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At least 55 records · Page 3

Real-time model-based vision system for object acquisition and tracking

A machine vision system is described which is designed to acquire and track polyhedral objects moving and rotating in space by means of two or more cameras, programmable image-processing hardware, and a general-purpose computer for high-level functions. The image-processing hardware is capable of performing a large variety of operations on images and on image-like arrays of data. Acquisition utilizes image locations and velocities of the features extracted by the image-processing hardware to determine the three-dimensional position, orientation, velocity, and angular velocity of the object. Tracking correlates edges detected in the current image with edge locations predicted from an internal model of the object and its motion, continually updating velocity information to predict where edges should appear in future frames. With some 10 frames processed per second, real-time tracking is possible.

Wilcox, Brian↗

Tracking falling objects

Moving lens follows movement of object accelerated by gravity. Lenses and mirrors maintain constant magnification regardless of distance between moving optical carriage mechanism and fixed telescope. Device tracks objects up to 2 cm in diameter over vertical distance of 2 m.

Frazer, R. E.↗

Developing Methods for Exercise System Kinematics Tracking

BACKGROUND How to quantify the load and forces produced by exercise equipment and their Vibration Isolation and Stabilization (VIS) platforms in-flight is an active area of investigation. Kinematic tracking paired with system modeling can provide insights as well as verification and validation of simulations used for system design and development. Traditional motion capture methods can require significant cost in equipment procurement and crew-time, but newer lessons learned can be leveraged [1]. The VIS systems of current and future exercise hardware on the International Space Station (ISS) such as the Cycle Ergometer with Vibration Isolation System (CEVIS) and the European Enhanced Exploration Exercise Device (E4D) are not currently outfitted with IMUs or similar measurement devices. Video-based methods would enable use of multi-purpose, crew-familiar flight equipment. An initial exploration of video-based solutions was performed utilizing 2-camera video from crew cycling on Teal-CEVIS on the ISS. METHODS AND RESULTS Our group has scoped a variety of video-based object tracking methods. To date, we have primarily investigated computer vision toolkits such as openCV. Techniques explored include key-point detection, background subtraction, region-of interest tracking, color-based tracking, tag masking and tracking, and corner detection. Although object-tracking and 6D pose estimation is a rich field, space applications are a unique problem that are challenging for existing software and toolkits. The majority of the existing object-tracking applications involve vehicles/pedestrians and household objects with simple backgrounds. We have identified the following features which pose particular challenges for on-station exercise equipment tracking: Busy and visually cluttered background Low-textured tracking object with relatively small motions Occlusions and motion by human subject and loose, floating objects Limited number of video cameras with no fixed global references Limited ability to add tags, markers, or visual references to the tracking object Lack of training data for Machine Learning (ML) algorithms CONCLUSION We will summarize the efficacy of techniques tested for a ground mock-trial and the on-station exercise trial. It is likely that human-in-loop feedback or a conglomerate of methods is required. ML-based methods, like those implemented for human body tracking [2], may still be a viable option, but more training data and validation is needed.

L B Nilsson↗

Developing Methods for Exercise System Kinematic Tracking

BACKGROUND How to quantify the load and forces produced by exercise equipment and their Vibration Isolation and Stabilization (VIS) platforms in-flight is an active area of investigation. Kinematic tracking paired with system modeling can provide insights as well as verification and validation of simulations used for system design and development. Traditional motion capture methods can require significant cost in equipment procurement and crew-time, but newer lessons learned can be leveraged [1]. The VIS systems of current and future exercise hardware on the International Space Station (ISS) such as the Cycle Ergometer with Vibration Isolation System (CEVIS) and the European Enhanced Exploration Exercise Device (E4D) are not currently outfitted with IMUs or similar measurement devices. Video-based methods would enable use of multi-purpose, crew-familiar flight equipment. An initial exploration of video-based solutions was performed utilizing 2-camera video from crew cycling on Teal-CEVIS on the ISS. METHODS AND RESULTS Our group has scoped a variety of video-based object tracking methods. To date, we have primarily investigated computer vision toolkits such as open CV. Techniques explored include key-point detection, background subtraction, region-of interest tracking, color-based tracking, tag masking and tracking, and corner detection. Although object-tracking and 6D pose estimation is a rich field, space applications are a unique problem that are challenging for existing software and toolkits. The majority of the existing object-tracking applications involve vehicles/pedestrians and household objects with simple backgrounds. We have identified the following features which pose particular challenges for on-station exercise equipment tracking: 1. Busy and visually cluttered background 2. Low-textured tracking object with relatively small motions 3. Occlusions and motion by human subject and loose, floating objects 4. Limited number of video cameras with no fixed global references 5. Limited ability to add tags, markers, or visual references to the tracking object 6. Lack of training data for Machine Learning (ML) algorithms CONCLUSION We will summarize the efficacy of techniques tested for a ground mock-trial and the on-station exercise trial. It is likely that human-in-loop feedback or a conglomerate of methods is required. ML-based methods, like those implemented for human body tracking [2], may still be a viable option, but more training data and validation is needed.

