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At least 127 records · Page 7

Operator Trust Function for Predicted Drone Arrival

To realize the full benefit from autonomy, systems will have to react to unknown events and uncertain dynamic environments. The resulting number of behaviors is essentially infinite; thus, the system is effectively non-deterministic but an operator needs to understand and trust the actions of the autonomous vehicles. This research began to tackle non-deterministic systems and trust by beginning to develop a user trust function based on intent information displayed and the prescribed bounds on allowable behaviors/actions of the non-deterministic system. Linear regression shows promise on being able to predict a person’s confidence of the machine’s prediction. Linear regression techniques indicated that subject characteristics, scenario difficulty, the experience with the system, and confidence earlier in the scenario account for approximately 60% of the variation in confidence ratings. This paper details the specifics of the liner regression model – essentially a trust function – for predicting a person’s confidence.

Trujillo, Anna C.↗

Recovering from On-orbit Anomalies on the Astrobee Free Flyers and its Systems

Since 2019, NASA has been operating three Astrobee free flying robots on board the International Space Station (ISS) providing an autonomous and flexible research platform for national and international payload developers in microgravity and serving as a robotic assistant for astronauts on the ISS. During its use on the ISS, in particular with over 750 hours of free-flyer operation as of March 2022, Astrobee and its Docking Station have encountered multiple software and hardware anomalies. These anomalies were either resolved remotely via software and firmware updates, or, where not possible, with hardware replacements on orbit or by the return of the faulty unit to NASA’s ground facilities for its repair. Despite being inherently designed to be repaired or replaced on orbit, Astrobee and its systems can still suffer anomalies that would be complex enough to disassemble, cause risks of hardware damage, or use excessive crew time to perform the repair in orbit. That was the case for the anomaly the Astrobee unit ‘Honey’ encountered, reason why it needed to be down-massed for repair. One of the most common points of failure was found to be the SD card, which is used for the different Astrobee processors and for the Dock Station. Other comparable SD card anomalies were found also on the Astrobee ground units, which provided useful data in the effort of upgrading their systems. This presentation will focus on 1) The overview of the different faults and anomalies on Astrobee and its systems on orbit and on the ground 2) The processes and procedures implemented to resolve the anomalies 3) The implementation of software updates and hardware upgrades in order to reduce the risk on returning anomalies 4) The lessons learned in increasing Astrobee’s robustness and resilience to such anomalies.

International Space Station↗

Certification Concepts for AI/ML Systems

This presentation goes over some of the tools developed at NASA Ames in the Robust Software Engineering group for the assurance and certification of autonomous systems. The research themes presented include improving safety and risk assessment as early as possible in the lifecycle, elicitation and formalization of requirements to facilitate traceability throughout the lifecycle, especially when formal methods are used, algorithms, tools and techniques for the V&V of ML-enabled systems, advanced testing, use of runtime monitoring to ease use of untrusted components, and contribution to draft regulatory standards and assistance in producing and presenting certification evidences.

Autonomy↗

Simple Pattern Traffic Generation for Automated Flight Research in Non-Towered Traffic Patterns

Research efforts into autonomous air traffic will necessitate tools for testing algorithm capabilities. Testing will require flexible methods for creating large quantities of artificial data to verify the safety of automated systems. The traffic generation method in this work was developed to test traffic prediction and replanning algorithms for an autonomous vehicle attempting to land at a non-towered airport. The traffic generation method produces airport approach trajectories supporting a wide range of pattern entry types and typical pattern modification maneuvers for multiple aircraft types with varying performance capabilities. For each aircraft there are options for choosing the approach type, modifying how the approach is flown, and imposing scenario-driven temporal constraints, such as spacing between pairs of aircraft. The tool uses simplified aircraft dynamics to produce position and velocity profiles for traffic vehicles. Additionally, the tool supports standalone simulation tests or batch/bulk testing efforts, multiple output data options, and facilitates post-processing analysis.

