From the Moon to the Earth: Planetary Exploration to Self-Driving Cars
This presentation provides an overview of robotics research activities at NASA Ames, which range from new techniques for planetary exploration to self-driving cars.
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This presentation provides an overview of robotics research activities at NASA Ames, which range from new techniques for planetary exploration to self-driving cars.
Several techniques have been explored and demonstrated that allow for greater data return on space-to-ground links. Among these techniques, arraying several smaller diameter dish antennas together is one method used in several arenas. These arrays can achieve larger effective area and gain than are available from a single larger antenna. This technique is routinely used by the NASA Deep Space Network (DSN) at 8.4 GHz where the incoming signals are much weaker than those experienced by the near-Earth satellite community. When considering arraying at much higher frequencies such as 32 GHz deep-space Ka-band, the phase alignment of the individual antenna signals is significantly disrupted by atmospheric turbulence. Since 2012, several downlink array demonstrations have been conducted using 32 GHz carrier signals emitted by the deep space probes Cassini and Kepler. Site test interferometers (STIs) that receive signals from geostationary satellites have been deployed at all three DSN tracking complexes for long-term monitoring of atmospheric delay fluctuations. In a previous DSN array demonstration study involving the Cassini spacecraft, it was shown that statistics of the adjusted STI phase fluctuations matched the statistics of concurrent array demonstration phase fluctuations. These adjustments accounted for differences in antenna separation, elevation angle and spacecraft frequencies. The STI antenna separations were about 200 m and the DSN antenna separations were about 300 m. These adjustments made use of the thick-layer turbulence model that was applicable to the Goldstone desert climate during the summer months for which the data were acquired. In this paper, we report on the results of additional array demonstrations involving the Kepler spacecraft and compare the adjusted STI phase fluctuations with those seen by a nearby two-element array of 34 m diameter antennas tracking Kepler’s 32 GHz signal at the Goldstone, California and Madrid, Spain DSN sites. We also discuss results from a demonstration using an array over a longer 12.5 km baseline. The Cassini and Kepler array demonstrations were found to validate the long term statistics acquired from several years of STI data as well as the models used to adjust the statistics for the conditions of an array. These statistics represent reliable estimates of the phase fluctuations that would be seen by an array tracking a deep space signal after applying appropriate adjustments for a given array configuration, elevation angle profile and observing frequency.
The problem of control command and maneuver induced structural loads is an important aspect of any control system design. The aircraft structure and the control architecture must be designed to achieve desired piloted control responses while limiting the imparted structural loads. The classical approach is to utilize high structural margins, restrict control surface commands to a limited set of analyzed combinations, and train pilots to follow procedural maneuvering limitations. With recent advances in structural sensing and the continued desire to improve safety and vehicle fuel efficiency, it is both possible and desirable to develop control architectures that enable lighter vehicle weights while maintaining and improving protection against structural damage. An optimal control technique has been explored and shown to achieve desirable vehicle control performance while limiting sensed structural loads to specified values. This technique has been implemented and flown on the National Aeronautics and Space Administration Full-scale Advanced Systems Testbed aircraft. The flight tests illustrate that the approach achieves the desired performance and show promising potential benefits. The flights also uncovered some important issues that will need to be addressed for production application.
A comparative study of wall mounted swept ramp injectors fitted with injector nozzles of different shape has been conducted in a constant area duct to explore mixing enhancement techniques for scramjet combustors. Six different injector nozzle inserts, all having equal exit and throat areas, were tested to explore the interaction between the preconditioned fuel jet and the vortical flowfield produced by the ramp: circular nozzle (baseline), nozzle with three downstream facing steps, nozzle with four vortex generators, elliptical nozzle, tapered-slot nozzle, and trapezoidal nozzle. The main flow was air at Mach 2, and the fuel was simulated by air injected at Mach 1.63 or by helium injected at Mach 1.7. Pressure and temperature surveys, combined with Mie and Rayleigh scattering visualization, were used to investigate the flow field. The experiments were compared with three dimensional Navier-Stokes computations. The results indicate that the mixing process is dominated by the streamwise vorticity generated by the ramp, the injectors' inner geometry having a minor effect. It was also found that the injectant/air mixing in the far-field is nearly independent of the injector geometry, molecular weight of the injectant, and the initial convective Mach number.