L Nilsson↗

Real-time tracking of objects for space applications using a laser range scanner

Real-time tracking of multiple targets and three dimensional object features was demonstrated using a laser range scanner. The prototype was immune to ambient illumination and sun interference. Tracking error feedback was simultaneously obtained from individual targets, global predicted target position, and the human operator. A more complete study of calibration parameters and temperature variations on the scanner is needed to determine the exact performance of the sensor. Lissajous patterns used in three-dimensional real-time tracking prove helpful given their high resolution. The photogrammetry-based Advanced Space Vision System (ASVS) is discussed in combination with the laser range scanner.

Blais, F.↗

Real-time tracking of objects for a KC-135 microgravity experiment

The design of a visual tracking system for use on the Extra-Vehicular Activity Helper/Retriever (EVAHR) is discussed. EVAHR is an autonomous robot designed to perform numerous tasks in an orbital microgravity environment. Since the ability to grasp a freely translating and rotating object is vital to the robot's mission, the EVAHR must analyze range image generated by the primary sensor. This allows EVAHR to locate and focus its sensors so that an accurate set of object poses can be determined and a grasp strategy planned. To test the visual tracking system being developed, a mathematical simulation was used to model the space station environment and maintain dynamics on the EVAHR and any other free floating objects. A second phase of the investigation consists of a series of experiments carried out aboard a KC-135 aircraft flying a parabolic trajectory to simulate microgravity.

Littlefield, Mark L.↗

Memory object tagged memory monitoring method and system

Described are a method and processing apparatus to tag and track objects related to memory allocation calls. An application or software adds a tag to a memory allocation call to enable object level tracking. An entry is made into an object tracking table, which stores the tag and a variety of statistics related to the object and associated memory devices. The object statistics may be queried by the application to tune power/performance characteristics either by the application making runtime placement decisions, or by off-line code tuning based on a previous run. The application may add a tag to a memory allocation call to specify the type of memory characteristics requested based on the object statistics.

Roberts, David A.↗

California wildfire spread derived using VIIRS satellite observations and an object-based tracking system

Changing wildfire regimes in the western US and other fire-prone regions pose considerable risks to human health and ecosystem function. However, our understanding of wildfire behavior is still limited by a lack of data products that systematically quantify fire spread, behavior and impacts. Here we develop a novel object-based system for tracking the progression of individual fires using 375 m Visible Infrared Imaging Radiometer Suite active fire detections. At each half-daily time step, fire pixels are clustered according to their spatial proximity, and are either appended to an existing active fire object or are assigned to a new object. This automatic system allows us to update the attributes of each fire event, delineate the fire perimeter, and identify the active fire front shortly after satellite data acquisition. Using this system, we mapped the history of California fires during 2012–2020. Our approach and data stream may be useful for calibration and evaluation of fire spread models, estimation of near-real-time wildfire emissions, and as means for prescribing initial conditions in fire forecast models.

