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All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

Adaptive Stress Testing of Collision Avoidance Systems for Small UASs with Deep Reinforcement Learning

The next-generation Airborne Collision Avoidance System for smaller UASs (ACAS sXu) is currently being developed and tested by the Federal Aviation Administration (FAA) to provide detect-and-avoid capability for small unmanned aircraft operating beyond line-of-sight. Due to the complexity and safety-critical nature of the system, safety validation is important not only for the certification of the final system, but also for informing changes during the iterative development process. In this paper, we analyze a prototype of ACAS sXu in simulated aircraft encounters to discover scenarios of small near mid-air collisions (sNMACs), an important safety event in which two aircraft come closer than 50 feet horizontally and 15 feet vertically. Due to the size and complexity of the system as well as rarity of sNMAC events, traditional methods such as Monte Carlo testing often require informed setup and targeting to elicit failures. However, such a dependence on domain knowledge can be incompatible with the independent verification and validation (IV&V) process, the aim of which is to discover unforeseen issues. To address these challenges, we apply an accelerated validation method called adaptive stress testing (AST) to find the most likely sNMAC scenarios without reliance on system introspection. AST uses reinforcement learning to adapt the search towards the most promising areas of the search space as it progresses. We use a state-of-the-art deep reinforcement learning algorithm, proximate policy optimization, to more efficiently search the large and continuous state space. We find that this approach significantly improves the performance of AST compared to a prior approach based on Monte Carlo tree search. We perform experiments using AST to find sNMAC events under various encounter configurations, varying parameters pertaining to dynamics and coordination. Our experiments show AST to be very effective at finding sNMAC scenarios. We summarize our findings, presenting high-level categories of discovered sNMACs and specific examples of encounters in each category.

aircraft collision avoidance↗

NASA NTRS2015

Small UAV Automatic Ground Collision Avoidance System Design Considerations and Flight Test Results

The National Aeronautics and Space Administration (NASA) Armstrong Flight Research Center Small Unmanned Aerial Vehicle (SUAV) Automatic Ground Collision Avoidance System (Auto GCAS) project demonstrated several important collision avoidance technologies. First, the SUAV Auto GCAS design included capabilities to take advantage of terrain avoidance maneuvers flying turns to either side as well as straight over terrain. Second, the design also included innovative digital elevation model (DEM) scanning methods. The combination of multi-trajectory options and new scanning methods demonstrated the ability to reduce the nuisance potential of the SUAV while maintaining robust terrain avoidance. Third, the Auto GCAS algorithms were hosted on the processor inside a smartphone, providing a lightweight hardware configuration for use in either the ground control station or on board the test aircraft. Finally, compression of DEM data for the entire Earth and successful hosting of that data on the smartphone was demonstrated. The SUAV Auto GCAS project demonstrated that together these methods and technologies have the potential to dramatically reduce the number of controlled flight into terrain mishaps across a wide range of aviation platforms with similar capabilities including UAVs, general aviation aircraft, helicopters, and model aircraft.

Sorokowski, Paul↗

NASA NTRS2018

Signatures of the Impact Histories of Comets and Asteroids within Shocked Phyllosilicates, Enstatite, and Forsterite Minerals

Throughout the lifetime of the solar system, collisions between small bodies and impacts on the surfaces of small bodies in the Kuiper Belt have occured at speeds of 1.5 - 3 km s-1 (Stern, Astron J 124, 2002), typically at 1-10 km s-1 between Trojan asteroids (Marzari et al. Icarus 119, 1996), and at ~4-8 km s-1 in the asteroid belt (Farinella and Davis, Icarus 97, 1992). Shock effects recorded by minerals composing these bodies are one observable legacy of this evolutionary process, whether they were generated through large collisions, micrometeoroid impacts, or processing during the formation of the solar system. Shock metamorphism has been observed in cometary samples such as those from Comet Wild 2 (Keller et al. Geochim. Cosmochim. Acta 72, 2008; Tomeoka et al. MAPS 43, 2008; Jacobs et al. MAPS 44, 2009) as well as in forsterites and enstatites found in meteorites (McCausland et al. AGU, 2010). To investigate the observable signatures of these processes, we have conducted a suite of impact experiments at NASA Johnson Space Center's Experimental Impact Laboratory (EIL). Target materials included Mg-rich forsterite (olivine), Mg-rich enstatite (orthopyroxene), and antigorite and lizardite (both in the serpentine group of phyllosilicates). Alumina-ceramic spheres were launched at speeds ranging from ~2.0 - 2.6 km s-1 into targets at temperatures from 25degC to -100degC. Recent advancements have been made in cooling targets in the EIL's vertical gun. Liquid nitrogen (LN2) is fed through a unique jacket surrounding the metallic sample container to chill the samples. Real-time values from temperature sensors attached to the sample holder are converted to target temperature through predetermined regression relationships, providing the target temperature at the time of impact with sub-degree accuracy. Fourier Transform Infrared Spectrometer (FTIR) data in the near to mid-IR will be presented, along with trends relating temperature and velocity with impact speeds, and thereby peak shock stresses experienced by the impacted minerals.