The use of mass spectrometry in fields related to polymers has increased significantly over the past three decades and will be explored in this literature review. The importance of this technique is highlighted when exploring how polymers degrade, verifying purchased materials, and as internal requirements change. The primary focus will be on four ionization techniques and the triple quadrupole and quadrupole / time-of-flight mass spectrometers. The advantages and limitations of each will also be explored.
Orthogonal defect classification (ODC) is a method used to categorize software defects, providing valuable insights into the development process. This study focuses on automating the classification of software bug reports into different ODC defect types using few shot learning, a machine learning approach that requires minimal labeled data. Previous research has manually classified bug reports or used traditional machine learning algorithms like linear support vector machine, achieving limited success. Our approach uses few shot learning to improve classification accuracy and efficiency. The results show a harmonic mean of recall and precision (i.e., the F1 score) of around 0.6 which is a performance improvement over previous methods. The results highlight the potential benefit of few shot learning techniques and their application in enhancing the safety and reliability of nuclear digital instrumentation and control (DI&C) systems. Future work will explore incorporating advanced techniques to supplement the model's training data and achieve better results.
The non-destructive readout capability of the Skipper Charge Coupled Device (CCD) has been demonstrated to reduce the noise limitation of conventional silicon devices to levels that allow single-photon or single-electron counting. The noise reduction is achieved by taking multiple measurements of the charge in each pixel. These multiple measurements come at the cost of extra readout time, which has been a limitation for the broader adoption of this technology in particle physics, quantum imaging, and astronomy applications. This work presents recent results of a novel sensor architecture that uses multiple non-destructive floating-gate amplifiers in series to achieve sub-electron readout noise in a thick, fully-depleted silicon detector to overcome the readout time overhead of the Skipper-CCD. This sensor is called the Multiple-Amplifier Sensing Charge-Coupled Device (MAS-CCD) can perform multiple independent charge measurements with each amplifier, and the measurements from multiple amplifiers can be combined to further reduce the readout noise. We will show results obtained for sensors with 8 and 16 amplifiers per readout stage in new readout operations modes to optimize its readout speed. The noise reduction capability of the new techniques will be demonstrated in terms of its ability to reduce the noise by combining the information from the different amplifiers, and to resolve signals in the order of a single photon per pixel. The first readout operation explored here avoids the extra readout time needed in the MAS-CCD to read a line of the sensor associated with the extra extent of the serial register. The second technique explore the capability of the MAS-CCD device to perform a region of interest readout increasing the number of multiple samples per amplifier in a targeted region of the active area of the device.
Here, this study explores the use of charge-coupled devices (CCDs) for detecting low-energy beta particles from tritium decay - a critical signal for nuclear safety, nuclear nonproliferation, and environmental monitoring. We employ a dual approach utilizing both measured CCD data and detailed Geant4 simulations. Our analysis compares classical techniques with advanced deep learning methods, including convolutional neural networks (CNNs), autoencoders trained exclusively on tritium data, and preliminary studies on boosted decision trees (BDTs). The CNN, trained on mixed signal/background datasets, demonstrates superior classification performance, while the autoencoder shows the potential of unsupervised, background-agnostic strategies when background characteristics are poorly defined. These results highlight the excellent sensitivity achievable thanks to the background rejection made possible by information-rich CCD data, paving the way for improved portable tritium monitoring.
Here, the filterscope diagnostic uses bandpass filters and photomultiplier tubes (PMTs) to detect specific spectral emission lines. A filterscope was used to measure the W I 400.88 nm line emission as a function of ion energy on the Radio Frequency Plasma Interaction Experiment (RF PIE) for the purpose of assessing W erosion on plasma-facing components (PFCs). Different filter techniques are being explored and compared in order to effectively screen out nearby impurity lines, like the Ar II 401.39 nm line. The effectiveness of these techniques is determined by comparing the measurements to a high-resolution 1.0 m Czerny–Turner spectrometer with 0.012 nm spectral resolution. The ability to filter out nearby impurity emissions is useful when imaging PFCs in fusion devices including divertor and antenna guard limiters. Initial results with a helium plasma show little difference between the two techniques at higher bias voltages. In a helium plasma at lower dc bias voltages, a two-filter technique with filters at two separate wavelengths was shown to be more effective at screening out background signals. Data collected with an argon plasma however show the technique with overlapping filters on the line of interest is a closer match to spectrometer data at lower dc bias voltages.