54 ENVIRONMENTAL SCIENCES↗

Orbital Debris: Past, Present, and Future

In the early days of spaceflight, the gBig Sky h theory was the near universally accepted paradigm for dealing with collisions of orbiting objects. This theory was also used during the early years of the aviation industry. Just as it did in aviation, the gBig Sky h theory breaks down as more and more objects accumulate in the environment. Fortunately, by the late 1970 fs some visionaries in NASA and the US Department of Defense (DoD) realized that trends in the orbital environment would inevitably lead to increased risks to operational spacecraft from collisions with other orbiting objects. The NASA Orbital Debris Program was established at and has been conducted at Johnson Space Center since 1979. At the start of 1979, fewer than 5000 objects were being tracked by the US Space Surveillance Network and very few attempts had been made to sample the environment for smaller sizes. Today, the number of tracked objects has quadrupled. Ground ]based and in situ measurements have statistically sampled the LEO environment over most sizes and mitigation guidelines and requirements are common among most space faring nations. NASA has been a leader, not only in defining the debris environment, but in promoting awareness of the issues in the US and internationally, and in providing leadership in developing policies to address the issue. This paper will discuss in broad terms the evolution of the NASA debris program from its beginnings to its present broad range of debris related research. The paper will discuss in some detail current research topics and will attempt to predict future research trends.

Stansbery, Gene↗

Launch Collision Probability

This report analyzes the probability of a launch vehicle colliding with one of the nearly 10,000 tracked objects orbiting the Earth, given that an object on a near-collision course with the launch vehicle has been identified. Knowledge of the probability of collision throughout the launch window can be used to avoid launching at times when the probability of collision is unacceptably high. The analysis in this report assumes that the positions of the orbiting objects and the launch vehicle can be predicted as a function of time and therefore that any tracked object which comes close to the launch vehicle can be identified. The analysis further assumes that the position uncertainty of the launch vehicle and the approaching space object can be described with position covariance matrices. With these and some additional simplifying assumptions, a closed-form solution is developed using two approaches. The solution shows that the probability of collision is a function of position uncertainties, the size of the two potentially colliding objects, and the nominal separation distance at the point of closest approach. ne impact of the simplifying assumptions on the accuracy of the final result is assessed and the application of the results to the Cassini mission, launched in October 1997, is described. Other factors that affect the probability of collision are also discussed. Finally, the report offers alternative approaches that can be used to evaluate the probability of collision.

Bollenbacher, Gary↗

NASA Lewis Launch Collision Probability Model Developed and Analyzed

There are nearly 10,000 tracked objects orbiting the earth. These objects encompass manned objects, active and decommissioned satellites, spent rocket bodies, and debris. They range from a few centimeters across to the size of the MIR space station. Anytime a new satellite is launched, the launch vehicle with its payload attached passes through an area of space in which these objects orbit. Although the population density of these objects is low, there always is a small but finite probability of collision between the launch vehicle and one or more of these space objects. Even though the probability of collision is very low, for some payloads even this small risk is unacceptable. To mitigate the small risk of collision associated with launching at an arbitrary time within the daily launch window, NASA performs a prelaunch mission assurance Collision Avoidance Analysis (or COLA). For the COLA of the Cassini spacecraft, the NASA Lewis Research Center conducted an in-house development and analysis of a model for launch collision probability. The model allows a minimum clearance criteria to be used with the COLA analysis to ensure an acceptably low probability of collision. If, for any given liftoff time, the nominal launch vehicle trajectory would pass a space object with less than the minimum required clearance, launch would not be attempted at that time. The model assumes that the nominal positions of the orbiting objects and of the launch vehicle can be predicted as a function of time, and therefore, that any tracked object that comes within close proximity of the launch vehicle can be identified. For any such pair, these nominal positions can be used to calculate a nominal miss distance. The actual miss distances may differ substantially from the nominal miss distance, due, in part, to the statistical uncertainty of the knowledge of the objects positions. The model further assumes that these position uncertainties can be described with position covariance matrices. With these, and some additional simplifying assumptions, a closed-form solution for the probability of collision is obtained. This solution provides clear insights into how each of the independent parameters affects the probability of collision. It shows that for a given maximum probability of collision and prior knowledge of the objects position uncertainties and sizes, only knowledge of the nominal closest approach distance is required to make the launch/no launch decision. The model was completed and used for the mission assurance COLA analysis for the Cassini spacecraft, which was launched on a Titan IV/Centaur rocket on October 15, 1997. Although the model was specifically developed for the Cassini mission, it is clearly applicable for other launches as well. The effect of COLA closures on the launch window is shown. The bar represents the entire 140-min launch window on October 15, 1997; the blackened areas represent the loss of launch opportunities due to the potential for a collision with an orbiting object.

