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NASA NTRS2022

TruePAL – An AI Assistant for First Responder Safety

This paper presents the development of an AI assistant, Trusted and Explainable Artificial Intelligence for Saving Lives (TruePAL), to provide real-time warning of risks of potential crashes to the first responders. The TruePAL system employs an AI and deep learning technology for saving first responders and roadside crews lives in and around active traffic. A deep neural network (DNN) and a Non-Axiomatic Reasoning System (NARS) are implemented as an AI system. A mobile app with AI interface is developed to perform verbal communication with the first responders. The TruePAL team has developed an explainable AI approach by opening up the DNN blackbox to extract the activation filters of various features and parts of the targeted objects. The combination of DNN and NARS makes the TruePAL system explainable to the users. TruePAL ingests on-board cameras, radar, and other sensor signals, analyzes the environment and traffic patterns to generate timely warning to drivers and roadside crews to avoid crashes. The TruePAL team, in collaboration with the Miami/Dade Police Dept., has designed five use cases and multiple sub-scenarios in a CARLA driving simulator to test the capability of TruePAL in timely warning to the first responder drivers in potential crash scenarios. We have successfully demonstrated its capability of timely warning in over a dozen scenarios based on the use cases. The preliminary test simulation results show that TruePAL could provide the drivers and crew members advanced warning before a crash occurs.

Chow, Edward↗
NASA NTRS2004

Designing Agent Collectives For Systems With Markovian Dynamics

The Collective Intelligence (COIN) framework concerns the design of collectives of agents so that as those agents strive to maximize their individual utility functions, their interaction causes a provided world utility function concerning the entire collective to be also maximized. Here we show how to extend that framework to scenarios having Markovian dynamics when no re-evolution of the system from counter-factual initial conditions (an often expensive calculation) is permitted. Our approach transforms the (time-extended) argument of each agent's utility function before evaluating that function. This transformation has benefits in scenarios not involving Markovian dynamics of an agent's utility function are observable. We investigate this transformation in simulations involving both hear and quadratic (nonlinear) dynamics. In addition, we find that a certain subset of these transformations, which result in utilities that have low opacity (analogous to having high signal to noise) but are not factored (analogous to not being incentive compatible), reliably improve performance over that arising with factored utilities. We also present a Taylor Series method for the fully general nonlinear case.

Wolpert, David H.↗
NASA NTRS2009

Ground/Flight Correlation of Aerodynamic Loads with Structural Response

Ground and flight tests provide a basis and methodology for in-flight characterization of the aerodynamic and structural performance through the monitoring of the fluid-structure interaction. The NF-15B flight tests of the Intelligent Flight Control System program provided a unique opportunity to test the correlation of aerodynamic loads with points of flow attaching and detaching from the surface, which are also known as flow bifurcation points, as observed in a previous wind tunnel test performed at the U.S. Air Force Academy (Colorado Springs, Colorado). Moreover, flight tests, along with the subsequent unsteady aerodynamic tests in the NASA Transonic Dynamics Tunnel (TDT), provide a basis using surface flow sensors as means of assessing the aeroelastic performance of flight vehicles. For the flight tests, the NF-15B tail was instrumented with hot-film sensors and strain gages for measuring root-bending strains. This data were gathered via selected sideslip maneuvers performed at level flight and subsonic speeds. The aerodynamic loads generated by the sideslip maneuver resulted in a structural response, which were then compared with the hot-film sensor signals. The hot-film sensor signals near the stagnation region were found to be highly correlated with the root-bending strains. For the TDT tests, a flexible wing section developed under the U.S. Air Force Research Lab SensorCraft program was instrumented with strain gages, accelerometers, and hot-film sensors at two span stations. The TDT tests confirmed the correlation between flow bifurcation points and the wing structural response to tunnel-generated gusts. Furthermore, as the wings structural modes were excited by the gusts, a gradual phase change between the flow bifurcation point and the structural mode occurred during a resonant condition.

