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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Cognition and procedure representational requirements for predictive human performance models

Models and modeling environments for human performance are becoming significant contributors to early system design and analysis procedures. Issues of levels of automation, physical environment, informational environment, and manning requirements are being addressed by such man/machine analysis systems. The research reported here investigates the close interaction between models of human cognition and models that described procedural performance. We describe a methodology for the decomposition of aircrew procedures that supports interaction with models of cognition on the basis of procedures observed; that serves to identify cockpit/avionics information sources and crew information requirements; and that provides the structure to support methods for function allocation among crew and aiding systems. Our approach is to develop an object-oriented, modular, executable software representation of the aircrew, the aircraft, and the procedures necessary to satisfy flight-phase goals. We then encode in a time-based language, taxonomies of the conceptual, relational, and procedural constraints among the cockpit avionics and control system and the aircrew. We have designed and implemented a goals/procedures hierarchic representation sufficient to describe procedural flow in the cockpit. We then execute the procedural representation in simulation software and calculate the values of the flight instruments, aircraft state variables and crew resources using the constraints available from the relationship taxonomies. The system provides a flexible, extensible, manipulative and executable representation of aircrew and procedures that is generally applicable to crew/procedure task-analysis. The representation supports developed methods of intent inference, and is extensible to include issues of information requirements and functional allocation. We are attempting to link the procedural representation to models of cognitive functions to establish several intent inference methods including procedural backtracking with concurrent search, temporal reasoning, and constraint checking for partial ordering of procedures. Finally, the representation is being linked to models of human decision making processes that include heuristic, propositional and prescriptive judgement models that are sensitive to the procedural content in which the valuative functions are being performed.

Corker, K.↗
NASA NTRS2004

Cassini science planning process

The mission design for Cassini-Huygens calls for a four-year orbital survey of the Saturnian system and the descent into the Titan atmosphere and eventual soft-landing of the Huygens probe. The Cassini orbiter tour consists of 76 orbits around Saturn with 44 close Titan flybys and 8 targeted icy satellite flybys. The Cassini orbiter spacecraft carries twelve scientific instruments that will perform a wide range of observations on a multitude of designated targets. The science opportunities, frequency of encounters, the length of the Tour, and the use of distributed operations pose significant challenges for developing the science plan for the orbiter mission. The Cassini Science Planning Process is the process used to develop and integrate the science and engineering plan that incorporates an acceptable level of science required to meet the primary mission objectives far the orbiter. The bulk of the integrated science and engineering plan will be developed prior to Saturn Orbit Insertion (Sol). The Science Planning Process consists of three elements: 1) the creation of the Tour Atlas, which identifies the science opportunities in the tour, 2) the development of the Science Operations Plan (SOP), which is the conflict-free timeline of all science observations and engineering activities, a constraint-checked spacecraft pointing profile, and data volume allocations to the science instruments, and 3) an Aftermarket and SOP Update process, which is used to update the SOP while in tour with the latest information on spacecraft performance, science opportunities, and ephemerides. This paper will discuss the various elements of the Science Planning Process used on the Cassini Mission to integrate, implement, and adapt the science and engineering activity plans for Tour.

Cassini↗
NASA NTRS2006

Spitzer Space Telescope Sequencing Operations Software, Strategies, and Lessons Learned

The Space Infrared Telescope Facility (SIRTF) was launched in August, 2003, and renamed to the Spitzer Space Telescope in 2004. Two years of observing the universe in the wavelength range from 3 to 180 microns has yielded enormous scientific discoveries. Since this magnificent observatory has a limited lifetime, maximizing science viewing efficiency (ie, maximizing time spent executing activities directly related to science observations) was the key operational objective. The strategy employed for maximizing science viewing efficiency was to optimize spacecraft flexibility, adaptability, and use of observation time. The selected approach involved implementation of a multi-engine sequencing architecture coupled with nondeterministic spacecraft and science execution times. This approach, though effective, added much complexity to uplink operations and sequence development. The Jet Propulsion Laboratory (JPL) manages Spitzer s operations. As part of the uplink process, Spitzer s Mission Sequence Team (MST) was tasked with processing observatory inputs from the Spitzer Science Center (SSC) into efficiently integrated, constraint-checked, and modeled review and command products which accommodated the complexity of non-deterministic spacecraft and science event executions without increasing operations costs. The MST developed processes, scripts, and participated in the adaptation of multi-mission core software to enable rapid processing of complex sequences. The MST was also tasked with developing a Downlink Keyword File (DKF) which could instruct Deep Space Network (DSN) stations on how and when to configure themselves to receive Spitzer science data. As MST and uplink operations developed, important lessons were learned that should be applied to future missions, especially those missions which employ command-intensive operations via a multi-engine sequence architecture.

