this way, events in the field of view can present low-bandwidth information to the host rather than high-bandwidth bitmap data constantly being generated by the cameras. This approach offers greater flexibility than conventional systems, without compromising performance through using many small, low-cost cameras with overlapping fields of view. This means significant increased viewing without ignoring surveillance areas, which can occur when pan, tilt, and zoom cameras look away. Additionally, due to the sharing of a single cable for power and data, the installation costs are lower. The technology is targeted toward 3D scene extraction and automatic target tracking for military and commercial applications. Security systems and environmental/ vehicular monitoring systems are also potential applications.

Freudinger, Lawrence C.↗
NASA NTRS2008

Measuring Positions of Objects using Two or More Cameras

An improved method of computing positions of objects from digitized images acquired by two or more cameras (see figure) has been developed for use in tracking debris shed by a spacecraft during and shortly after launch. The method is also readily adaptable to such applications as (1) tracking moving and possibly interacting objects in other settings in order to determine causes of accidents and (2) measuring positions of stationary objects, as in surveying. Images acquired by cameras fixed to the ground and/or cameras mounted on tracking telescopes can be used in this method. In this method, processing of image data starts with creation of detailed computer- aided design (CAD) models of the objects to be tracked. By rotating, translating, resizing, and overlaying the models with digitized camera images, parameters that characterize the position and orientation of the camera can be determined. The final position error depends on how well the centroids of the objects in the images are measured; how accurately the centroids are interpolated for synchronization of cameras; and how effectively matches are made to determine rotation, scaling, and translation parameters. The method involves use of the perspective camera model (also denoted the point camera model), which is one of several mathematical models developed over the years to represent the relationships between external coordinates of objects and the coordinates of the objects as they appear on the image plane in a camera. The method also involves extensive use of the affine camera model, in which the distance from the camera to an object (or to a small feature on an object) is assumed to be much greater than the size of the object (or feature), resulting in a truly two-dimensional image. The affine camera model does not require advance knowledge of the positions and orientations of the cameras. This is because ultimately, positions and orientations of the cameras and of all objects are computed in a coordinate system attached to one object as defined in its CAD model.

Klinko, Steve↗
NASA NTRS2016

Geocam Space: Enhancing Handheld Digital Camera Imagery from the International Space Station for Research and Applications