Autonomous Vehicle↗

Intelligent Surrogate Model Development: Boosting Computational Efficiency for Autonomous Control of Advanced Reactors

Advanced reactors promise enhanced safety, greater efficiency, and waste reductions. To fully realize these benefits, it is crucial to address the need for autonomous or semi-autonomous control systems that require fewer operators. This research primarily supports the MARVEL autonomous control system, which requires real-time operation. However, the current RELAP5 reactor thermal hydraulic transient simulation is excessively time-consuming. Therefore, this study aims to leverage deep learning techniques to develop a surrogate model, providing a more efficient and accurate alternative for real-time performance. The model was trained using a combination of one-timestep prediction and scheduled sampling. It was then used for recursive prediction of the reactor state. This developed surrogate model significantly improves computational efficiency, achieving a 12 times acceleration.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

A perspective on Bayesian methods applied to materials discovery and design

For more than two decades, there has been increasing interest in developing frameworks for the accelerated discovery and design of novel materials that could enable promising and transformative technologies. The Integrated Computational Materials Engineering (ICME) program called for integrating computational tools to establish linkages along process-structure-property-performance (PSPP) chains. The Materials Genome Initiative called for integrating experiments and computations within data science frameworks as a strategy to accelerate the materials development cycle. While these frameworks and paradigms have been quite influential, traditional ICME or data science-based approaches tend to have some limitations, mainly when querying the materials space is costly and very little information is available. Bayesian methods are more suitable in this context due to their efficiency gains. To this end, the materials discovery problem is framed as a Bayesian Optimization (BO). Different examples in which BO has been applied to solve materials discovery problems are presented. The methods/examples discussed include BO under model uncertainty, multi-information source BO, multi-objective and multi-constraint BO, and batch BO. Bayesian Materials Discovery is a promising area of research that is likely to become more influential as more attention is put on autonomous materials discovery platforms. Therefore, a discussion is provided on the potential development of such methods to increase the ability of existing platforms in materials discovery. Here, the ultimate goal is to pave the way to autonomous materials discovery.

36 MATERIALS SCIENCE↗

HCPerf: Driving Performance-Directed Hierarchical Coordination for Autonomous Vehicles

The rapid development of autonomous driving poses new research challenges to the on-vehicle computing system. In particular, the execution time of autonomous driving tasks highly depends on the specific driving environment. For instance, the execution time of configurable sensor fusion increases significantly as the scene becomes complex, which leads to end-to-end deadline misses from sensing to control and may cause accidents. Thus, a framework that can effectively utilize the system resources to guarantee the end-to-end deadlines of autonomous driving tasks as well as effectively prioritize the responsiveness and throughput of the control commands is crucial for autonomous driving. In this paper, we propose HCPerf, a performance-directed hierarchical coordination framework that intelligently coordinates the autonomous driving tasks with high execution time variation and complex dependencies according to the driving performance in real-time. Specifically, HCPerf mainly consists of two coordinators. The internal coordinator intelligently schedules the tasks according to the driving performance of the vehicle in order to help them meet the end-to-end deadlines while well prioritizing the responsiveness and throughput of the control commands. At the same time, the external coordinator dynamically tunes the rates of tasks according to the schedulability in order to efficiently utilize the system resource. We conduct extensive experiments on both simulation and hardware testbeds with the representative autonomous driving application. The results show that HCPerf can effectively improve the driving performance by 7.69%-45.94% in different driving scenarios.

Ma, Jialiang↗

AssistTaxi: A Comprehensive Dataset for Taxiway Analysis and Autonomous Operations

The availability of high-quality datasets play a crucial role in advancing research and development especially, for safety critical and autonomous systems. This poster presents AssistTaxi, which is a comprehensive novel dataset which is a collection of images for runway and taxiway analysis. The dataset comprises of more than 300,000 frames of diverse and carefully collected data, gathered from Melbourne (MLB) and Grant-Valkaria (X59) general aviation airports. The importance of AssistTaxi lies in its potential to advance autonomous operations, enabling researchers and developers to train and evaluate algorithms for efficient and safe taxiing. Researchers can utilize AssistTaxi to benchmark their algorithms, assess performance, and explore novel approaches for runway and taxiway analysis. Additionally, the dataset serves as a valuable resource for validating and enhancing existing algorithms as well as facilitating innovation in autonomous operations for aviation. We also propose an initial approach to label the dataset using a contour based detection and line extraction technique.

