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NASA NTRS2004

Science Goal Monitor: Science Goal Driven Automation for NASA Missions

Infusion of automation technologies into NASA s future missions will be essential because of the need to: (1) effectively handle an exponentially increasing volume of scientific data, (2) successfully meet dynamic, opportunistic scientific goals and objectives, and (3) substantially reduce mission operations staff and costs. While much effort has gone into automating routine spacecraft operations to reduce human workload and hence costs, applying intelligent automation to the science side, i.e., science data acquisition, data analysis and reactions to that data analysis in a timely and still scientifically valid manner, has been relatively under-emphasized. In order to introduce science driven automation in missions, we must be able to: capture and interpret the science goals of observing programs, represent those goals in machine interpretable language; and allow spacecrafts onboard systems to autonomously react to the scientist's goals. In short, we must teach our platforms to dynamically understand, recognize, and react to the scientists goals. The Science Goal Monitor (SGM) project at NASA Goddard Space Flight Center is a prototype software tool being developed to determine the best strategies for implementing science goal driven automation in missions. The tools being developed in SGM improve the ability to monitor and react to the changing status of scientific events. The SGM system enables scientists to specify what to look for and how to react in descriptive rather than technical terms. The system monitors streams of science data to identify occurrences of key events previously specified by the scientist. When an event occurs, the system autonomously coordinates the execution of the scientist s desired reactions. Through SGM, we will improve om understanding about the capabilities needed onboard for success, develop metrics to understand the potential increase in science returns, and develop an operational prototype so that the perceived risks associated with increased use of automation can be reduced.

Koratkar, Anuradha↗
NASA NTRS2000

Goals Analysis Procedure Guidelines for Applying the Goals Analysis Process

One of the key elements to successful project management is the establishment of the "right set of requirements", requirements that reflect the true customer needs and are consistent with the strategic goals and objectives of the participating organizations. A viable set of requirements implies that each individual requirement is a necessary element in satisfying the stated goals and that the entire set of requirements, taken as a whole, is sufficient to satisfy the stated goals. Unfortunately, it is the author's experience that during project formulation phases' many of the Systems Engineering customers do not conduct a rigorous analysis of the goals and objectives that drive the system requirements. As a result, the Systems Engineer is often provided with requirements that are vague, incomplete, and internally inconsistent. To complicate matters, most systems development methodologies assume that the customer provides unambiguous, comprehensive and concise requirements. This paper describes the specific steps of a Goals Analysis process applied by Systems Engineers at the NASA Langley Research Center during the formulation of requirements for research projects. The objective of Goals Analysis is to identify and explore all of the influencing factors that ultimately drive the system's requirements.

Motley, Albert E., III↗
NASA NTRS2003

Science Goal Driven Automation for NASA Missions: The Science Goal Monitor

Infusion of automation technologies into NASA s future missions will be essential not only to achieve substantial reduction in mission operations staff and costs, but also in order to both effectively handle an exponentially increasing volume of scientific data and to successfully meet dynamic, opportunistic scientific goals and objectives. Current spacecraft operations cannot respond to science driven events, such as intrinsically variable or short-lived phenomena in a timely manner. For such investigations, we must teach our platforms to dynamically understand, recognize, and react to the scientists goals. While much effort has gone into automating routine spacecraft operations to reduce human workload and hence costs, applying intelligent automation to the science side, i.e., science data acquisition, data analysis and reactions to that data analysis in a timely and still scientifically valid manner, has been relatively under-emphasized.