Bollenbacher, Gary↗

Real-time optical multiple-object recognition and tracking demonstration: A friendly challenge to the digital field

Researchers demonstrated the first optical multiple object tracking system. The system is capable of simultaneous tracking of multiple objects, each with independent movements in real-time, limited only to the TV frame rate (30 msec). In order to perform a similar tracking operation, a large computer system and very complex software would be needed. Although researchers have demonstrated the tracking of only 3 objects, the system capacity can easily be expanded by 2 orders of magnitude.

Chao, Tien-Hsin↗

Current Characteristics and Trends of the Tracked Satellite Population in the Human Space Flight Regime

Since the end of the Apollo program in 1972, human space flight has been restricted to altitudes below 600 km above the Earth s surface with most missions restricted to a ceiling below 400 km. An investigation of the tracked satellite population transiting and influencing the human space flight regime during the past 11 years (equivalent to a full solar cycle) has recently been completed. The overall effects of satellite breakups and solar activity are typically less pronounced in the human space flight regime than other regions of low Earth orbit. As of January 2006 nearly 1500 tracked objects resided in or traversed the human space flight regime, although two-thirds of these objects were in orbits of moderate to high eccentricity, significantly reducing their effect on human space flight safety. During the period investigated, the spatial density of tracked objects in the 350-400 km altitude regime of the International Space Station demonstrated a steady decline, actually decreasing by 50% by the end of the period. On the other hand, the region immediately above 600 km experienced a significant increase in its population density. This regime is important for future risk assessments, since this region represents the reservoir of debris which will influence human space flight safety in the future. The paper seeks to put into sharper perspective the risks posed to human space flight by the tracked satellite population, as well as the influences of solar activity and the effects of compliance with orbital debris mitigation guidelines on human space flight missions. Finally, the methods and successes of characterizing the population of smaller debris at human space flight regimes are addressed.

Johnson, Nicholas L.↗

Application of the one-dimensional Fourier transform for tracking moving objects in noisy environments

In Riddle and Rajala (1981), an algorithm was presented which operates on an image sequence to identify all sets of pixels having the same velocity. The algorithm operates by performing a transformation in which all pixels with the same two-dimensional velocity map to a peak in a transform space. The transform can be decomposed into applications of the one-dimensional Fourier transform and therefore can gain from the computational advantages of the FFT. The aim of this paper is the concern with the fundamental limitations of that algorithm, particularly as relates to its sensitivity to image-disturbing parameters as noise, jitter, and clutter. A modification to the algorithm is then proposed which increases its robustness in the presence of these disturbances.

Rajala, S. A.↗

Small Orbital Debris Mitigation Mission Architecture

Small orbital debris in LEO (1-10 cm in size) presents a clear and present danger to operational LEO spacecraft. This debris field has dramatically increased (nearly doubled) in recent years following the Chinese ASAT Test in 2007 and the Iridium/Cosmos collision in 2009. Estimates of the number of small debris have grown to 500,000 objects after these two events; previously the population was 300,000 objects. These small, untracked debris objects (appproximately 500,000) outnumber the larger and tracked objects (appproximately 20,000) by a factor 25 to 1. Therefore, the risk of the small untracked debris objects to operational spacecraft is much greater than the risk posed by the larger and tracked LEO debris objects. A recent study by The Aerospace Corporation found that the debris environment will increase the costs of maintaining a constellation of government satellites by 5%, a constellation of large commercial satellites by 11%, and a constellation of factory built satellites by 26% from $7.6 billion to $9.57 billion. Based upon these facts, the NASA Marshall Space Flight Center (MSFC) Advanced Concepts Office (ACO) performed an architecture study on Small Orbital Debris Active Removal (SODAR) using a space-based nonweapons- class laser satellite for LEO debris removal. The goal of the SODAR study was to determine the ability of a space-based laser system to remove the most pieces of debris (1 cm to 10 cm, locations unknown), in the shortest amount of time, with the fewest number of spacecraft. The ESA developed MASTER2005 orbital debris model was used to probabilistically classify the future debris environment including impact velocity, magnitude, and directionality. The study ground rules and assumptions placed the spacecraft into a high inclination Low Earth Orbit at 800 km as an initial reference point. The architecture study results found that a spacecraft with an integrated forward-firing laser is capable of reducing the small orbital debris flux within a 60 to 100 km orbital shell by a significant amount within the one spacecraft's operational lifetime. The technology developments required for such an architecture to be successfully employed are: 1) A pico-pulsed, space qualified laser and 2) The ability to detect and track a small LEO small debris object from a space based platform. Therefore, a conceptual design for a demonstration satellite to showcase the ability to detect and track small orbital debris was completed