Lederer, Susan M.↗

NASA NTRS2018

[Micron]ADS-B Detect and Avoid Flight Tests on Phantom 4 Unmanned Aircraft System

Researchers at the National Aeronautics and Space Administration Armstrong Flight Research Center in Edwards, California and Vigilant Aerospace Systems collaborated for the flight-test demonstration of an Automatic Dependent Surveillance-Broadcast based collision avoidance technology on a small unmanned aircraft system equipped with the uAvionix Automatic Dependent Surveillance-Broadcast transponder. The purpose of the testing was to demonstrate that National Aeronautics and Space Administration / Vigilant software and algorithms, commercialized as the FlightHorizon UAS"TM", are compatible with uAvionix hardware systems and the DJI Phantom 4 small unmanned aircraft system. The testing and demonstrations were necessary for both parties to further develop and certify the technology in three key areas: flights beyond visual line of sight, collision avoidance, and autonomous operations. The National Aeronautics and Space Administration and Vigilant Aerospace Systems have developed and successfully flight-tested an Automatic Dependent Surveillance-Broadcast Detect and Avoid system on the Phantom 4 small unmanned aircraft system. The Automatic Dependent Surveillance-Broadcast Detect and Avoid system architecture is especially suited for small unmanned aircraft systems because it integrates: 1) miniaturized Automatic Dependent Surveillance-Broadcast hardware; 2) radio data-link communications; 3) software algorithms for real-time Automatic Dependent Surveillance-Broadcast data integration, conflict detection, and alerting; and 4) a synthetic vision display using a fully-integrated National Aeronautics and Space Administration geobrowser for three dimensional graphical representations for ownship and air traffic situational awareness. The flight-test objectives were to evaluate the performance of Automatic Dependent Surveillance-Broadcast Detect and Avoid collision avoidance technology as installed on two small unmanned aircraft systems. In December 2016, four flight tests were conducted at Edwards Air Force Base. Researchers in the ground control station looking at displays were able to verify the Automatic Dependent Surveillance-Broadcast target detection and collision avoidance resolutions.

avoidance↗

NASA NTRS2024

A Method of Compliance for Achieving Target Collision Risk in UTM Operations

This work proposes a method of compliance to ensure that the collision risks among small unmanned aircraft systems meet the target level of safety. This method presents what is needed for a strategic conflict detection service to achieve the target level of safety when conflict between operational intents are not permitted in nominal situations. A volume-based collision risk model is first developed to calculate the UA-to-UA collision risk given any two operational intent volumes. With this collision risk model, a test strategy is then proposed to assess if a strategic conflict detection service can reduce the collision risk and meet the target level of safety. The method also specifies operational data that are required to be collected to verify if requirements on conformance are being met. Additionally, two new requirements are identified and proposed by this method beyond the current standard for strategic conflict detection. In the sensitivity analysis, three main factors contributing to the collision risk are investigated. The analysis shows that buffers should be considered in a strategic conflict detection service when deconflicting operational intents. The results also reveal that the selection of test cases plays an important role in evaluating the strategic conflict detection service, and they should be representative and sufficiently complex in evaluation tests.