Korathkar, Anuradha↗
NASA NTRS2013

Goal-Function Tree Modeling for Systems Engineering and Fault Management

The draft NASA Fault Management (FM) Handbook (2012) states that Fault Management (FM) is a "part of systems engineering", and that it "demands a system-level perspective" (NASAHDBK- 1002, 7). What, exactly, is the relationship between systems engineering and FM? To NASA, systems engineering (SE) is "the art and science of developing an operable system capable of meeting requirements within often opposed constraints" (NASA/SP-2007-6105, 3). Systems engineering starts with the elucidation and development of requirements, which set the goals that the system is to achieve. To achieve these goals, the systems engineer typically defines functions, and the functions in turn are the basis for design trades to determine the best means to perform the functions. System Health Management (SHM), by contrast, defines "the capabilities of a system that preserve the system's ability to function as intended" (Johnson et al., 2011, 3). Fault Management, in turn, is the operational subset of SHM, which detects current or future failures, and takes operational measures to prevent or respond to these failures. Failure, in turn, is the "unacceptable performance of intended function." (Johnson 2011, 605) Thus the relationship of SE to FM is that SE defines the functions and the design to perform those functions to meet system goals and requirements, while FM detects the inability to perform those functions and takes action. SHM and FM are in essence "the dark side" of SE. For every function to be performed (SE), there is the possibility that it is not successfully performed (SHM); FM defines the means to operationally detect and respond to this lack of success. We can also describe this in terms of goals: for every goal to be achieved, there is the possibility that it is not achieved; FM defines the means to operationally detect and respond to this inability to achieve the goal. This brief description of relationships between SE, SHM, and FM provide hints to a modeling approach to provide formal connectivity between the nominal (SE), and off-nominal (SHM and FM) aspects of functions and designs. This paper describes a formal modeling approach to the initial phases of the development process that integrates the nominal and off-nominal perspectives in a model that unites SE goals and functions of with the failure to achieve goals and functions (SHM/FM). This methodology and corresponding model, known as a Goal-Function Tree (GFT), provides a means to represent, decompose, and elaborate system goals and functions in a rigorous manner that connects directly to design through use of state variables that translate natural language requirements and goals into logical-physical state language. The state variable-based approach also provides the means to directly connect FM to the design, by specifying the range in which state variables must be controlled to achieve goals, and conversely, the failures that exist if system behavior go out-of-range. This in turn allows for the systems engineers and SHM/FM engineers to determine which state variables to monitor, and what action(s) to take should the system fail to achieve that goal. In sum, the GFT representation provides a unified approach to early-phase SE and FM development. This representation and methodology has been successfully developed and implemented using Systems Modeling Language (SysML) on the NASA Space Launch System (SLS) Program. It enabled early design trade studies of failure detection coverage to ensure complete detection coverage of all crew-threatening failures. The representation maps directly both to FM algorithm designs, and to failure scenario definitions needed for design analysis and testing. The GFT representation provided the basis for mapping of abort triggers into scenarios, both needed for initial, and successful quantitative analyses of abort effectiveness (detection and response to crew-threatening events).

Patterson, Jonathan D.↗
NASA NTRS2008

Providing Goal-Based Autonomy for Commanding a Spacecraft

A computer program for use aboard a scientific-exploration spacecraft autonomously selects among goals specified in high-level requests and generates corresponding sequences of low-level commands, understandable by spacecraft systems. (As used here, 'goals' signifies specific scientific observations.) From a dynamic, onboard set of goals that could oversubscribe spacecraft resources, the program selects a non-oversubscribing subset that maximizes a quality metric. In an early version of the program, the requested goals are assumed to have fixed starting times and durations. Goals can conflict by exceeding a limit on either the number of separate goals or the number of overlapping goals making demands on the same resource. The quality metric used in this version is chosen to ensure that a goal will never be replaced by another having lower priority. At any time, goals can be added or removed, or their priorities can be changed, and the 'best' goal will be selected. Once a goal has been selected, the program implements a robust, flexible approach to generation of low-level commands: Rather than generate rigid sequences with fixed starting times, the program specifies flexible sequences that can be altered to accommodate run time variations.

Rabideau, Gregg↗
NASA NTRS2015

A Fast Goal Recognition Technique Based on Interaction Estimates

Goal Recognition is the task of inferring an actor's goals given some or all of the actor's observed actions. There is considerable interest in Goal Recognition for use in intelligent personal assistants, smart environments, intelligent tutoring systems, and monitoring user's needs. In much of this work, the actor's observed actions are compared against a generated library of plans. Recent work by Ramirez and Geffner makes use of AI planning to determine how closely a sequence of observed actions matches plans for each possible goal. For each goal, this is done by comparing the cost of a plan for that goal with the cost of a plan for that goal that includes the observed actions. This approach yields useful rankings, but is impractical for real-time goal recognition in large domains because of the computational expense of constructing plans for each possible goal. In this paper, we introduce an approach that propagates cost and interaction information in a plan graph, and uses this information to estimate goal probabilities. We show that this approach is much faster, but still yields high quality results.