Data Collection↗

Space Station module Power Management And Distribution (PMAD) system

This project consists of several tasks which are unified toward experimentally demonstrating the operation of a highly autonomous, user-supportive power management and distribution system for Space Station Freedom (SSF) habitation/laboratory modules. This goal will be extended to a demonstration of autonomous, cooperative power system operation for the whole SSF power system through a joint effort with NASA's Lewis Research Center, using their Autonomous Power System. Short term goals for the space station module power management and distribution include having an operational breadboard reflecting current plans for SSF, improving performance of the system communications, and improving the organization and mutability of the artificial intelligence (AI) systems. In the middle term, intermediate levels of autonomy will be added, user interfaces will be modified, and enhanced modeling capabilities will be integrated in the system. Long term goals involve conversion of all software into Ada, vigorous verification and validation efforts and, finally, seeing an impact of this research on the operation of SSF. Conversion of the system to a DC Star configuration is now in progress, and should be completed by the end of October, 1989. This configuration reflects the latest SSF module architecture. Hardware is now being procured which will improve system communications significantly. The Knowledge-Based Management System (KBMS) is initially developed and the rules from FRAMES have been implemented in the KBMS. Rules in the other two AI systems are also being grouped modularly, making them more tractable, and easier to eventually move into the KBMS. Adding an intermediate level of autonomy will require development of a planning utility, which will also be built using the KBMS. These changes will require having the user interface for the whole system available from one interface. An Enhanced Model will be developed, which will allow exercise of the system through the interface without requiring all of the power hardware to be operational. The functionality of the AI systems will continue to be advanced, including incipient failure detection. Ada conversion will begin with the lowest level processor (LLP) code. Then selected pieces of the higher level functionality will be recorded in Ada and, where possible, moved to the LLP level. Validation and verification will be done on the Ada code, and will complete sometimes after completion of the Ada conversion.

Walls, Bryan↗

An Architecture to Enable Autonomous Control of Spacecraft

Autonomy is required for manned spacecraft missions distant enough that light-time communication delays make ground-based mission control infeasible. Presently, ground controllers develop a complete schedule of power modes for all spacecraft components based on a large number of factors. The proposed architecture is an early attempt to formalize and automate this process using on-vehicle computation resources. In order to demonstrate this architecture, an autonomous electrical power system controller and vehicle Mission Manager are constructed. These two components are designed to work together in order to plan upcoming load use as well as respond to unanticipated deviations from the plan. The communication protocol was developed using "paper" simulations prior to formally encoding the messages and developing software to implement the required functionality. These software routines exchange data via TCP/IP sockets with the Mission Manager operating at NASA Ames Research Center and the autonomous power controller running at NASA Glenn Research Center. The interconnected systems are tested and shown to be effective at planning the operation of a simulated quasi-steady state spacecraft power system and responding to unexpected disturbances.

space power systems↗

Pilot in Command: An Illustration of Autonomous Flight Management

Several years of NASA research have produced the concept for air traffic management called "Distributed Air/Ground Traffic Management," a major operational advancement that should significantly increase the capacity of the National Airspace System. A key component, "Autonomous Flight Management," introduces a new class of aircraft operations in which pilots are authorized to freely maneuver and execute optimal trajectories independent from air traffic controllers. These aircraft operators would benefit from significant increases in flexibility to optimize all flight operations and from avoiding most of the delays associated with ground-controlled operations. Responsibilities for aircraft separation and arrival flow conformance are transferred to the flight deck, and the pilots use computerized decision-support tools to accomplish these tasks. A research prototype of these tools called the "Autonomous Operations Planner" is being developed at the NASA Langley Research Center. This 14-minute video illustrates Autonomous Flight Management from the airline pilot's perspective.

Wing, David J.↗

A mission executor for an autonomous underwater vehicle

The Naval Postgraduate School has been conducting research into the design and testing of an Autonomous Underwater Vehicle (AUV). One facet of this research is to incrementally design a software architecture and implement it in an advanced testbed, the AUV II. As part of the high level architecture, a Mission Executor is being constructed using CLIPS (C Language Integrated Production System) version 5.0. The Mission Executor is an expert system designed to oversee progress from the AUV launch point to a goal area and back to the origin. It is expected that the executor will make informed decisions about the mission, taking into account the navigational path, the vehicle subsystem health, and the sea environment, as well as the specific mission profile which is downloaded from an offboard mission planner. Heuristics for maneuvering, avoidance of uncharted obstacles, waypoint navigation, and reaction to emergencies (essentially the expert knowledge of a submarine captain) are required. Many of the vehicle subsystems are modeled as objects using the CLIPS Object Oriented Language (COOL) embedded in CLIPS 5.0. Also, truth maintenance is applied to the knowledge base to keep configurations updated.