The application of an adaptive real-time measurement-based performance optimization technique is being explored for a future flight research program. The key technical challenge of the approach is parameter identification, which uses a perturbation-search technique to identify changes in performance caused by forced oscillations of the controls. The controls on the NASA F-15 highly integrated digital electronic control (HIDEC) aircraft were perturbed using inlet cowl rotation steps at various subsonic and supersonic flight conditions to determine the effect on aircraft performance. The feasibility of the perturbation-search technique for identifying integrated airframe-propulsion system performance effects was successfully shown through flight experiments and postflight data analysis. Aircraft response and control data were analyzed postflight to identify gradients and to determine the minimum drag point. Changes in longitudinal acceleration as small as 0.004 g were measured, and absolute resolution was estimated to be 0.002 g or approximately 50 lbf of drag. Two techniques for identifying performance gradients were compared: a least-squares estimation algorithm and a modified maximum likelihood estimator algorithm. A complementary filter algorithm was used with the least squares estimator.
The application of an adaptive real-time measurement-based performance optimization technique is being explored for a future flight research program. The key technical challenge of the approach is parameter identification, which uses a perturbation-search technique to identify changes in performance caused by forced oscillations of the controls. The controls on the NASA F-15 highly integrated digital electronic control (HIDEC) aircraft were perturbed using inlet cowl rotation steps at various subsonic and supersonic flight conditions to determine the effect on aircraft performance. The feasibility of the perturbation-search technique for identifying integrated airframe-propulsion system performance effects was successfully shown through flight experiments and postflight data analysis. Aircraft response and control data were analyzed postflight to identify gradients and to determine the minimum drag point. Changes in longitudinal acceleration as small as 0.004 g were measured, and absolute resolution was estimated to be 0.002 g or approximately 50 lbf of drag. Two techniques for identifying performance gradients were compared: a least-squares estimation algorithm and a modified maximum likelihood estimator algorithm. A complementary filter algorithm was used with the least squares estimator.
The functions of a regeneratively-cooled nozzle are to (1) expand combustion gases to increase exhaust gas velocity while, (2) maintaining adequate wall temperatures to prevent structural failure, and (3) transfer heat from the hot gases to the coolant fluid to promote injector performance and stability. Regeneratively-cooled nozzles are grouped into two categories: tube-wall nozzles and channel wall nozzles. A channel wall nozzle is designed with an internal liner containing a series of integral coolant channels that are closed out with an external jacket. Manifolds are attached at each end of the nozzle to distribute coolant to and away from the channels. A variety of manufacturing techniques have been explored for channel wall nozzles, including state of the art laser-welded closeouts and pressure-assisted braze closeouts. This paper discusses techniques that NASA MSFC is evaluating for rapid fabrication of channel wall nozzles that address liner fabrication, slotting techniques and liner closeout techniques. Techniques being evaluated for liner fabrication include large-scale additive manufacturing of freeform-deposition structures to create the liner blanks. Abrasive water jet milling is being evaluated for cutting the complex coolant channel geometries. Techniques being considered for rapid closeout of the slotted liners include freeform deposition, explosive bonding and Cold Spray. Each of these techniques, development work and results are discussed in further detail in this paper.
This paper introduces memoized symbolic execution (Memoise), a novel approach for more efficient application of forward symbolic execution, which is a well-studied technique for systematic exploration of program behaviors based on bounded execution paths. Our key insight is that application of symbolic execution often requires several successive runs of the technique on largely similar underlying problems, e.g., running it once to check a program to find a bug, fixing the bug, and running it again to check the modified program. Memoise introduces a trie-based data structure that stores the key elements of a run of symbolic execution. Maintenance of the trie during successive runs allows re-use of previously computed results of symbolic execution without the need for re-computing them as is traditionally done. Experiments using our prototype embodiment of Memoise show the benefits it holds in various standard scenarios of using symbolic execution, e.g., with iterative deepening of exploration depth, to perform regression analysis, or to enhance coverage.