Collision Risk↗

NASA NTRSDate not supplied

A Method of Compliance for Achieving Target Collision Risk in UTM Operations

UTM, Method of Compliance, collision risk↗

NASA NTRSDate not supplied

A Method of Compliance for Achieving Target Collision Risk in UTM Operations

UTM↗

NASA NTRS1978

A note on the problem of jet stream formation

It is noted that the formation of 'jet streams', or narrow ringlike structures of small particles, in early planetary and satellite systems cannot result solely from inelastic collisions among the small particles. The possibility is considered that gravitational encounters between the particles will perturb them into more eccentric orbits and thus maintain the orbital coupling between particles (or jet streams) in neighboring orbits. It is found that when the gravitational effect of the particles is taken into account, the average eccentricity of the particles increases as agglomeration due to inelastic collisions proceeds. With respect to jet-stream formation, it is suggested that the ever-increasing orbital eccentricity of the particles will aid in coupling together the different 'sub-jet streams', so that large-scale orbital focusing toward the center of the whole system can continue. Alternative mechanisms leading to planetary accretion are briefly discussed.

Ip, W.-H.↗

NASA NTRSDate not supplied

Adaptive Stress Testing: Using Reinforcement Learning to Find Failures in Safety-Critical Systems

Emerging applications in artificial intelligence, such as driverless cars and autonomous aircraft promise to be more efficient, cheaper to operate, and always available. However, ensuring the safety of these systems remains a major challenge to their certification and adoption. These autonomous systems are expected to routinely make safety-critical decisions where failures can have serious consequences including loss of life and property. Testing and validation techniques aim to identify and diagnose potential failures before the system is deployed. However, finding failure scenarios in autonomous systems can be very challenging due to high-dimensional and continuous state spaces, interaction with large environments over many time steps, and the rarity of failures. This talk presents Adaptive Stress Testing (AST), a simulation-based testing framework for finding the most likely path to a failure event of a safety-critical system. The key idea of AST is that stress testing can be formulated as a Partially Observable Markov Decision Process (POMDP), which enables reinforcement learning techniques to be used for finding failure events. Reinforcement learning algorithms can efficiently explore the search space and have been shown to scale to very large systems. We present applications of AST to find failures in various safety-critical systems including the aircraft collision avoidance systems, autonomous cars, and small unmanned aerial vehicles.

autonomous vehicles↗

NASA NTRSDate not supplied

Monocular Ranging for Small Unmanned Aerial Systems in the Far-Field

Recent proliferation of small Unmanned Aerial Systems (sUAS) applications requires onboard collision avoidance systems to mitigate the risk of collision with non-cooperative aircraft and manned aircraft, which may not see sUAS in time to perform an avoidance maneuver. An attractive avenue for onboard collision avoidance is the utilization of machine vision cameras due to their low size, weight and power (SWaP) requirements. In this paper, we characterize the range performance of a machine vision system developed in-house and mounted onto an sUAS. The technique was designed to estimate the performance of a sense-and-avoid system to ensure that the sensing components meet the well-clear requirements for the chosen platform and avoidance strategy. Experimental flight-test data was acquired from test-flights flown along multiple collision geometries for two intruders: a general Aviation (GA) aircraft and a fixed-wing sUAS. The ownship and both intruders were instrumented with inertial navigation systems (INS) recording position and attitude information. The range at first detection, 𝑹𝟎, was extracted from in-flight imagery of head-on collision course geometry synchronized with INS data from both aircraft and ground-truth values extracted from the raw imagery. This initial detection distance, 𝑹𝟎, scales with atmospheric attenuation. Therefore, under clear sky conditions, the derived 𝑹𝟎 value represents the upper bound on the detection range achievable by the test configuration of the detector. Results indicate that the maximum initial detection distance for a 4k resolution action camera fitted with a 41º Field of View (FOV) lens is 2.763 ± 0.037 km for a GA aircraft and 0.881 ± 0.061 km for a fixed-wing sUAS, respectively. The in results this study suggest that a vision-based detect and track system may be analyzed using the sensor characterization and contextualized within aircraft well-clear volumes.

Chester V. Dolph↗

NASA NTRS1979

The nature and effects of impact cratering on small bodies

Collisions between asteroids and other forms of solar system debris are discussed, especially relatively high-energy, non-catastrophic collisions, the resulting craters, and the effects they should have on the surfaces and interiors of target bodies. Attention is given to the nature and formation of impact craters, as well as to shock waves and the energy (kinetic, internal) imparted through them, crater scaling, stress wave-surface interactions, impact melt, and the effects of non-escaping ejecta on the surface of the target body (rock, fine-grained regolith, porous media).