Lee, Yuh-Jeng↗

Use of Traffic Intent Information by Autonomous Aircraft in Constrained Operations

This paper presents findings of a research study designed to provide insight into the issue of intent information exchange in constrained en-route air-traffic operations and its effect on pilot decision-making and flight performance. The piloted simulation was conducted in the Air Traffic Operations Laboratory at the NASA Langley Research Center. Two operational modes for autonomous flight management were compared under conditions of low and high operational complexity (traffic and airspace hazard density). The tactical mode was characterized primarily by the use of traffic state data for conflict detection and resolution and a manual approach to meeting operational constraints. The strategic mode involved the combined use of traffic state and intent information, provided the pilot an additional level of alerting, and allowed an automated approach to meeting operational constraints. Operational constraints applied in the experiment included separation assurance, schedule adherence, airspace hazard avoidance, flight efficiency, and passenger comfort. The strategic operational mode was found to be effective in reducing unnecessary maneuvering in conflict situations where the intruder's intended maneuvers would resolve the conflict. Conditions of high operational complexity and vertical maneuvering resulted in increased proliferation of conflicts, but both operational modes exhibited characteristics of stability based on observed conflict proliferation rates of less than 30 percent. Scenario case studies illustrated the need for maneuver flight restrictions to prevent the creation of new conflicts through maneuvering and the need for an improved user interface design that appropriately focuses the pilot's attention on conflict prevention information. Pilot real-time assessment of maximum workload indicated minimal sensitivity to operational complexity, providing further evidence that pilot workload is not the limiting factor for feasibility of an en-route distributed traffic management system, even under highly constrained conditions.

Wing, David J.↗

Enabling Modular Autonomous Feedback‐Loops in Materials Science through Hierarchical Experimental Laboratory Automation and Orchestration

Abstract Materials acceleration platforms (MAPs) operate on the paradigm of integrating combinatorial synthesis, high‐throughput characterization, automatic analysis, and machine learning. Within a MAP, one or multiple autonomous feedback loops may aim to optimize materials for certain functional properties or to generate new insights. The scope of a given experiment campaign is defined by the range of experiment and analysis actions that are integrated into the experiment framework. Herein, the authors present a method for integrating many actions within a hierarchical experimental laboratory automation and orchestration (HELAO) framework. They demonstrate the capability of orchestrating distributed research instruments that can incorporate data from experiments, simulations, and databases. HELAO interfaces laboratory hardware and software distributed across several computers and operating systems for executing experiments, data analysis, provenance tracking, and autonomous planning. Parallelization is an effective approach for accelerating knowledge generation provided that multiple instruments can be effectively coordinated, which the authors demonstrate with parallel electrochemistry experiments orchestrated by HELAO. Efficient implementation of autonomous research strategies requires device sharing, asynchronous multithreading, and full integration of data management in experimental orchestration, which to the best of the authors’ knowledge, is demonstrated for the first time herein.

36 MATERIALS SCIENCE↗

Stimulus specificity and individual stereotypy of autonomic responses to motion stressors

Motion sickness research shows a lack of agreement regarding the contribution of the autonomic nervous system (ANS). The resolution of this question is exigent for Space Adaptation Syndrome, zero gravity sickness. A case is drawn for the necessity to apply a methodological approach that incorporates: (1) standardization of parameters in relation to the individual differences in variability and prestimulus levels; (2) a concern for patterning of responses; and (3) the physiological association with subjective reports. Vasomotor, heart rate, respiration rate, skin conductance and subjective reports of malaise were collected from 22 subjects while participating in three motion stressors; vertical acceleration, Coriolis stimulation, and combined optokinetic and Coriolis stimulation. The results demonstrate that ANS response patterns can be separated into three mutually exclusive components: (1) a generalized response to motion sickness; (2) a stimulus specific response to the type of stressor being presented; and (3) individualized stereotypical response patterns that are associated with subjective reports of malaise.