Potential applications to planetary explorations of research techniques and findings related to structure of proteins and nucleic acids
Partners in Solutions is an exciting new program in which AAPM partners with our vendors to present practical “hands-on” information about the equipment and software systems that we use in our clinics. The imaging topic this year is CT scanner dose optimization capabilities. Note that the sessions are being held in a special purpose room built on the Exhibit Hall Floor, to encourage further interaction with the vendors. Dose Optimization Capabilities of GE Computed Tomography Scanners Presentation Time: 11:15 – 11:45 AM GE Healthcare is dedicated to the delivery of high quality clinical images through the development of technologies, which optimize the application of ionizing radiation. In computed tomography, dose management solutions fall into four categories: employs projection data and statistical modeling to decrease noise in the reconstructed image - creating an opportunity for mA reduction in the acquisition of diagnostic images. Veo represents true Model Based Iterative Reconstruction (MBiR). Using high-level algorithms in tandem with advanced computing power, Veo enables lower pixel noise standard deviation and improved spatial resolution within a single image. Advanced Adaptive Image Filters allow for maintenance of spatial resolution while reducing image noise. Examples of adaptive image space filters include Neuro 3-D filters and Cardiac Noise Reduction Filters. AutomA adjusts mA along the z-axis and is the CT equivalent of auto exposure control in conventional x-ray systems. Dynamic Z-axis Tracking offers an additional opportunity for dose reduction in helical acquisitions while SmartTrack Z-axis Tracking serves to ensure beam, collimator and detector alignment during tube rotation. SmartmA provides angular mA modulation. ECG Helical Modulation reduces mA during the systolic phase of the heart cycle. SmartBeam optimization uses bowtie beam-shaping hardware and software to filter off-axis x-rays - minimizing dose and reducing x-ray scatter. The DICOM Radiation Dose Structured Report (RDSR) generates a dose report at the conclusion of every examination. Dose Check preemptively notifies CT operators when scan parameters exceed user-defined dose thresholds. DoseWatch is an information technology application providing vendor-agnostic dose tracking and analysis for CT (and all other diagnostic x-ray modalities) SnapShot Pulse improves coronary CTA dose management. VolumeShuttle uses two acquisitions to increase coverage, decrease dose, and conserve on contrast administration. Color-Coding for Kids applies the Broselow-Luten Pediatric System to facilitate pediatric emergency care and reduce medical errors. FeatherLight achieves dose optimization through pediatric procedure-based protocols. Adventure Series scanners provide a child-friendly imaging environment promoting patient cooperation with resultant reduction in retakes and patient motion. Philips CT Dose Optimization Tools and Advanced Reconstruction Presentation Time: 11:45 ‘ 12:15 PM The first part of the talk will cover “Dose Reduction and Dose Optimization Technologies” present in Philips CT Scanners. The main Technologies to be presented include: DoseRight and tube current modulation (DoseRight, Z-DOM, 3D-DOM, DoseRight Cardiac) Special acquisition modes Beam filtration and beam shapers Eclipse collimator and ClearRay collimator NanoPanel detector DoseRight will cover automatic tube current selection that automatically adjusts the dose for the individual patient. The presentation will explore the modulation techniques currently employed in Philips CT scanners and will include the algorithmic concepts as well as illustrative examples. Modulation and current selection technologies to be covered include the Automatic Current Selection component of DoseRight, ZDOM longitudinal dose modulation, 3D-DOM (combination of longitudinal and rotational dose modulation), Cardiac Dose right (an ECG based dose modulation scheme), and the DoseRight Index (DRI) IQ index. The special acquisition modes covers acquisition techniques such as prospective gating that is designed to reduce exposure to the patient through the Cardiac Step and Shoot scan mode. This mode can substitute the much higher dose retrospective scan modes for certain types of cardiac imaging. The beam filtration and beam shaper portion will discuss the variety of filtration and beam shaping configurations available on Philips scanners. This topic includes the x-ray beam characteristics, tube filtration as well as dose compensator characteristics. The Eclipse collimator, ClearRay collimator and the NanoPanel detector portion will discuss additional technologies specific to wide coverage CT that address some of the unique challenges encountered and techniques employed to optimize image quality and optimize dose utilization. The Eclipse collimator reduces extraneous exposure by actively blocking the radiation tails at either end of helical scans that do not contribute to the image generation. The