Cintala, M. J.↗

NASA NTRSDate not supplied

Ground to Air Testing of a Fused Optical-Radar Aircraft Detection and Tracking System

Onboard detection and tracking capability are integral to the sensing component in collision avoidance systems needed to safely operate autonomous urban air taxis and small Unmanned Aircraft Systems. Ground-based validation of detection and tracking systems is an important milestone towards the end goal of real-time collision avoidance using onboard sensors and algorithms. In this work, we evaluate three Extended Kalman Filter(EKF)based fusion trackers with radar and vision detection inputs, and compare them with baseline trackers for each sensor type. Performance is assessed using field collected data of ground to air test flights with the sensors co-located on a stable platform with an instrumented multirotor acting as the intruder performing a waypoint pattern at a distance of1.1km to 0.3km to simulate a head-on collision geometry. Fusing an image-based morphological detector with a radar detector using an EKF covered 74% of the ground truth position updates logged by the flight controller on the multirotor within 50 meters after accounting for alignment offsets while covering 15% more ground truth updates relative to radar only. Removing timestamps when the intruder aircraft is occluded by trees and only considering timestamps where the radar has an update, the EKF image-based morphological detector combined with the radar detector covered 90% of the of the ground truth position updates within 50metersand 97% within 100 meters.

Chester V Dolph↗

NASA NTRSDate not supplied

Classifying Aircraft using Velocity Data with Support Vector Machines and Likelihood Ratio Tests

Timely classification of aircraft is important for small unmanned aerial system (sUAS) technologies, such as onboard collision avoidance systems, and aerial perimeter security for prisons and sports venues. This work uses velocity-based metrics to classify multi-rotor sUAS, fixed wings UAS, and general aviation planes using two classification methods: Support Vector Machines (SVM), and Likelihood Ratio (LR) tests. We found that a 96% classification accuracy is achieved when either classifier is trained using average speed derived from flight controller data or radar data and tested with one second of radar data. Further, we show that LR tests perform similarly to SVM for single metric classification. In addition, we present two novel metrics for classifying aircraft: log variance of absolute change in speed, and log variance of relative change in speed. Finally, we discuss challenges associated with training classifiers with flight controller data but testing on radar data.

Logan T Dihel↗

NASA NTRS1990

Exclusive measurements of light fragment production at forward angles in Ne-Pb and Ne-NaF collisions at E/A=400 MeV and 800 MeV

Emission of light fragments at small angles is studied in relativistic heavy ion collisions using the Diogene plastic wall for both symmetrical and non-symmetrical target-projectile systems with 400 MeV per nucleon and 800 MeV per nucleon incident neon nuclei. Efficiency of multiplicity measurements in the small angle range for the selection of central or peripheral collisions is confirmed for asymmetric systems. Differential production cross sections of Z = 1 fragments show evidence for the existence of two emitting sources. The apparent temperature of each source is obtained from comparison with a thermodynamical model.

NASA Discipline Number 04-10↗

NASA NTRS2019

Landsat 9 Micrometeoroid and Orbital Debris (MMOD) Mission Success Approach

Landsat 9* (L9) is the successor mission to Landsat 8 (L8) previously known as Landsat Data Continuity Mission (LDCM). Both missions are large unmanned remote sensing satellites operating in sunsynchronous polar orbits. As opposed to L8/LDCM, systems engineers for L9 incorporated Micrometeoroid/Orbital Debris (MMOD) protection for small object collisions as part of the L9’s mission success criteria. In other words, the NASA Process for Limiting Orbital Debris (NASA-STD-8719.14A) only calls for analyses of the protection of disposal-critical hardware, but L9 opted to also assess and provide small particle penetration protections for all observatory components including instruments that are not part of the spacecraft components needed for controlled reentry. Systems engineers at Goddard developed a design process to protect against MMOD during the life of Low Earth Orbit (LEO) observatories, and in particular the Landsat 9 Mission. Simply stated, this design process enhanced the effectiveness of existing Multi-Layer Insulation (MLI) to provide the needed protection. The end goal of the design process was to establish a necessary blanket areal density for a given electronics box or instrument wall thickness and a separation between the outer MLI blanket and the structure underneath. The trade space was presented as a set of design curves for different combinations of blanket density, box wall thickness, and separation distance between MLI and structure. An advantage of this process was that it is largely independent of MMOD flux data on a surface-by surface basis. Ultimately, cost savings should result from incorporating small object penetration protection early in the design cycle, rather than adding spot shielding blankets later as needed to meet an overall penetration risk standard (the more traditional approach). The approach and implementation to the L9 Observatory design will be addressed in this paper. *L9 is a joint mission being formulated, implemented, and operated by the National Aeronautics and Space Administration (NASA) and the Department of the Interior’s (DOI) United States Geological Survey (USGS).

