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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Assurance of Model-Based Fault Diagnosis

Autonomy is an increasingly important technology for robotic scientific and commercial spacecraft. An important motivation for developing onboard autonomy is to enable quick response to dynamic environment and situations, including fault conditions that a spacecraft may encounter. The reliability of such autonomous capabilities depends on the quality of their knowledge of a spacecraft’s health state. Model-based approaches to fault management, i.e. model-based fault diagnosis (MBFD), is one approach to continuously verify correct behavior in addition to diagnosing symptoms to estimate the spacecraft’s health state. The proper functioning of MBFD is dependent on 1) the quality of the model that is analyzed and compared to the outputs of onboard sensors to estimate the system’s health state, and 2) the correct functioning of the diagnosis engine that interrogates the model and compares its analysis to observed system behavior. We are currently developing Verification and Validation (V&V) approaches to provide the necessary confidence that MBFD systems are correctly estimating the health of on-board spacecraft components and systems. Our work is intended to narrow the gap between the rapidly maturing field of ModelBased System Engineering (including MBFD) and the less-well understood area of identifying and applying appropriate V&V techniques to MBFD. Our effort is investigating three areas: 1) developing V&V techniques for the diagnostic model, 2) developing V&V techniques for the diagnostic engine in isolation, and 3) developing V&V techniques for the diagnostic engine and model in combination. This paper describes the work we have completed in the first area. We describe our approach to selecting a system to be represented by a model, the approach to modeling the system, the verification approach we developed for the model, and the results of the verification activity. We conclude with a description of the work remaining in the last two areas, which will be addressed over the next two years.

Chung, Seung↗
NASA NTRS2003

Distributed real-time model-based diagnosis

This paper presents an approach to onboard anomaly diagnosis that combines the simplicity and real-time guarantee of a rule-based diagnosis system with the specification ease and coverage guarantees of a model-based diagnosis system.

autonomy diagnosis↗
NASA NTRS1992

Needs for supervised space robots in space exploration

The areas of application for space robots in the Space Exploration Initiative (SEI) are examined by reviewing the roles of SEI supervised robots particularly with planet-surface systems (PSSs). Treatment is given to both teleoperated conventional robot systems and autonomous intelligent systems for comparison in terms of safety, reliability, and productivity. Two development stages are proposed including one with a robotic actor, human observer, and a human supervisor and a second in which a closed-loop control and monitoring system is established. The use of remote control is shown to require robustness, self-calibration and -diagnosis, adjustable autonomy, and multitask capability. The requirements of intelligent control are also listed so that the PSSs of the SEI can be used to enable surface exploration, local-resource utilization potential, and reductions of human tasks.

Erickson, Jon D.↗
NASA NTRS2001

Architectures and Evaluation for Adjustable Control Autonomy for Space-Based Life Support Systems

In the past five years, a number of automation applications for control of crew life support systems have been developed and evaluated in the Adjustable Autonomy Testbed at NASA's Johnson Space Center. This paper surveys progress on an adjustable autonomous control architecture for situations where software and human operators work together to manage anomalies and other system problems. When problems occur, the level of control autonomy can be adjusted, so that operators and software agents can work together on diagnosis and recovery. In 1997 adjustable autonomy software was developed to manage gas transfer and storage in a closed life support test. Four crewmembers lived and worked in a chamber for 91 days, with both air and water recycling. CO2 was converted to O2 by gas processing systems and wheat crops. With the automation software, significantly fewer hours were spent monitoring operations. System-level validation testing of the software by interactive hybrid simulation revealed problems both in software requirements and implementation. Since that time, we have been developing multi-agent approaches for automation software and human operators, to cooperatively control systems and manage problems. Each new capability has been tested and demonstrated in realistic dynamic anomaly scenarios, using the hybrid simulation tool.

Malin, Jane T.↗
NASA NTRS2006

Adjustably Autonomous Multi-agent Plan Execution with an Internal Spacecraft Free-Flying Robot Prototype

We present an multi-agent model-based autonomy architecture with monitoring, planning, diagnosis, and execution elements. We discuss an internal spacecraft free-flying robot prototype controlled by an implementation of this architecture and a ground test facility used for development. In addition, we discuss a simplified environment control life support system for the spacecraft domain also controlled by an implementation of this architecture. We discuss adjustable autonomy and how it applies to this architecture. We describe an interface that provides the user situation awareness of both autonomous systems and enables the user to dynamically edit the plans prior to and during execution as well as control these agents at various levels of autonomy. This interface also permits the agents to query the user or request the user to perform tasks to help achieve the commanded goals. We conclude by describing a scenario where these two agents and a human interact to cooperatively detect, diagnose and recover from a simulated spacecraft fault.