ClearRay collimator and the NanoPanel detector optimize the quality of the signal that reaches the detectors by addressing the increased scattered radiation present in wide coverage and the NanoPanel detector adds superior electronic noise characteristics valuable when imaging at a low dose level. The second part of the talk will present “Advanced Reconstruction Technologies” currently available on Philips CT Scanners. The talk will cover filtered back projection (FBP), iDose4 and Iterative Model Reconstruction (IMR). Each reconstruction method will include a discussion of the algorithm as well as similarities and differences between the algorithms. Examples illustrating the merits of each algorithm will be presented, and techniques and metrics to characterize the performance of each type of algorithm will be presented. The Filtered Back projection portion will discuss and provide a brief summary of relevant standard image reconstruction techniques in common use, and discuss the common tradeoffs when using the FBP algorithm. The iDose4 portion will present the algorithms used for iDose4 as well the different levels. The meaning of different levels of iDose4 available will be presented and quantified. Guidelines for selection iDose4 parameters based on the imaging need will be explained. The different image quality goals available with iDose4 and specifically how iDose4 enables noise reduction, spatial resolution improvement or both will be explained. The approaches to leveraging the benefits of iDose4 such as improved spatial resolution, decreased noise, and artifact prevention will be described and quantified; and measurements and metrics behind the improvements will be presented. The image quality benefits in specific imaging situations as well as how to best combine the technology with other dose reduction strategies to ensure the best image quality at a given dose level will be presented. Insight into the IMR algorithm as well as contrast to the iDose4 techniques and performance characteristics will be discussed. Metrics and techniques for characterizing this class of algorithm and IQ performance will be presented. The image quality benefits and the dose reduction capabilities of IMR will be explored. Illustrative examples of the noise reduction, spatial resolution improvement, and low contrast detectability improvements of the reconstruction method will be presented: clinical cases and phantom measurements demonstrating the benefits of IMR in the areas of low dose imaging, spatial resolution and low contrast resolution are discussed and the technical details behind the measurements will be presented compared to both iDose4 and traditional filtered back projection (FBP)
Neutron imaging is complementary to X-ray imaging where both are used to investigate the internal features of objects nondestructively. Historically, it only began three years after discovery of the neutron in 1932, however, neutron radiographs with reasonable quality were first made in the mid-fifties. Conventionally, the image is produced by placing the object between the neutron source and a two-dimensional position sensitive detector. The source commonly has a full energy spectrum (white beam) of thermal or cold neutrons to obtain high intensity in the sample and short exposure time. As a result, all neutron energies contribute to the obtained radiograph. Since the interaction of the neutron with matter is energy dependent, different energies produce different contrast on the radiographic image, hence, additional information about the object can be obtained. Neutron imaging that utilizes a narrow spectrum of energy instead of white beam is called energy selective neutron imaging. Many techniques have been explored to select a narrow band of neutron energy for the use in imaging such as the use velocity selectors, double crystal Monochromators, and time of flight techniques (at pulsed neutron sources). The PULSTAR reactor of North Carolina State University (1 MWth) currently has an operational neutron powder diffractometer (NPD) installed on beam tube no. 4, which was designed for neutron scattering experiments and can provide a monoenergetic beam of neutrons. The neutron energy could be selected by diffraction means using a Si bent perfect crystal as a Monochromator. In this work, an investigation of energy selective neutron imaging at the NPD is discussed in terms of the system performance and the ability of material discrimination on a test sample by observing the contrast variations of the neutron radiographs obtained using different neutron energies. Energy selective neutron imaging experiment was successfully tested at the PULSTAR reactor's NPD. Although, the uniform region is small and the exposure time is long in comparison with the NIF, both facilities exhibit similar spatial resolution which is a very important characteristic for any imaging facility. The contrast variation of neuron radiographs for the test sample obtained at different energies indicated a potential advantage for using energy selective neutron imaging over the white beam. (authors)