gola recognition↗
NASA NTRS1973

The GOAL-to-HAL/S translator specification

The specification sets forth a technical framework within which to deal with the transfer of specific GOAL features to HAL/S. Key technical features of the translator are described which communicate with the data bank, handle repeat statements, and deal with software interrupts. GOAL programs, databank information, and GOAL system subroutines are integrated into one GOAL in HAL/S. This output is fully compatible HAL/S source ready for insertion into the HAL/S compiler. The Translator uses a PASS1 to establish all the global data needed for the HAL/S output program. Individual GOAL statements are translated in PASS2. The specification document makes extensive use of flowcharts to specify exactly how each variation of each GOAL statement is to be translated. The specification also deals with definitions and assumptions, executive support structure and implementation. An appendix, entitled GOAL-to-HAL Mapping, provides examples of translated GOAL statements.

Stanten, S. F.↗
NASA NTRS2013

Goal-Function Tree Modeling for Systems Engineering and Fault Management

The draft NASA Fault Management (FM) Handbook (2012) states that Fault Management (FM) is a "part of systems engineering", and that it "demands a system-level perspective" (NASAHDBK- 1002, 7). What, exactly, is the relationship between systems engineering and FM? To NASA, systems engineering (SE) is "the art and science of developing an operable system capable of meeting requirements within often opposed constraints" (NASA/SP-2007-6105, 3). Systems engineering starts with the elucidation and development of requirements, which set the goals that the system is to achieve. To achieve these goals, the systems engineer typically defines functions, and the functions in turn are the basis for design trades to determine the best means to perform the functions. System Health Management (SHM), by contrast, defines "the capabilities of a system that preserve the system's ability to function as intended" (Johnson et al., 2011, 3). Fault Management, in turn, is the operational subset of SHM, which detects current or future failures, and takes operational measures to prevent or respond to these failures. Failure, in turn, is the "unacceptable performance of intended function." (Johnson 2011, 605) Thus the relationship of SE to FM is that SE defines the functions and the design to perform those functions to meet system goals and requirements, while FM detects the inability to perform those functions and takes action. SHM and FM are in essence "the dark side" of SE. For every function to be performed (SE), there is the possibility that it is not successfully performed (SHM); FM defines the means to operationally detect and respond to this lack of success. We can also describe this in terms of goals: for every goal to be achieved, there is the possibility that it is not achieved; FM defines the means to operationally detect and respond to this inability to achieve the goal. This brief description of relationships between SE, SHM, and FM provide hints to a modeling approach to provide formal connectivity between the nominal (SE), and off-nominal (SHM and FM) aspects of functions and designs. This paper describes a formal modeling approach to the initial phases of the development process that integrates the nominal and off-nominal perspectives in a model that unites SE goals and functions of with the failure to achieve goals and functions (SHM/FM).

Johnson, Stephen B.↗
NASA NTRS2013

Goal-Function Tree Modeling for Systems Engineering and Fault Management

This paper describes a new representation that enables rigorous definition and decomposition of both nominal and off-nominal system goals and functions: the Goal-Function Tree (GFT). GFTs extend the concept and process of functional decomposition, utilizing state variables as a key mechanism to ensure physical and logical consistency and completeness of the decomposition of goals (requirements) and functions, and enabling full and complete traceabilitiy to the design. The GFT also provides for means to define and represent off-nominal goals and functions that are activated when the system's nominal goals are not met. The physical accuracy of the GFT, and its ability to represent both nominal and off-nominal goals enable the GFT to be used for various analyses of the system, including assessments of the completeness and traceability of system goals and functions, the coverage of fault management failure detections, and definition of system failure scenarios.

Johnson, Stephen B.↗
NASA NTRS2005

Software for Optimizing Plans Involving Interdependent Goals

A computer program enables construction and optimization of plans for activities that are directed toward achievement of goals that are interdependent. Goal interdependence is defined as the achievement of one or more goals affecting the desirability or priority of achieving one or more other goals. This program is overlaid on the Automated Scheduling and Planning Environment (ASPEN) software system, aspects of which have been described in a number of prior NASA Tech Briefs articles. Unlike other known or related planning programs, this program considers interdependences among goals that can change between problems and provides a language for easily specifying such dependences. Specifications of the interdependences can be formulated dynamically and provided to the associated planning software as part of the goal input. Then an optimization algorithm provided by this program enables the planning software to reason about the interdependences and incorporate them into an overall objective function that it uses to rate the quality of a plan under construction and to direct its optimization search. In tests on a series of problems of planning geological experiments by a team of instrumented robotic vehicles (rovers) on new terrain, this program was found to enhance plan quality.