missions operations↗
NASA NTRS2006

A Roadmap for using Agile Development in a Traditional System

I. Ensemble Development Group: a) Produces activity planning software for in spacecraft; b) Built on Eclipse Rich Client Platform (open source development and runtime software); c) Funded by multiple sources including the Mars Technology Program; d) Incorporated the use of Agile Development. II. Next Generation Uplink Planning System: a) Researches the Activity Planning and Sequencing Subsystem for Mars Science Laboratory (APSS); b) APSS includes Ensemble, Activity Modeling, Constraint Checking, Command Editing and Sequencing tools plus other uplink generation utilities; c) Funded by the Mars Technology Program; d) Integrates all of the tools for APSS.

uplink planning systems↗
NASA NTRS1992

Symbolic discrete event system specification

Extending discrete event modeling formalisms to facilitate greater symbol manipulation capabilities is important to further their use in intelligent control and design of high autonomy systems. An extension to the DEVS formalism that facilitates symbolic expression of event times by extending the time base from the real numbers to the field of linear polynomials over the reals is defined. A simulation algorithm is developed to generate the branching trajectories resulting from the underlying nondeterminism. To efficiently manage symbolic constraints, a consistency checking algorithm for linear polynomial constraints based on feasibility checking algorithms borrowed from linear programming has been developed. The extended formalism offers a convenient means to conduct multiple, simultaneous explorations of model behaviors. Examples of application are given with concentration on fault model analysis.

Zeigler, Bernard P.↗
NASA NTRS2008

Verification and Planning Based on Coinductive Logic Programming

Coinduction is a powerful technique for reasoning about unfounded sets, unbounded structures, infinite automata, and interactive computations [6]. Where induction corresponds to least fixed point's semantics, coinduction corresponds to greatest fixed point semantics. Recently coinduction has been incorporated into logic programming and an elegant operational semantics developed for it [11, 12]. This operational semantics is the greatest fix point counterpart of SLD resolution (SLD resolution imparts operational semantics to least fix point based computations) and is termed co- SLD resolution. In co-SLD resolution, a predicate goal p( t) succeeds if it unifies with one of its ancestor calls. In addition, rational infinite terms are allowed as arguments of predicates. Infinite terms are represented as solutions to unification equations and the occurs check is omitted during the unification process. Coinductive Logic Programming (Co-LP) and Co-SLD resolution can be used to elegantly perform model checking and planning. A combined SLD and Co-SLD resolution based LP system forms the common basis for planning, scheduling, verification, model checking, and constraint solving [9, 4]. This is achieved by amalgamating SLD resolution, co-SLD resolution, and constraint logic programming [13] in a single logic programming system. Given that parallelism in logic programs can be implicitly exploited [8], complex, compute-intensive applications (planning, scheduling, model checking, etc.) can be executed in parallel on multi-core machines. Parallel execution can result in speed-ups as well as in larger instances of the problems being solved. In the remainder we elaborate on (i) how planning can be elegantly and efficiently performed under real-time constraints, (ii) how real-time systems can be elegantly and efficiently model- checked, as well as (iii) how hybrid systems can be verified in a combined system with both co-SLD and SLD resolution. Implementations of co-SLD resolution as well as preliminary implementations of the planning and verification applications have been developed [4]. Co-LP and Model Checking: The vast majority of properties that are to be verified can be classified into safety properties and liveness properties. It is well known within model checking that safety properties can be verified by reachability analysis, i.e, if a counter-example to the property exists, it can be finitely determined by enumerating all the reachable states of the Kripke structure.