Dorais, Gregory A.↗
NASA NTRS1987

Diagnosis: Reasoning from first principles and experiential knowledge

Completeness, efficiency and autonomy are requirements for suture diagnostic reasoning systems. Methods for automating diagnostic reasoning systems include diagnosis from first principles (i.e., reasoning from a thorough description of structure and behavior) and diagnosis from experiential knowledge (i.e., reasoning from a set of examples obtained from experts). However, implementation of either as a single reasoning method fails to meet these requirements. The approach of combining reasoning from first principles and reasoning from experiential knowledge does address the requirements discussed above and can possibly ease some of the difficulties associated with knowledge acquisition by allowing developers to systematically enumerate a portion of the knowledge necessary to build the diagnosis program. The ability to enumerate knowledge systematically facilitates defining the program's scope, completeness, and competence and assists in bounding, controlling, and guiding the knowledge acquisition process.

Williams, Linda J. F.↗
NASA NTRS2021

Functional Autonomy Challenges in Sampling for an Europa Lander Mission

We present a baseline approach to Functional Autonomyfor the purpose of conducting excavation and samplingbehaviors in a proposed Europa Lander mission. Aspects ofthe problems of site selection, excavation progress tracking,and fault identification are related; with particular emphasison parameters peculiar to an icy moon environment. Firstpass approaches to addressing these challenges are presentedin isolation, while motivating the current development goal ofproducing a general Functional Autonomy architecture thatallows state estimation, fault diagnosis, isolation, & recovery(FDIR), and adaptive behaviors to be formulated in concert.

Backes, Paul↗
NASA NTRS2015

Gas House Autonomous System Monitoring

Gas House Autonomous System Monitoring (GHASM) will employ Integrated System Health Monitoring (ISHM) of cryogenic fluids in the High Pressure Gas Facility at Stennis Space Center. The preliminary focus of development incorporates the passive monitoring and eventual commanding of the Nitrogen System. ISHM offers generic system awareness, adept at using concepts rather than specific error cases. As an enabler for autonomy, ISHM provides capabilities inclusive of anomaly detection, diagnosis, and abnormality prediction. Advancing ISHM and Autonomous Operation functional capabilities enhances quality of data, optimizes safety, improves cost effectiveness, and has direct benefits to a wide spectrum of aerospace applications.

Miller, Luke↗
NASA NTRS2005

Lessons Learned in the Livingstone 2 on Earth Observing One Flight Experiment

The Livingstone 2 (L2) model-based diagnosis software is a reusable diagnostic tool for monitoring complex systems. In 2004, L2 was integrated with the JPL Autonomous Sciencecraft Experiment (ASE) and deployed on-board Goddard's Earth Observing One (EO-1) remote sensing satellite, to monitor and diagnose the EO-1 space science instruments and imaging sequence. This paper reports on lessons learned from this flight experiment. The goals for this experiment, including validation of minimum success criteria and of a series of diagnostic scenarios, have all been successfully net. Long-term operations in space are on-going, as a test of the maturity of the system, with L2 performance remaining flawless. L2 has demonstrated the ability to track the state of the system during nominal operations, detect simulated abnormalities in operations and isolate failures to their root cause fault. Specific advances demonstrated include diagnosis of ambiguity groups rather than a single fault candidate; hypothesis revision given new sensor evidence about the state of the system; and the capability to check for faults in a dynamic system without having to wait until the system is quiescent. The major benefits of this advanced health management technology are to increase mission duration and reliability through intelligent fault protection, and robust autonomous operations with reduced dependency on supervisory operations from Earth. The work-load for operators will be reduced by telemetry of processed state-of-health information rather than raw data. The long-term vision is that of making diagnosis available to the onboard planner or executive, allowing autonomy software to re-plan in order to work around known component failures. For a system that is expected to evolve substantially over its lifetime, as for the International Space Station, the model-based approach has definite advantages over rule-based expert systems and limit-checking fault protection systems, as these do not scale well. The model-based approach facilitates reuse of the L2 diagnostic software; only the model of the system to be diagnosed and telemetry monitoring software has to be rebuilt for a new system or expanded for a growing system. The hierarchical L2 model supports modularity and expendability, and as such is suitable solution for integrated system health management as envisioned for systems-of-systems.