Estlin, Tara↗
NASA NTRS1973

GOAL-to-HAL translation study

This report deals with the feasibility, problems, solutions, and mapping of a GOAL language to HAL language translator. Ground Operations Aerospace Language, or GOAL, is a test-oriented higher order language developed by the John F. Kennedy Space Center to be used in checkout and launch of the space shuttle. HAL is a structured higher order language developed by the Johnson Space Center to be used in writing the flight software for the onboard shuttle computers. Since the onboard computers will extensively support ground checkout of the space shuttle, and since these computers and the software development facilities on the ground use the HAL language as baseline, the translation of GOAL to HAL becomes significant. The issue of feasibility was examined and it was found that a GOAL to HAL translator is feasible. Special problems are identified and solutions proposed. Finally, examples of translation are provided for each category of complete GOAL statement.

Flanders, J. H.↗
NASA NTRS2006

Constellation Stretch Goals: Review of Industry Inputs

Many good ideas received based on industry experience: a) Shuttle operations; b) Commercial aircraft production; c) NASA's historical way of doing business; d) Military and commercial programs. Aerospace performed preliminary analysis: a) Potential savings; b) Cost of implementation; c) Performance or other impact/penalties; d) Roadblocks; e) Unintended consequences; f) Bottom line. Significant work ahead for a "Stretch Goal"to become a good, documented requirement: 1) As a group, the relative "value" of goals are uneven; 2) Focused analysis on each goal is required: a) Need to ensure that a new requirement produces the desired consequence; b) It is not certain that some goals will not create problems elsewhere. 3) Individual implementation path needs to be studied: a) Best place to insert requirement (what level, which document); b) Appropriate wording for the requirement. Many goals reflect "best practices" based on lessons learned and may have value beyond near-term CxP requirements process.

Lang, John↗
NASA NTRS2008

Does NASA's Constellation Architecture Offer Opportunities to Achieve Multiple Additional Goals in Space?

Every major NASA human spaceflight program in the last four decades has been modified to achieve goals in space not incorporated within the original design goals: the Apollo Applications Program, Skylab, Space Shuttle, and International Space Station. Several groups in the US have been identifying major future science goals, the science facilities necessary to investigate them, as well as possible roles for augmented versions of elements of NASA's Constellation program. Specifically, teams in the astronomy community have been developing concepts for very capable missions to follow the James Webb Space Telescope that could take advantage of - or require - free-space operations by astronauts and/or robots. Taking as one example, the Single-Aperture Far-InfraRed (SAFIR) telescope with a approx. 10+ m aperture proposed for operation in the 2020 timeframe. According to current NASA plans, the Ares V launch vehicle (or a variant) will be available about the same time, as will the capability to transport astronauts to the vicinity of the Moon via the Orion Crew Exploration Vehicle and associated systems. [As the lunar surface offers no advantages - and major disadvantages - for most major optical systems, the expensive system for landing and operating on the lunar surface is not required.] Although as currently conceived, SAFIR and other astronomical missions will operate at the Sun-Earth L2 location, it appears trivial to travel for servicing to the more accessible Earth-Moon L1,2 locations. Moreover. as the recent Orbital Express and Automated Transfer Vehicle missions have demonstrated, future robotic capabilities should offer capabilities that would (remotely) extend human presence far beyond the vicinity of the Earth. In addition to multiplying the value of NASA's architecture for future human spaceflight to achieve the goals multiple major stakeholders. if humans one day travel beyond the Earth-Moon system - say, to Mars - technologies and capabilities for operating for long periods in free space must be developed. The engineering, management. and operational successes of the Space Station have demonstrated that international collaboratio~i is possible. However, there is a danger that the hard-won lessons of cLul+sent programs will be lost without continuing development of in-space operations. A program to achieve. for example. major astronomical goals in space using astronauts and robots will sustain international capabilities. produce highly visible achievements. and appeal to a11 additional broad community of stakeholders not currently involved with missions to the lunar surface.