Handheld astronaut photography of the Earth has been collected from the International Space Station (ISS) since 2000, making it the most temporally extensive remotely sensed dataset from this unique Low Earth orbital platform. Exclusive use of digital handheld cameras to perform Earth observations from the ISS began in 2004. Nadir viewing imagery is constrained by the inclined equatorial orbit of the ISS to between 51.6 degrees North and South latitude, however numerous oblique images of land surfaces above these latitudes are included in the dataset. While unmodified commercial off-the-shelf digital cameras provide only visible wavelength, three-band spectral information of limited quality current cameras used with long (400+ mm) lenses can obtain high quality spatial information approaching 2 meters/ground pixel resolution. The dataset is freely available online at the Gateway to Astronaut Photography of Earth site (http://eol.jsc.nasa.gov), and now comprises over 2 million images. Despite this extensive image catalog, use of the data for scientific research, disaster response, commercial applications and visualizations is minimal in comparison to other data collected from free-flying satellite platforms such as Landsat, Worldview, etc. This is due primarily to the lack of fully-georeferenced data products - while current digital cameras typically have integrated GPS, this does not function in the Low Earth Orbit environment. The Earth Science and Remote Sensing (ESRS) Unit at NASA Johnson Space Center provides training in Earth Science topics to ISS crews, performs daily operations and Earth observation target delivery to crews through the Crew Earth Observations (CEO) Facility on board ISS, and also catalogs digital handheld imagery acquired from orbit by manually adding descriptive metadata and determining an image geographic centerpoint using visual feature matching with other georeferenced data, e.g. Landsat, Google Earth, etc. The lack of full geolocation information native to the data makes it difficult to integrate astronaut photographs with other georeferenced data to facilitate quantitative analysis such as urban land cover/land use classification, change detection, or geologic mapping. The manual determination of image centerpoints is both time and labor-intensive, leading to delays in releasing geolocated and cataloged data to the public, such as the timely use of data for disaster response. The GeoCam Space project was funded by the ISS Program in 2015 to develop an on-orbit hardware and ground-based software system for increasing the efficiency of geolocating astronaut photographs from the ISS (Fig. 1). The Intelligent Robotics Group at NASA Ames Research Center leads the development of both the ground and on-orbit systems in collaboration with the ESRS Unit. The hardware component consists of modified smartphone elements including cameras, central processing unit, wireless Ethernet, and an inertial measurement unit (gyroscopes/accelerometers/magnetometers) reconfigured into a compact unit that attaches to the base of the current Nikon D4 camera - and its replacement, the Nikon D5 - and connects using the standard Nikon peripheral connector or USB port. This provides secondary, side and downward facing cameras perpendicular to the primary camera pointing direction. The secondary cameras observe calibration targets with known internal X, Y, and Z position affixed to the interior of the ISS to determine the camera pose corresponding to each image frame. This information is recorded by the GeoCam Space unit and indexed for correlation to the camera time recorded for each image frame. Data - image, EXIF header, and camera pose information - is transmitted to the ground software system (GeoRef) using the established Ku-band USOS downlink system. Following integration on the ground, the camera pose information provides an initial geolocation estimate for the individual film frame. This new capability represents a significant advance in geolocation from the manual feature-matching approach for both nadir and off-nadir viewing imagery. With the initial geolocation estimate, full georeferencing of an image is completed using the rapid tie-pointing interface in GeoRef, and the resulting data is added to the Gateway to Astronaut Photography of Earth online database in both Geotiff and Keyhole Markup Language (kml) formats. The integration of the GeoRef software component of Geocam Space into the CEO image cataloging workflow is complete, and disaster response imagery acquired by the ISS crew is now fully georeferenced as a standard data product. The on-orbit hardware component (GeoSens) is in final prototyping phase, and is on-schedule for launch to the ISS in late 2016. Installation and routine use of the Geocam Space system for handheld digital camera photography from the ISS is expected to significantly improve the usefulness of this unique dataset for a variety of public- and private-sector applications.

Stefanov, William L.↗
NASA NTRSDate not supplied

Camera Calibration and Alignment Metrology at Johnson Space Center’s Electro-Optics Laboratory

It is increasingly common to see spacecraft equipped with cameras for the purpose of navigation. Images are either sent to Earth or processed autonomously on-board to provide information about the vehicle’s position, velocity, and/or attitude. These can be images of stars or celestial bodies for absolute navigation, or images of another spacecraft for relative navigation. While monocular cameras do not provide range information, the images they capture can be processed to determine bearing vectors to target objects within the camera’s field of view. For a camera to be effective in navigation, it must be carefully calibrated and aligned. This involves accurately modeling the optical effects that govern the projection of line-of-sight directions onto the camera’s pixels and determining the camera’s orientation relative to the spacecraft’s reference frame. Engineers at Johnson Space Center’s Electro-Optics Lab regularly perform camera inspection, calibration, and alignment metrology. This was done for the Orion Optical Navigation (OpNav) Camera, the Orion Docking Camera (DCAM), and for numerous cameras belonging to commercial partners. The nature of optical navigation means that cameras must be well-calibrated and their attitude well understood to provide high accuracy bearing measurements to the navigation filter. The stringent accuracy requirements for Orion could not have been met using traditional checkerboard camera calibration or by simply relying on design drawings. This paper details the hardware, software, techniques, and algorithms used by the EOL team to achieve this level of accuracy.