Morgan, M. G.↗

Advances in Autonomous Communications and Operations: Tes-N Series

Advances in nanosat subsystems over the past decade have taken the CubeSat standard from a communication-limited educational tool to a powerful platform enabling space research. The potential for autonomous operations may greatly increase the capability of downlinking even larger data sets. This is enabled through miniaturization of software-defined radio/cognitive communication solutions and a rapidly growing number of ground stations and satellite network crosslinks. The TechEdSat-n orbital flight series is currently demonstrating experiments using cognitive communication concepts including User Initiated Service (UIS) and High-rate Delay Tolerant Networks (HDTN), which show a significant step toward improved capability. At the core of this is the use of the Iridium L-band Short Burst Data (SBD) modems, pioneered by TES-n for space applications. SBD enables unique rapid command, control, and scheduling to initiate the UIS and HDTN protocols. This occurs by performing GPS-assisted on-orbit ephemeris determination, enabling negotiation with high bandwidth ground assets to repeatedly downlink over a specific commercial or government-owned ground station. The technique is RF band-agnostic and may be extended to higher bandwidth stations and SDRs. This may also include free-space optical communication, through both laser and omnidirectional LEDs, which can provide an attractive protocol for downlinking very large datasets over far fewer ground stations. In addition, this may be extended to lunar applications for such future concepts as LunaNet, whereby scheduling and cognitive technologies can assist in greatly improving Earth downlink capabilities with ground stations which will see greater competition for usage. Lastly, the NASA Communication Service Program (CSP), intended to eventually replace the NASA Tracking and Data Relay Satellite System (TDRSS) will also demonstrate the feasibility of commercially-provided satellite communication capabilities. All of these combined advances, including large advances in on-board computation on small platforms, will result in more remarkable data processing capability – yielding even more as of yet unknown discoveries.

Autonomy↗

Cardiac Autonomic Effects of Acute Exposures to Airborne Particulates in Men and Women

The aim of this research was to investigate cardiac autonomic changes associated with acute exposures to airborne particulates. Methods: High fidelity 12-lead ECG (CardioSoft, Houston, TX) was acquired from 19 (10 male / 9 female) non-smoking volunteers (age 33.6 +/- 6.6 yrs) during 10 minutes pre-exposure, exposure and post-exposure to environmental tobacco smoke (ETS), cooking oil fumes, wood smoke and sham (water vapor). To control exposure levels, noise, subject activity, and temperature, all studies were conducted inside an environmental chamber. Results: The short-term fractal scaling exponent (Alpha-1) and the ratio of low frequency to high frequency Heart Rate Variability (HRV) powers (LF/HF, a purported sympathetic index) were both higher in males (p<0.017 and p<0.05, respectively) whereas approximate entropy (ApEn) and HF/(LF+HF) (a purported parasympathetic index) were both lower in males (p<0.036, and p<0.044, respectively). Compared to pre-exposure (p<0.0002) and sham exposure (p<0.047), male heart rates were elevated during early ETS post-exposure. Our data suggest that, in addition to tonic HRV gender differences, cardiac responses to some acute airborne particulates are gender related.

Howarth, M. S.↗

The Personal Satellite Assistant: An Internal Spacecraft Autonomous Mobile Monitor

This paper presents an overview of the research and development effort at the NASA Ames Research Center to create an internal spacecraft autonomous mobile monitor capable of performing intra-vehicular sensing activities by autonomously navigating onboard the International Space Station. We describe the capabilities, mission roles, rationale, high-level functional requirements, and design challenges for an autonomous mobile monitor. The rapid prototyping design methodology used, in which five prototypes of increasing fidelity are designed, is described as well as the status of these prototypes, of which two are operational and being tested, and one is actively being designed. The physical test facilities used to perform ground testing are briefly described, including a micro-gravity test facility that permits a prototype to propel itself in 3 dimensions with 6 degrees-of-freedom as if it were in an micro-gravity environment. We also describe an overview of the autonomy framework and its components including the software simulators used in the development process. Sample mission test scenarios are also described. The paper concludes with a discussion of future and related work followed by the summary.

Dorais, Gregory A.↗