Mangalam, Arun S.↗
NASA NTRS2001

Designing Agent Collectives For Systems With Markovian Dynamics

The "Collective Intelligence" (COIN) framework concerns the design of collectives of agents so that as those agents strive to maximize their individual utility functions, their interaction causes a provided "world" utility function concerning the entire collective to be also maximized. Here we show how to extend that framework to scenarios having Markovian dynamics when no re-evolution of the system from counter-factual initial conditions (an often expensive calculation) is permitted. Our approach transforms the (time-extended) argument of each agent's utility function before evaluating that function. This transformation has benefits in scenarios not involving Markovian dynamics, in particular scenarios where not all of the arguments of an agent's utility function are observable. We investigate this transformation in simulations involving both linear and quadratic (nonlinear) dynamics. In addition, we find that a certain subset of these transformations, which result in utilities that have low "opacity (analogous to having high signal to noise) but are not "factored" (analogous to not being incentive compatible), reliably improve performance over that arising with factored utilities. We also present a Taylor Series method for the fully general nonlinear case.

Wolpert, David H.↗
NASA NTRS1993

PTTI-aided ephemeris calculation and rapid data link acquisition for manned space flight

Complexity of future manned space flight mission control can be significantly reduced by integrating GPS, the PTTI source, into telemetry, tracking, and command (TT&C). Future telecommunications, space tracking electronic intelligence, metrology, navigation, and data acquisition will thereby be served, including: on-board ephemeris determination, reduced synchronization time for time division multiple access (TDMA) links, and in-flight clock calibration, increasing on-board autonomy and reducing ground support costs. Manned space transportation through the first quarter of the 21st century will probably depend on a mix of vehicles, including the Advanced Manned Launch System (AMLS), the Personnel Launch System (PLS), and continued use of the Shuttle Fleet. Precise Ephemeris is important on-board for mission success, status monitoring, also for rendezvous and docking. Use of GPS can eliminate ground based tracking/processing, enhancing autonomy and reducing communications bandwidth. GPS time can simplify complicated functions used in bandwidth efficient time division multiple access (TDMA) communications, such as: precise and realtime synchronization of receive reference timing, transmit-timing and acquisition control, unique synchronization word (UW) detection, and elastic buffering. High clock accuracy provides increased signal-to-noise (S/N) ratio during acquisition, permitting narrower acquisition frequency and time windows. Spaceborne systems requirements to provide capabilities such as: refinement of the GEM-72 gravity model based on satellite tracking observations from ATS-6 to GEOS-3, relativistic clock experiments, NASA crustal dynamics program for developing space geodetic techniques to study the earth's crust, its gravity field, and earthquake mechanisms, and multi-disciplinary space geodetic tracking for studying global climatic changes are also reviewed.

Anderman, Alfred↗
NASA NTRS1989

A design philosophy for multi-layer neural networks with applications to robot control

A system is proposed which receives input information from many sensors that may have diverse scaling, dimension, and data representations. The proposed system tolerates sensory information with faults. The proposed self-adaptive processing technique has great promise in integrating the techniques of artificial intelligence and neural networks in an attempt to build a more intelligent computing environment. The proposed architecture can provide a detailed decision tree based on the input information, information stored in a long-term memory, and the adapted rule-based knowledge. A mathematical model for analysis will be obtained to validate the cited hypotheses. An extensive software program will be developed to simulate a typical example of pattern recognition problem. It is shown that the proposed model displays attention, expectation, spatio-temporal, and predictory behavior which are specific to the human brain. The anticipated results of this research project are: (1) creation of a new dynamic neural network structure, and (2) applications to and comparison with conventional multi-layer neural network structures. The anticipated benefits from this research are vast. The model can be used in a neuro-computer architecture as a building block which can perform complicated, nonlinear, time-varying mapping from a multitude of input excitory classes to an output or decision environment. It can be used for coordinating different sensory inputs and past experience of a dynamic system and actuating signals. The commercial applications of this project can be the creation of a special-purpose neuro-computer hardware which can be used in spatio-temporal pattern recognitions in such areas as air defense systems, e.g., target tracking, and recognition. Potential robotics-related applications are trajectory planning, inverse dynamics computations, hierarchical control, task-oriented control, and collision avoidance.