Hayden, Sandra C.↗
NASA NTRS2008

NASA Tech Briefs, August 2008

Customizable Digital Receivers for Radar Two-Camera Acquisition and Tracking of a Flying Target Visual Data Analysis for Satellites A Data Type for Efficient Representation of Other Data Types Hand-Held Ultrasonic Instrument for Reading Matrix Symbols Broadband Microstrip-to-Coplanar Strip Double-Y Balun A Topographical Lidar System for Terrain-Relative Navigation Programmable Low-Voltage Circuit Breaker and Tester Electronic Switch Arrays for Managing Microbattery Arrays Topics covered include: Lower-Dark-Current, Higher-Blue-Response CMOS Imagers; Fabricating Large-Area Sheets of Single-Layer Graphene by CVD; Support for Diagnosis of Custom Computer Hardware; Providing Goal-Based Autonomy for Commanding a Spacecraft; Dynamic Method for Identifying Collected Sample Mass; Optimal Planning and Problem-Solving; Attitude-Control Algorithm for Minimizing Maneuver Execution Errors; Grants Document-Generation System; Heat-Storage Modules Containing LiNO3 3H2O and Graphite Foam; Precipitation-Strengthened, High-Temperature, High-Force Shape Memory Alloys; Improved Relief Valve Would Be Less Susceptible to Failure; Safety Modification of Cam-and-Groove Hose Coupling; Using Composite Materials in a Cryogenic Pump; Using Electronic Noses to Detect Tumors During Neurosurgery; Producing Newborn Synchronous Mammalian Cells; Smaller, Lower-Power Fast-Neutron Scintillation Detectors; Rotationally Vibrating Electric-Field Mill; Estimating Hardness from the USDC Tool-Bit Temperature Rise; Particle-Charge Spectrometer; Automated Production of Movies on a Cluster of Computers; FIDO-Class Development Rover; and Tone-Based Command of Deep Space Probes Using Ground Antennas.

Source record↗
NASA NTRS2011

Exploration Medical System Demonstration Project

A near-Earth Asteroid (NEA) mission will present significant new challenges including hazards to crew health created by exploring a beyond low earth orbit destination, traversing the terrain of asteroid surfaces, and the effects of variable gravity environments. Limited communications with ground-based personnel for diagnosis and consultation of medical events require increased crew autonomy when diagnosing conditions, creating treatment plans, and executing procedures. Scope: The Exploration Medical System Demonstration (EMSD) project will be a test bed on the International Space Station (ISS) to show an end-to-end medical system assisting the Crew Medical Officers (CMO) in optimizing medical care delivery and medical data management during a mission. NEA medical care challenges include resource and resupply constraints limiting the extent to which medical conditions can be treated, inability to evacuate to Earth during many mission phases, and rendering of medical care by a non-clinician. The system demonstrates the integration of medical technologies and medical informatics tools for managing evidence and decision making. Project Objectives: The objectives of the EMSD project are to: a) Reduce and possibly eliminate the time required for a crewmember and ground personnel to manage medical data from one application to another. b) Demonstrate crewmember's ability to access medical data/information via a software solution to assist/aid in the treatment of a medical condition. c) Develop a common data management architecture that can be ubiquitously used to automate repetitive data collection, management, and communications tasks for all crew health and life sciences activities. d) Develop a common data management architecture that allows for scalability, extensibility, and interoperability of data sources and data users. e) Lower total cost of ownership for development and sustainment of peripheral hardware and software that use EMSD for data management f) Provide better crew health via the reduction in crew errors, crew time, and ground time.

Chin, D. A.↗
NASA NTRS1994

Distributed intelligence for ground/space systems

DI is short for Distributed Intelligence for Ground/Space Systems and the DI Study is one in a series of ESA projects concerned with the development of new concepts and architectures for future autonomous spacecraft systems. The kick-off of DI was in January 1994 and the planned duration is three years. The background of DI is the desire to design future ground/space systems with a higher degree of autonomy than seen in today's missions. The aim of introducing autonomy in spacecraft systems is to: (1) lift the role of the spacecraft operators from routine work and basic troubleshooting to supervision; (2) ease access to and increase availability of spacecraft resources; (3) carry out basic mission planning for users; (4) enable missions which have not yet been feasible due to eg. propagation delays, insufficient ground station coverage etc.; and (5) possibly reduce mission cost. The study serves to identify the feasibility of using state-of-the-art technologies in the area of planning, scheduling, fault detection using model-based diagnosis and knowledge processing to obtain a higher level of autonomy in ground/space systems.