Thronson, Harley↗
NASA NTRS2008

Does NASA's Constellation Architecture Offer Opportunities to Achieve Multiple Additional Goals in Space?

Every major NASA human spaceflight program in the last four decades has been modified to achieve goals in space not incorporated within the original design goals: the Apollo Applications Program, Skylab, Space Shuttle, and International Space Station. Several groups in the US have been identifying major future science goals, the science facilities necessary to investigate them, as well as possible roles for augmented versions of elements of NASA's Constellation program. Specifically, teams in the astronomy community have been developing concepts for very capable missions to follow the James Webb Space Telescope that could take advantage of - or require - free-space operations by astronauts and/or robots. Taking as one example, the Single-Aperture Far-InfraRed (SAFIR) telescope with a approx.10+ m aperture proposed for operation in the 2020 timeframe. According to current NASA plans, the Ares V launch vehicle (or a variant) will be available about the same time, as will the capability to transport astronauts to the vicinity of the Moon via the Orion Crew Exploration Vehicle and associated systems. [As the lunar surface offers no advantages - and major disadvantages - for most major optical systems, the expensive system for landing and operating on the lunar surface is not required.] Although as currently conceived, SAFIR and other astronomical missions will operate at the Sun-Earth L2 location, it appears trivial to travel for servicing to the more accessible Earth-Moon L1,2 locations. Moreover, as the recent Orbital Express and Automated Transfer Vehicle missions have demonstrated, future robotic capabilities should offer capabilities that would (remotely) extend human presence far beyond the vicinity of the Earth. In addition to multiplying the value of NASA's architecture for future human spaceflight to achieve the goals multiple major stakeholders, if humans one day travel beyond the Earth-Moon system - say, to Mars - technologies and capabilities for operating for long periods in free space must be developed. The engineering. management, and operational successes of the Space Station have demonstrated that international collaboration is possible. However, there is a danger that the hard-won lessons of current programs will be lost without continuing development of in-space operations. A program to achieve. for example, major astronomical goals in space using astronauts and robots will sustain international capabilities, produce highly visible achievements, and appeal to an additional broad community of stakeholders not currently involved with missions to the lunar surface.

Thronson, Harley A.↗
NASA NTRSDate not supplied

Anisotropic Goal-Based Mesh Adaptation Metric Clarification and Development

Adaptive unstructured mesh techniques have a limited, but growing impact on production analysis workflows to control discretization error for reliable simulation results. Multiple independent implementations of flow solvers, anisotropic metric construction methods, and anisotropic mesh adaptation mechanics have matured. Goal-based metrics target estimated error in output functions, such as lift and drag, through the guidance of an adjoint solution. A unification of goal-based anisotropic metrics is presented for steady viscous flows, which is an active area of research. These goal-based metrics drive robust and efficient anisotropic mesh adaptation for the calculation of output functions. The super-convergent functional output error behavior of stabilized finite-element methods is exploited without a formal proof, and evidence of super-convergence is shown in numerical experiments. Mesh adapted drag and lift outputs for two simple bodies in compressible viscous flow show convergence of error to less than a single drag count. Asymptotic behavior established for relatively coarse meshes shows the efficiency of this goal-based metric when compared to solution interpolation error control and expert-guided meshing. Anisotropic mesh adaptation techniques are applied to a transport aircraft in a high-lift configuration where variation between approaches decreases with mesh refinement, but asymptotic behavior is not observed with available resources.

goal-based↗
NASA NTRS1973

Shuttle avionics and the goal language including the impact of error detection and redundancy management

The relationship is examined between the space shuttle onboard avionics and the ground test computer language GOAL when used in the onboard computers. The study is aimed at providing system analysis support to the feasibility analysis of a GOAL to HAL translator, where HAL is the language used to program the onboard computers for flight. The subject is dealt with in three aspects. First, the system configuration at checkout, the general checkout and launch sequences, and the inventory of subsystems are described. Secondly, the hierarchic organization of onboard software and different ways of introducing GOAL-derived software onboard are described. Also the flow of commands and test data during checkout is diagrammed. Finally, possible impact of error detection and redundancy management on the GOAL language is discussed.

Flanders, J. H.↗