Wiegmann, Bruce M.↗

The Zwicky Transient Facility: Data Processing, Products, and Archive

The Zwicky Transient Facility (ZTF) is a new robotic time-domain survey currently in progress using the Palomar 48-inch Schmidt Telescope. ZTF uses a 47 square degree field with a 600 megapixel camera to scan the entire northern visible sky at rates of ∼3760 square degrees/hour to median depths of g ~ 20.8 and r ~ 20.6 mag (AB, 5σ in 30 sec). We describe the Science Data System that is housed at IPAC, Caltech. This comprises the data-processing pipelines, alert production system, data archive, and user interfaces for accessing and analyzing the products. The real-time pipeline employs a novel image-differencing algorithm, optimized for the detection of point-source transient events. These events are vetted for reliability using a machine-learned classifier and combined with contextual information to generate data-rich alert packets. The packets become available for distribution typically within 13 minutes (95th percentile) of observation. Detected events are also linked to generate candidate moving-object tracks using a novel algorithm. Objects that move fast enough to streak in the individual exposures are also extracted and vetted. We present some preliminary results of the calibration performance delivered by the real-time pipeline. The reconstructed astrometric accuracy per science image with respect to Gaia DR1 is typically 45 to 85 milliarcsec. This is the RMS per-axis on the sky for sources extracted with photometric S/N ≥10 and hence corresponds to the typical astrometric uncertainty down to this limit. The derived photometric precision (repeatability) at bright unsaturated fluxes varies between 8 and 25 millimag. The high end of these ranges corresponds to an airmass approaching ∼2—the limit of the public survey. Photometric calibration accuracy with respect to Pan-STARRS1 is generally better than 2%. The products support a broad range of scientific applications: fast and young supernovae; rare flux transients; variable stars; eclipsing binaries; variability from active galactic nuclei; counterparts to gravitational wave sources; a more complete census of Type Ia supernovae; and solar-system objects.

Frank J. Masci↗

Visual tracking in stereo

A method is described for visual object tracking by a computer vision system using TV cameras and special low-level image processing hardware. The tracker maintains an internal model of the location, orientation, and velocity of the object in three-dimensional space. This model is used to predict where features of the object will lie on the two-dimensional images produced by stereo TV cameras. The differences in the locations of features in the two-dimensional images as predicted by the internal model and as actually seen create an error signal in the two-dimensional representation. This is multiplied by a generalized inverse Jacobian matrix to deduce the error in the internal model. The procedure repeats to update the internal model of the object's location, orientation and velocity continuously.

Saund, E.↗

The Relationship Between African Easterly Waves and Tropical Cyclones in Historical and Future Climates in the HighResMIP‐PRIMAVERA Simulations

Abstract The deadly and destructive nature of tropical cyclones (TCs) makes understanding their response to future climate change of the utmost importance. TC genesis hinges on multiple factors, including an initial disturbance. African easterly waves (AEWs) have been shown to serve as such disturbances for TCs developing in the North Atlantic. It is therefore crucial to understand the relationship between AEWs and TCs and how this relationship may be affected by climate change. In this study, we examine the AEW‐TC relationship in historical and future climates using three models from the HighResMIP PRIMAVERA simulations. The AEWs and TCs were tracked in the model data using objective tracking algorithms, and AEW and TC tracks were then matched together if they were close to each other in space and time. The strength of the AEWs was measured using the eddy kinetic energy and the curvature vorticity of the waves. TC strength and intensity were measured using potential intensity and lifetime maximum 10 m windspeed. We found that future changes in the frequency of AEWs are not a good indicator of future TC activity. However, AEW strength, as well as environmental conditions conducive to strong TCs, are good indicators of AEWs that develop into TCs in both historical and future climates.

54 ENVIRONMENTAL SCIENCES↗