Aarup, Mads↗
NASA NTRS2011

Technology Development to Support Human Health and Performance in Exploration Beyond Low Earth Orbit

In the course of defining the level of risks and mitigating the risks for exploration missions beyond low Earth orbit, NASA s Human Research Program (HRP) has identified the need for technology development in several areas. Long duration missions increase the risk of serious medical conditions due to limited options for return to Earth; no resupply; highly limited mass, power, volume; and communication delays. New space flight compatible medical capabilities required include: diagnostic imaging, oxygen concentrator, ventilator, laboratory analysis (saliva, blood, urine), kidney stone diagnosis & treatment, IV solution preparation and delivery. Maintenance of behavioral health in such an isolated, confined and extreme environment requires new sensory stimulation (e.g., virtual reality) technology. Unobtrusive monitoring of behavioral health and treatment methods are also required. Prolonged exposure to weightlessness deconditions bone, muscle, and the cardiovascular system. Novel exercise equipment or artificial gravity are necessary to prevent deconditioning. Monitoring of the degree of deconditioning is required to ensure that countermeasures are effective. New technologies are required in all the habitable volumes (e.g., suit, capsule, habitat, exploration vehicle, lander) to provide an adequate food system, and to meet human environmental standards for air, water, and surface contamination. Communication delays require the crew to be more autonomous. Onboard decision support tools that assist crew with real-time detection and diagnosis of vehicle and habitat operational anomalies will enable greater autonomy. Multi-use shield systems are required to provide shielding from solar particle events. The HRP is pursuing the development of these technologies in laboratories, flight analog environments and the ISS so that the human health and performance risks will be acceptable with the available resources.

Kundrot, C.E.↗
NASA NTRS1997

On-Board Planning for New Millenium Deep Space One Autonomy

The Deep Space One (DS1) mission, scheduled to fly in 1998, will be the first NASA spacecraft to feature an on-board planner. The planner is part of an artificial intelligence based control architecture that comprises the planner/scheduler, a plan execution engine, and a model-based fault diagnosis and reconfiguration engine...This paper describes the on-board planning and scheduling component of the DS1 autonomy architecture.

Deep↗
NASA NTRS2021

On-Board Model Based Fault Diagnosis for CubeSat Attitude Control Subsystem: Flight Data Results

Self-sufficient, robotic spacecraft require estimates of their hardware health state in order to project future system state and plan actions toward achieving mission goals. In this paper, we report on integration of a Model-Based Fault Diagnosis (MBFD) model and reasoning engine into flight software leveraging the Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) mission, including test results against captured flight data using the ASTERIA system testbed. Our effort integrated the Model-based Off-Nominal State Identification and Detection (MONSID) model-based reasoning system, developed by Okean Solutions, into ASTERIA flight software using the F Prime software framework. The MONSID engine was supplied with a model of the Blue Canyon Technologies XACT attitude control system (ACS) and tested against flight data and seeded fault tests. While we were unable to conduct an on-board experiment due to the premature loss of ASTERIA, our effort proved the feasibility of on-board model-based fault management, demonstrating reliable and accurate diagnosis using captured data, and further supporting a closed-loop spacecraft autonomy demonstration including autonomous navigation in off-nominal conditions.

Prather, Maurice↗
NASA NTRS2004

Identifying Model-Based Reconfiguration Goals through Functional Deficiencies

Model-based diagnosis is now advanced to the point autonomous systems face some uncertain and faulty situations with success. The next step toward more autonomy is to have the system recovering itself after faults occur, a process known as model-based reconfiguration. After faults occur, given a prediction of the nominal behavior of the system and the result of the diagnosis operation, this paper details how to automatically determine the functional deficiencies of the system. These deficiencies are characterized in the case of uncertain state estimates. A methodology is then presented to determine the reconfiguration goals based on the deficiencies. Finally, a recovery process interleaves planning and model predictive control to restore the functionalities in prioritized order.

Benazera, Emmanuel↗
NASA NTRS2013

Embedding Temporal Constraints For Coordinated Execution in Habitat Automation

Future NASA plans call for long-duration deep space missions with human crews. Because of light-time delay and other considerations, increased autonomy will be needed. This will necessitate integration of tools in such areas as anomaly detection, diagnosis, planning, and execution. In this paper we investigate an approach that integrates planning and execution by embedding planner-derived temporal constraints in an execution procedure. To avoid the need for propagation, we convert the temporal constraints to dispatchable form. We handle some uncertainty in the durations without it affecting the execution; larger variations may cause activities to be skipped.

Morris, Paul↗
NASA NTRS2006

Contingency Software in Autonomous Systems

This viewgraph presentation reviews the development of contingency software for autonomous systems. Autonomous vehicles currently have a limited capacity to diagnose and mitigate failures. There is a need to be able to handle a broader range of contingencies. The goals of the project are: 1. Speed up diagnosis and mitigation of anomalous situations.2.Automatically handle contingencies, not just failures.3.Enable projects to select a degree of autonomy consistent with their needs and to incrementally introduce more autonomy.4.Augment on-board fault protection with verified contingency scripts

autonomous systems↗