Vadiee, Nader↗
NASA NTRS2010

High-Speed Ring Bus

The high-speed ring bus at the Jet Propulsion Laboratory (JPL) allows for future growth trends in spacecraft seen with future scientific missions. This innovation constitutes an enhancement of the 1393 bus as documented in the Institute of Electrical and Electronics Engineers (IEEE) 1393-1999 standard for a spaceborne fiber-optic data bus. It allows for high-bandwidth and time synchronization of all nodes on the ring. The JPL ring bus allows for interconnection of active units with autonomous operation and increased fault handling at high bandwidths. It minimizes the flight software interface with an intelligent physical layer design that has few states to manage as well as simplified testability. The design will soon be documented in the AS-1393 standard (Serial Hi-Rel Ring Network for Aerospace Applications). The framework is designed for "Class A" spacecraft operation and provides redundant data paths. It is based on "fault containment regions" and "redundant functional regions (RFR)" and has a method for allocating cables that completely supports the redundancy in spacecraft design, allowing for a complete RFR to fail. This design reduces the mass of the bus by incorporating both the Control Unit and the Data Unit in the same hardware. The standard uses ATM (asynchronous transfer mode) packets, standardized by ITU-T, ANSI, ETSI, and the ATM Forum. The IEEE-1393 standard uses the UNI form of the packet and provides no protection for the data portion of the cell. The JPL design adds optional formatting to this data portion. This design extends fault protection beyond that of the interconnect. This includes adding protection to the data portion that is contained within the Bus Interface Units (BIUs) and by adding to the signal interface between the Data Host and the JPL 1393 Ring Bus. Data transfer on the ring bus does not involve a master or initiator. Following bus protocol, any BIU may transmit data on the ring whenever it has data received from its host. There is no centralized arbitration or bus granting. The JPL design provides for autonomous synchronization of the nodes on the ring bus. An address-synchronous latency adjust buffer (LAB) has been designed that cannot get out of synchronization and needs no external input. Also, a priority-driven cable selection behavior has been programmed into each unit on the ring bus. This makes the bus able to connect itself up, according to a maximum redundancy priority system, without the need for computer intervention at startup. Switching around a failed or switched-off unit is also autonomous. The JPL bus provides a map of all the active units for the host computer to read and use for fault management. With regard to timing, this enhanced bus recognizes coordinated timing on a spacecraft as critical and addresses this with a single source of absolute and relative time, which is broadcast to all units on the bus with synchronization maintained to the tens of nanoseconds. Each BIU consists of up to five programmable triggers, which may be programmed for synchronization of events within the spacecraft of instrument. All JPL-formatted data transmitted on the ring bus are automatically time-stamped.