Paul D Mckee↗
NASA NTRSDate not supplied

Camera Calibration and Alignment Metrology at Johnson Space Center’s Electro-Optics Laboratory

It is increasingly common to see spacecraft equipped with cameras for the purpose of navigation. Images are either sent to Earth or processed autonomously on-board to provide information about the vehicle’s position, velocity, and/or attitude. These can be images of stars or celestial bodies for absolute navigation, or images of another spacecraft for relative navigation. While monocular cameras do not provide range information, the images they capture can be processed to determine bearing vectors to target objects within the camera’s field of view. For a camera to be effective in navigation, it must be carefully calibrated and aligned. This involves accurately modeling the optical effects that govern the projection of line-of-sight directions onto the camera’s pixels and determining the camera’s orientation relative to the spacecraft’s reference frame. Engineers at Johnson Space Center’s Electro-Optics Lab regularly perform camera inspection, calibration, and alignment metrology. This was done for the Orion Optical Navigation (OpNav) Camera, the Orion Docking Camera (DCAM), and for numerous cameras belonging to commercial partners. The nature of optical navigation means that cameras must be well-calibrated and their attitude well understood to provide high accuracy bearing measurements to the navigation filter. The stringent accuracy requirements for Orion could not have been met using traditional checkerboard camera calibration or by simply relying on design drawings. This paper details the hardware, software, techniques, and algorithms used by the EOL team to achieve this level of accuracy.

Paul McKee↗
DOE OSTI2024

Raccoon density estimation from camera traps for raccoon rabies management

Abstract Density estimation for unmarked animals is particularly challenging, yet density estimates are often necessary for effective wildlife management. Raccoons ( Procyon lotor ) are the primary terrestrial wildlife reservoir for Lyssavirus rabies within the United States. The raccoon rabies variant (RRVV) is actively managed at landscape scales using oral rabies vaccination (ORV) within the eastern United States. To effectively manage RRVV, it is important to know the density of raccoons to appropriately scale the density of ORV baits distributed on the landscape. We compared methods to estimate raccoon densities from camera‐trap data versus more intensive capture‐mark‐recapture (CMR) estimates across 2 land cover types (upland pine and bottomland hardwood) in the southeastern United States during 2019 and 2020. We evaluated the effect of alternative camera configurations and durations of camera trapping on density estimates and used an N‐mixture model to estimate raccoon densities, including covariates on abundance and detection. We further compared different methods of scaling camera‐based counts, with the maximum number of raccoons seen on any given image within a day best explaining density. Camera‐trap density estimates were moderately correlated with CMR estimates ( r = 0.56). However, densities from camera‐trap data were more reliable when classifying category of density as an index used to inform management (83% correct when compared to CMR estimates), although the densities in our study fell into the 2 lowest density classes only. Using more cameras reduced bias and uncertainty around density estimates; however, if ≤6 camera traps were used at a site, a line transect approach proved less biased than a grid design. Camera trapping should be conducted for at least 3 weeks for more accurate estimates of raccoon population density in our study area (<5% bias). We show that camera‐trap data can be used to assign raccoon densities to management‐relevant density index bins, but more studies are needed to ensure reliability across a greater range of environmental conditions and raccoon densities.