Approach↗

NASA NTRS2017

A Fuzzy Logic Approach for Separation Assurance and Collision Avoidance for Unmanned Aerial Systems

In the coming years, operations in low altitude airspace will vastly increase as the capabilities and applications of small Unmanned Aerial Systems (sUAS) continue to multiply. Therefore, solutions to managing sUAS in highly congested airspace must be explored. In this study, a Fuzzy Logic based approach was used to help mitigate the risk of collisions between aircraft using separation assurance and collision avoidance techniques. The system was evaluated for its effectiveness to mitigate the risk of mid-air collisions between aircraft. This system utilizes only current state information and can resolve potential conflicts without knowledge of intruder intent. The avoidance logic was verified using formal methods and shown to select the correct action in all instances. Additionally, the Fuzzy Logic Controllers were shown to always turn the vehicles in the correct direction. Numerical testing demonstrated that the avoidance system was able to prevent a mid-air collision between two sUAS in all tested cases. Simulations were also performed in a three-dimensional environment with a heterogenous fleet of sUAS performing a variety of realistic missions. Simulations showed that the system was 99.98 effective at preventing mid-air collisions when separation assurance was disabled (unmitigated case) and 100 effective when enabled (mitigated case).

Verification & Validation of a Fuzzy Logic Control↗

NASA NTRS2011

Collisional Processing of Comet Surfaces: Impact Experiments into Olivine

A new paradigm has emerged where 3.9 Ga ago, a violent reshuffling reshaped the placement of small bodies in the solar system (the Nice model). Surface properties of these objects may have been affected by collisions caused by this event, and by collisions with other small bodies since their emplacement. In addition, objects in the Kuiper Belt are believed to undergo extensive collisional processing while in the Kuiper Belt. Physical manifestations of shock effects (e.g., planar dislocations) in minerals typically found in comets will be correlated with spectral changes (e.g. reddening, loss and shift of peaks, new signatures) to allow astronomers to better understand geophysical impact processing that has occurred on small bodies. Targets will include solid and granular olivine (forsterite), impacted over a range of impact speeds with the Experimental Impact Laboratory at NASA JSC. Analyses include quantification of the dependence of the spectral changes with respect to impact speed, texture of the target, and temperature.

Lederer, S. M.↗

NASA NTRS2012

Collisional Processing of Comet and Asteroid Surfaces: Velocity Effects on Absorption Spectra

A new paradigm has emerged where 3.9 Gyr ago, a violent reshuffling reshaped the placement of small bodies in the solar system (the Nice model). Surface properties of these objects may have been affected by collisions caused by this event, and by collisions with other small bodies since their emplacement. These impacts affect the spectrographic observations of these bodies today. Shock effects (e.g., planar dislocations) manifest in minerals allowing astronomers to better understand geophysical impact processing that has occurred on small bodies. At the Experimental Impact Laboratory at NASA Johnson Space Center, we have impacted forsterite and enstatite across a range of velocities. We find that the amount of spectral variation, absorption wavelength, and full width half maximum of the absorbance peaks vary non-linearly with the velocity of the impact. We also find that the spectral variation increases with decreasing crystal size (single solid rock versus granular). Future analyses include quantification of the spectral changes with different impactor densities, temperature, and additional impact velocities. Results on diopside, fayalite, and magnesite can be found in Lederer et al., this meeting.

Lederer, S. M.↗