Wysocky, Terry↗
NASA NTRS2010

Physics-Based Methods of Failure Analysis and Diagnostics in Human Space Flight

The Integrated Health Management (IHM) for the future aerospace systems requires to interface models of multiple subsystems in an efficient and accurate information environment at the earlier stages of system design. The complexity of modern aeronautic and aircraft systems (including e.g. the power distribution, flight control, solid and liquid motors) dictates employment of hybrid models and high-level reasoners for analysing mixed continuous and discrete information flow involving multiple modes of operation in uncertain environments, unknown state variables, heterogeneous software and hardware components. To provide the information link between key design/performance parameters and high-level reasoners we rely on development of multi-physics performance models, distributed sensors networks, and fault diagnostic and prognostic (FD&P) technologies in close collaboration with system designers. The main challenges of our research are related to the in-flight assessment of the structural stability, engine performance, and trajectory control. The main goal is to develop an intelligent IHM that not only enhances components and system reliability, but also provides a post-flight feedback helping to optimize design of the next generation of aerospace systems. Our efforts are concentrated on several directions of the research. One of the key components of our strategy is an innovative approach to the diagnostics/prognostics based on the real time dynamical inference (DI) technologies extended to encompass hybrid systems with hidden state trajectories. The major investments are into the multiphysics performance modelling that provides an access of the FD&P technologies to the main performance parameters of e.g. solid and liquid rocket motors and composite materials of the nozzle and case. Some of the recent results of our research are discussed in this chapter. We begin by introducing the problem of dynamical inference of stochastic nonlinear models and reviewing earlier results. Next, we present our analytical approach to the solution of this problem based on the path integral formulation. The resulting algorithm does not require an extensive global search for the model parameters, provides optimal compensation for the effects of dynamical noise, and is robust for a broad range of dynamical models. In the following Section the strengths of the algorithm are illustrated illustrated by inferring the parameters of the stochastic Lorenz system and comparing the results with those of earlier research. Next, we discuss a number of recent results in application to the development of the IHM for aerospace system. Firstly, we apply dynamical inference approach to a solution of classical three tank problems with mixed unknown continuous and binary parameters. The problem is considered in the context of ground support system for filling fuel tanks of liquid rocket motors. It is shown that the DI algorithm is well suited for successful solution of a hybrid version of this benchmark problem even in the presence of additional periodic and stochastic perturbation of unknown strength. Secondly, we illustrate our approach by its application to an analysis of the nozzle fault in a solid rocket motor (SRM). The internal ballistics of the SRM is modelled as a set of one-dimensional partial differential equations coupled to the dynamics of the propellant regression. In this example we are specifically focussed on the inference of discrete and continuous parameters of the nozzle blocking fault and on the possibility of an application of the DI algorithm to reducing the probability of "misses" of an on-board FD&P for SRM. In the next section re-contact problem caused by first stage/upper stage separation failure is discussed. The reaction forces imposed on the nozzle of the upper stage during the re-contact and their connection to the nozzle damage and to the thrust vector control (TVC) signal are obtained. It is shown that transient impact induced torquean be modelled as a response of an effective damped oscillator. A possible application of the DI algorithm to the inference of damage parameters and predicting fault dynamics ahead of time using the actuator signal is discussed. Finally, we formulate Bayesian inferential framework for development of the IHM system for in-flight structural health monitoring (SHM) of composite materials. We consider the signal generated by piezoelectric actuator mounted on composite structure generating elastic waves in it. The signal received by the sensor is than compared with the baseline signal. The possibility of damage inference is discussed in the context of development of the SHM.

Smelyanskiy, Vadim N.↗
NASA NTRSDate not supplied

Unlocking the Mysteries of the Moon’s Shadowed Regions

The Moon poles host large quantities of water-ice deposits in the permanently shadowed regions (PSRs), which are vital for enabling sustainable human space exploration, making these regions high-priority targets for upcoming Artemis missions [1]. Unfortunately, today, the best available orbital lunar imagery [2, 3] lacks the meter-scale resolution and signal needed to understand the geomorphology and trafficability of PSRs, complicating the planning and execution of future missions seeking to explore PSRs. We have developed an image enhancement tool called HORUS (Hyper-effective nOise Removal Unet Software) [4, 5], designed to enhance LRO Narrow-Angle Camera (NAC) optical low-light imagery of permanently shadowed regions by effectively removing the CCD-related, photon, and other residual noises that corrupt the images. The tool is composed of two deep learning neural networks trained on environmental metadata and real and synthetic imagery, the latter generated by a physical noise model (LROC). We demonstrated that HORUS effectively produces low-noise, high-resolution images (~1.5m/px), achieving a 5 to 10x improvement over existing long-exposure images of PSRs. HORUS allows scientists and engineers to identify geomorphic features (e.g., craters and boulders) in shadowed regions as small as 3 meters across as well as to peek inside of small shadowed regions, for the first time. The tool was deployed and thoroughly validated for NASA's VIPER mission [6], where it was applied to 20 candidate target regions across the lunar South Pole. Additionally, we conducted different approaches to validate the resulting HORUS-processed images. With HORUS denoised images, VIPER scientists can increase their confidence on what surface features (previously unseen) exist in the shadowed regions, helping them plan rover traverses more safely and efficiently (e.g., Fig. 1) In this manuscript, we will describe how VIPER scientists are utilizing HORUS denoised images to extract new information from the terrain and increase their confidence in what surface features exist in the shadowed regions. In combination with other high-resolution images and digital elevation maps, HORUS images are helping the team analyze potential lading and science sites, as well as planning traverses more safely and efficiently (e.g., Fig. 1). Additionally, we will describe how HORUS tool unlocks a broad range of scientific and exploration applications to other Artemis and CPLS missions to the lunar poles, including (but not limited to) geomorphic analysis, change detection, surface hazard detection, and terrain relative navigation.

artificial intelligence↗