Davis, Amy J.↗
NASA NTRS2008

Deployable Wireless Camera Penetrators

A lightweight, low-power camera dart has been designed and tested for context imaging of sampling sites and ground surveys from an aerobot or an orbiting spacecraft in a microgravity environment. The camera penetrators also can be used to image any line-of-sight surface, such as cliff walls, that is difficult to access. Tethered cameras to inspect the surfaces of planetary bodies use both power and signal transmission lines to operate. A tether adds the possibility of inadvertently anchoring the aerobot, and requires some form of station-keeping capability of the aerobot if extended examination time is required. The new camera penetrators are deployed without a tether, weigh less than 30 grams, and are disposable. They are designed to drop from any altitude with the boost in transmitting power currently demonstrated at approximately 100-m line-of-sight. The penetrators also can be deployed to monitor lander or rover operations from a distance, and can be used for surface surveys or for context information gathering from a touch-and-go sampling site. Thanks to wireless operation, the complexity of the sampling or survey mechanisms may be reduced. The penetrators may be battery powered for short-duration missions, or have solar panels for longer or intermittent duration missions. The imaging device is embedded in the penetrator, which is dropped or projected at the surface of a study site at 90 to the surface. Mirrors can be used in the design to image the ground or the horizon. Some of the camera features were tested using commercial "nanny" or "spy" camera components with the charge-coupled device (CCD) looking at a direction parallel to the ground. Figure 1 shows components of one camera that weighs less than 8 g and occupies a volume of 11 cm3. This camera could transmit a standard television signal, including sound, up to 100 m. Figure 2 shows the CAD models of a version of the penetrator. A low-volume array of such penetrator cameras could be deployed from an aerobot or a spacecraft onto a comet or asteroid. A system of 20 of these penetrators could be designed and built in a 1- to 2-kg mass envelope. Possible future modifications of the camera penetrators, such as the addition of a chemical spray device, would allow the study of simple chemical reactions of reagents sprayed at the landing site and looking at the color changes. Zoom lenses also could be added for future use.

Badescu, Mircea↗
NASA NTRS2009

System Synchronizes Recordings from Separated Video Cameras

A system of electronic hardware and software for synchronizing recordings from multiple, physically separated video cameras is being developed, primarily for use in multiple-look-angle video production. The system, the time code used in the system, and the underlying method of synchronization upon which the design of the system is based are denoted generally by the term "Geo-TimeCode(TradeMark)." The system is embodied mostly in compact, lightweight, portable units (see figure) denoted video time-code units (VTUs) - one VTU for each video camera. The system is scalable in that any number of camera recordings can be synchronized. The estimated retail price per unit would be about $350 (in 2006 dollars). The need for this or another synchronization system external to video cameras arises because most video cameras do not include internal means for maintaining synchronization with other video cameras. Unlike prior video-camera-synchronization systems, this system does not depend on continuous cable or radio links between cameras (however, it does depend on occasional cable links lasting a few seconds). Also, whereas the time codes used in prior video-camera-synchronization systems typically repeat after 24 hours, the time code used in this system does not repeat for slightly more than 136 years; hence, this system is much better suited for long-term deployment of multiple cameras.

Nail, William↗
NASA NTRS2011

Unmanned Ground Vehicle Perception Using Thermal Infrared Cameras

The ability to perform off-road autonomous navigation at any time of day or night is a requirement for some unmanned ground vehicle (UGV) programs. Because there are times when it is desirable for military UGVs to operate without emitting strong, detectable electromagnetic signals, a passive only terrain perception mode of operation is also often a requirement. Thermal infrared (TIR) cameras can be used to provide day and night passive terrain perception. TIR cameras have a detector sensitive to either mid-wave infrared (MWIR) radiation (3-5?m) or long-wave infrared (LWIR) radiation (8-12?m). With the recent emergence of high-quality uncooled LWIR cameras, TIR cameras have become viable passive perception options for some UGV programs. The Jet Propulsion Laboratory (JPL) has used a stereo pair of TIR cameras under several UGV programs to perform stereo ranging, terrain mapping, tree-trunk detection, pedestrian detection, negative obstacle detection, and water detection based on object reflections. In addition, we have evaluated stereo range data at a variety of UGV speeds, evaluated dual-band TIR classification of soil, vegetation, and rock terrain types, analyzed 24 hour water and 12 hour mud TIR imagery, and analyzed TIR imagery for hazard detection through smoke. Since TIR cameras do not currently provide the resolution available from megapixel color cameras, a UGV's daytime safe speed is often reduced when using TIR instead of color cameras. In this paper, we summarize the UGV terrain perception work JPL has performed with TIR cameras over the last decade and describe a calibration target developed by General Dynamics Robotic Systems (GDRS) for TIR cameras and other sensors.