Introduction: NASA is preparing to land the first woman and first person of color on the Moon within the next decade, and ensuring the success of these missions will depend on our preparation on the ground in multiple ground-based lunar environment analogs. To achieve this, NASA has used full mission class analogs, of which NASA Extreme Environment Mission Operations (NEEMO) is the longest continuously running example. Discussion: NEEMO is NASA’s long-standing undersea high-fidelity spaceflight mission analog. It focuses on exploration science, EVA techniques and tools, and maturing ISS IVA flight hardware and operations concepts. NEEMO crews are composed of groups of US and International Partner (IP) astronauts, engineers and scientists who live, work and explore in a challenging environment analogous to the environment experienced currently on ISS and what is expected for future deep space exploration destinations. NEEMO missions are conducted at Aquarius Reef Base (ARB), which includes a shore base in Tavernier, FL, and the world's only undersea research station, the Aquarius habitat, which is located 5.4 miles (9 kilometers) off Key Largo in the Florida Keys National Marine Sanctuary. ARB is owned and operated by Florida International University (FIU). Aquarius was selected due to its remote and extreme location and its ability to provide the unique isolation and risk factors that spaceflight presents. NEEMO missions allow for evaluations of end-to-end EVA and Science exploration concepts of operations with a crew that is in situ in a true extreme environment. They also allow for evaluations of flight hardware and ops tools that are either pondered or destined for ISS or Gateway in the near future. NEEMO missions feature flight-like interactions between the crew and a Mission Control Center (MCC )and Science Team, which in turn allows evaluation of mission and science operations decision making and communications techniques. One reason NEEMO missions are of such high fidelity is that so many of the participants are experienced human space flight end operators. The majority of crewmembers are trained astronauts, and many of the MCC operators have credentials as current or former certified ISS MCC operators (e.g., CapCom, EVA Officer, etc.). Mission products are generated daily by the ground team and are modeled on ISS products (but modified as needed). A planning team manages the constantly evolving mission timelines in response to the ever-changing constraints and opportunities. During NEEMO missions, suited EVA crewmembers (using diving helmets) have clear voice communications with each other, the habitat, and the MCC and Science Team back on shore. Each EVA crewmember also sends helmet cam video to the habitat and MCC and Science Teams. Appropriate communications latencies are inserted for the destination being simulated as well. NEEMO missions are made possible by a broad collaboration of participants. Astronauts from all of the ISS partner agencies are eligible for crew assignment. Often the crew includes a NASA scientist, doctor or engineer with a particular skill to contribute. Sometimes crewmembers come from external entities–generally institutes or universities. Objectives come from a wide variety of sources as well, from within NASA, IPs, government agencies, academia, commercial companies and research institutes. A typical NEEMO mission is a collaboration between at least 5 NASA centers. To date, 23 NEEMO missions have been conducted since 2001, and NEEMO 24 is planned for 2022. Conclusion: NEEMO is a high-fidelity mission analog conducted in an extreme subsea environment. It features experienced end-operators in human spaceflight, from the astronaut crewmembers to key personnel staffing Mission Control. Acknowledgments: The authors wish to thank FIU and NASA’s HEO SEI/Strategic Analysis and Exploration Integration and Science Directorate organizations for the continued support that makes the NEEMO Project possible.
Exploratory analysis of the chemical space is an important task in the field of cheminformatics. For example, in drug discovery research, chemists investigate sets of thousands of chemical compounds in order to identify novel yet structurally similar synthetic compounds to replace natural products. Manually exploring the chemical space inhabited by all possible molecules and chemical compounds is impractical, and therefore presents a challenge. To fill this gap, we present ChemoGraph, a novel visual analytics technique for interactively exploring related chemicals. In ChemoGraph, we formalize a chemical space as a hypergraph and apply novel machine learning models to compute related chemical compounds. It uses a database to find related compounds from a known space and a machine learning model to generate new ones, which helps enlarge the known space. Moreover, ChemoGraph highlights interactive features that support users in viewing, comparing, and organizing computationally identified related chemicals. With a drug discovery usage scenario and initial expert feedback from a case study, we demonstrate the usefulness of ChemoGraph.