terrain classification↗
NASA NTRS2012

Mars Science Laboratory Engineering Cameras

NASA's Mars Science Laboratory (MSL) Rover, which launched to Mars in 2011, is equipped with a set of 12 engineering cameras. These cameras are build-to-print copies of the Mars Exploration Rover (MER) cameras, which were sent to Mars in 2003. The engineering cameras weigh less than 300 grams each and use less than 3 W of power. Images returned from the engineering cameras are used to navigate the rover on the Martian surface, deploy the rover robotic arm, and ingest samples into the rover sample processing system. The navigation cameras (Navcams) are mounted to a pan/tilt mast and have a 45-degree square field of view (FOV) with a pixel scale of 0.82 mrad/pixel. The hazard avoidance cameras (Haz - cams) are body-mounted to the rover chassis in the front and rear of the vehicle and have a 124-degree square FOV with a pixel scale of 2.1 mrad/pixel. All of the cameras utilize a frame-transfer CCD (charge-coupled device) with a 1024x1024 imaging region and red/near IR bandpass filters centered at 650 nm. The MSL engineering cameras are grouped into two sets of six: one set of cameras is connected to rover computer A and the other set is connected to rover computer B. The MSL rover carries 8 Hazcams and 4 Navcams.

Maki, Justin N.↗
NASA NTRS2018

On-Ground Calibration and Optical Alignment for the Orion Optical Navigation Camera

The Orion Multi-Purpose Crew Vehicle on-board Navigation System will utilize the Optical Navigation measurements of the Moon and Earth during cis-lunar operations. Misalignment or an un-calibrated optical navigation camera may cause large measurement residuals in any on-board attitude determination and navigation system. Therefore, a novel estimation technique to calibrate the internal camera parameters, and a high accuracy optical alignment procedure to estimate the external camera alignment are introduced in this paper. The intrinsic camera parameters such as the focal length, the principle point offsets, and the camera lens distortion parameters will be estimated and evaluated using images of star fields. This calibration estimation technique can be used either on-ground or in flight. The proposed technique in this paper is using the discrepancy between imaged star vectors attained from the OpNav camera, and the matched star vectors from the star catalog to determine the changes in internal camera parameters. This gave rise to the two basic types of calibration the attitude dependent and attitude independent methods. The former utilizes the errors in imaged and cataloged vectors themselves, and the latter using the discrepancy in angles between pairs of vectors from the camera and catalog. The alignment procedure is carried out using Theodolite autocollimator measurements taken off alignment cubes mounted on the Orion frame and also the measurements from the OpNav focal plane. It is assumed that the alignment cubes and OpNav camera are rigidly mounted to the frame so that flexing effects do not significantly alter the orientation of the cubes relative to the OpNav camera.

Samaan, Malak↗
DOE OSTI2025

Radiation Imaging with Event Camera

Neuromorphic or event-based imaging is a new, commercially available sensor technology inspired by how the human eye works. Instead of measuring frames at a fixed rate, the camera measures changes in pixel intensity asynchronously. This difference in readout architecture results in a high dynamic range and low latency. Event-based cameras have been used in a variety of applications, including object tracking, navigation, and lidar technologies. However, event-based cameras have not been adequately researched for their ability to image high-energy particles. This report explores the use of an event camera for imaging alpha, beta, and X-rays particles, when coupled with scintillator screens to convert high-energy particles into visible light. Methods to process event data were developed and are presented here, along with the results. The event camera can measure alpha and beta particles with comparable performance to that of a conventional camera. Event cameras can also image higher-activity sources and offer the possibility of discriminating particle interaction types on the basis of timing differences, which typical cameras cannot do. Additionally, event cameras can image objects with an X-ray source when the source strength dynamically changes but does not create a high-contrast image during static X-ray measurement.

47 OTHER INSTRUMENTATION↗
NASA NTRS2007

Advanced High-Definition Video Cameras

A product line of high-definition color video cameras, now under development, offers a superior combination of desirable characteristics, including high frame rates, high resolutions, low power consumption, and compactness. Several of the cameras feature a 3,840 2,160-pixel format with progressive scanning at 30 frames per second. The power consumption of one of these cameras is about 25 W. The size of the camera, excluding the lens assembly, is 2 by 5 by 7 in. (about 5.1 by 12.7 by 17.8 cm). The aforementioned desirable characteristics are attained at relatively low cost, largely by utilizing digital processing in advanced field-programmable gate arrays (FPGAs) to perform all of the many functions (for example, color balance and contrast adjustments) of a professional color video camera. The processing is programmed in VHDL so that application-specific integrated circuits (ASICs) can be fabricated directly from the program. ["VHDL" signifies VHSIC Hardware Description Language C, a computing language used by the United States Department of Defense for describing, designing, and simulating very-high-speed integrated circuits (VHSICs).] The image-sensor and FPGA clock frequencies in these cameras have generally been much higher than those used in video cameras designed and manufactured elsewhere. Frequently, the outputs of these cameras are converted to other video-camera formats by use of pre- and post-filters.

Glenn, William↗
NASA NTRS2007

Improved Tracking of Targets by Cameras on a Mars Rover

A paper describes a method devised to increase the robustness and accuracy of tracking of targets by means of three stereoscopic pairs of video cameras on a Mars-rover-type exploratory robotic vehicle. Two of the camera pairs are mounted on a mast that can be adjusted in pan and tilt; the third camera pair is mounted on the main vehicle body. Elements of the method include a mast calibration, a camera-pointing algorithm, and a purely geometric technique for handing off tracking between different camera pairs at critical distances as the rover approaches a target of interest. The mast calibration is an extension of camera calibration in which the camera images of calibration targets at known positions are collected at various pan and tilt angles. In the camerapointing algorithm, pan and tilt angles are computed by a closed-form, non-iterative solution of inverse kinematics of the mast combined with mathematical models of the cameras. The purely geometric camera-handoff technique involves the use of stereoscopic views of a target of interest in conjunction with the mast calibration.

Kim, Won↗
NASA NTRS2010

Infrared Camera System for Visualization of IR-Absorbing Gas Leaks

Leak detection and location remain a common problem in NASA and industry, where gas leaks can create hazardous conditions if not quickly detected and corrected. In order to help rectify this problem, this design equips an infrared (IR) camera with the means to make gas leaks of IR-absorbing gases more visible for leak detection and location. By comparing the output of two IR cameras (or two pictures from the same camera under essentially identical conditions and very closely spaced in time) on a pixel-by-pixel basis, one can cancel out all but the desired variations that correspond to the IR absorption of the gas of interest. This can be simply done by absorbing the IR lines that correspond to the gas of interest from the radiation received by one of the cameras by the intervention of a filter that removes the particular wavelength of interest from the "reference" picture. This can be done most sensitively with a gas filter (filled with the gas of interest) placed in front of the IR detector array, or (less sensitively) by use of a suitable line filter in the same location. This arrangement would then be balanced against the unfiltered "measurement" picture, which will have variations from IR absorption from the gas of interest. By suitable processing of the signals from each pixel in the two IR pictures, the user can display only the differences in the signals. Either a difference or a ratio output of the two signals is feasible. From a gas concentration viewpoint, the ratio could be processed to show the column depth of the gas leak. If a variation in the background IR light intensity is present in the field of view, then large changes in the difference signal will occur for the same gas column concentration between the background and the camera. By ratioing the outputs, the same signal ratio is obtained for both high- and low-background signals, even though the low-signal areas may have greater noise content due to their smaller signal strength. Thus, one embodiment would use a ratioed output signal to better represent the gas column concentration. An alternative approach uses a simpler multiplication of the filtered signal to make the filtered signal equal to the unfiltered signal at most locations, followed by a subtraction to remove all but the wavelength-specific absorption in the unfiltered sample. This signal processing can also reveal the net difference signal representing the leaking gas absorption, and allow rapid leak location, but signal intensity would not relate solely to gas absorption, as raw signal intensity would also affect the displayed signal. A second design choice is whether to use one camera with two images closely spaced in time, or two cameras with essentially the same view and time. The figure shows the two-camera version. This choice involves many tradeoffs that are not apparent until some detailed testing is done. In short, the tradeoffs involve the temporal changes in the field picture versus the pixel sensitivity curves and frame alignment differences with two cameras, and which system would lead to the smaller variations from the uncontrolled variables.

Youngquist, Robert↗
NASA NTRS2015

Low Noise Camera for Suborbital Science Applications

Low-cost, commercial-off-the-shelf- (COTS-) based science cameras are intended for lab use only and are not suitable for flight deployment as they are difficult to ruggedize and repackage into instruments. Also, COTS implementation may not be suitable since mission science objectives are tied to specific measurement requirements, and often require performance beyond that required by the commercial market. Custom camera development for each application is cost prohibitive for the International Space Station (ISS) or midrange science payloads due to nonrecurring expenses (~$2,000 K) for ground-up camera electronics design. While each new science mission has a different suite of requirements for camera performance (detector noise, speed of image acquisition, charge-coupled device (CCD) size, operation temperature, packaging, etc.), the analog-to-digital conversion, power supply, and communications can be standardized to accommodate many different applications. The low noise camera for suborbital applications is a rugged standard camera platform that can accommodate a range of detector types and science requirements for use in inexpensive to mid range payloads supporting Earth science, solar physics, robotic vision, or astronomy experiments. Cameras developed on this platform have demonstrated the performance found in custom flight cameras at a price per camera more than an order of magnitude lower.

Hyde, David↗
NASA NTRS2018

Context Cameras for the Orbiting Carbon Observatory 3 (OCO-3) Instrument

We have developed an adaptable camera platform that takes advantage of screened and qualified commercial off the shelf (COTS) components (CMOS sensor, rad-tolerant microcircuits, lenses) to significantly shorten development time of space-borne visible imaging systems while reducing the overall cost and risk of the development. This modular camera platform is implemented as a suite of two visible-light cameras for the Orbiting Carbon Observatory 3 (OCO-3) instrument at NASA’s Jet Propulsion Laboratory (JPL). The Internal Context Camera (ICC) and External Context Camera (ECC) provide contextual engineering imaging support for the calibration of the OCO-3 instrument, intended to significantly reduce the duration of the mission’s calibration campaign. The OCO-3 mission has taken advantage of the design and qualification work performed by JPL’s Mars 2020 Enhanced Engineering Camera (EECam) team in reusing the qualified COTS CMOS imaging sensor, proven electronic designs, and scalable field-programmable gate array (FPGA) firmware to meet OCO-3’s mission requirements and resource availability. We will be presenting the steps taken by JPL to design, build, and test the Context Cameras for the OCO-3 mission. We will highlight the design deviations from the Mars2020 EECams and discuss the methodology of tailoring the EECam design for the OCO-3 requirements. Camera imaging capabilities, including focal plane and optical performance, will be presented, as well as a summary of the calibration and environmental test results. Finally, we will discuss the potential for future applications for the Context Cameras.

Moore, Douglas↗
NASA NTRS1991

Composite video and graphics display for multiple camera viewing system in robotics and teleoperation

A system for real-time video image display for robotics or remote-vehicle teleoperation is described that has at least one robot arm or remotely operated vehicle controlled by an operator through hand-controllers, and one or more television cameras and optional lighting element. The system has at least one television monitor for display of a television image from a selected camera and the ability to select one of the cameras for image display. Graphics are generated with icons of cameras and lighting elements for display surrounding the television image to provide the operator information on: the location and orientation of each camera and lighting element; the region of illumination of each lighting element; the viewed region and range of focus of each camera; which camera is currently selected for image display for each monitor; and when the controller coordinate for said robot arms or remotely operated vehicles have been transformed to correspond to coordinates of a selected or nonselected camera.

Diner, Daniel B.↗