Bansal, Ajay↗
NASA NTRS2004

Automatic Generation of Algorithms for the Statistical Analysis of Planetary Nebulae Images

Analyzing data sets collected in experiments or by observations is a Core scientific activity. Typically, experimentd and observational data are &aught with uncertainty, and the analysis is based on a statistical model of the conjectured underlying processes, The large data volumes collected by modern instruments make computer support indispensible for this. Consequently, scientists spend significant amounts of their time with the development and refinement of the data analysis programs. AutoBayes [GF+02, FS03] is a fully automatic synthesis system for generating statistical data analysis programs. Externally, it looks like a compiler: it takes an abstract problem specification and translates it into executable code. Its input is a concise description of a data analysis problem in the form of a statistical model as shown in Figure 1; its output is optimized and fully documented C/C++ code which can be linked dynamically into the Matlab and Octave environments. Internally, however, it is quite different: AutoBayes derives a customized algorithm implementing the given model using a schema-based process, and then further refines and optimizes the algorithm into code. A schema is a parameterized code template with associated semantic constraints which define and restrict the template s applicability. The schema parameters are instantiated in a problem-specific way during synthesis as AutoBayes checks the constraints against the original model or, recursively, against emerging sub-problems. AutoBayes schema library contains problem decomposition operators (which are justified by theorems in a formal logic in the domain of Bayesian networks) as well as machine learning algorithms (e.g., EM, k-Means) and nu- meric optimization methods (e.g., Nelder-Mead simplex, conjugate gradient). AutoBayes augments this schema-based approach by symbolic computation to derive closed-form solutions whenever possible. This is a major advantage over other statistical data analysis systems which use numerical approximations even in cases where closed-form solutions exist. AutoBayes is implemented in Prolog and comprises approximately 75.000 lines of code. In this paper, we take one typical scientific data analysis problem-analyzing planetary nebulae images taken by the Hubble Space Telescope-and show how AutoBayes can be used to automate the implementation of the necessary anal- ysis programs. We initially follow the analysis described by Knuth and Hajian [KHO2] and use AutoBayes to derive code for the published models. We show the details of the code derivation process, including the symbolic computations and automatic integration of library procedures, and compare the results of the automatically generated and manually implemented code. We then go beyond the original analysis and use AutoBayes to derive code for a simple image segmentation procedure based on a mixture model which can be used to automate a manual preproceesing step. Finally, we combine the original approach with the simple segmentation which yields a more detailed analysis. This also demonstrates that AutoBayes makes it easy to combine different aspects of data analysis.

Fischer, Bernd↗
NASA NTRS2011

Observation Scheduling System

Software has been designed to schedule remote sensing with the Earth Observing One spacecraft. The software attempts to satisfy as many observation requests as possible considering each against spacecraft operation constraints such as data volume, thermal, pointing maneuvers, and others. More complex constraints such as temperature are approximated to enable efficient reasoning while keeping the spacecraft within safe limits. Other constraints are checked using an external software library. For example, an attitude control library is used to determine the feasibility of maneuvering between pairs of observations. This innovation can deal with a wide range of spacecraft constraints and solve large scale scheduling problems like hundreds of observations and thousands of combinations of observation sequences.

Chien, Steve A.↗
NASA NTRS2007

The ANMLite Language and Logic for Specifying Planning Problems

We present the basic concepts of the ANMLite planning language. We discuss various aspects of specifying a plan in terms of constraints and checking the existence of a solution with the help of a model checker. The constructs of the ANMLite language have been kept as simple as possible in order to reduce complexity and simplify the verification problem. We illustrate the language with a specification of the space shuttle crew activity model that was constructed under the Spacecraft Autonomy for Vehicles and Habitats (SAVH) project. The main purpose of this study was to explore the implications of choosing a robust logic behind the specification of constraints, rather than simply proposing a new planning language.

Butler, Ricky W.↗
NASA NTRS1983

Skylab observations of the solar C I multiplets at 1560- and 1657-A

Skylab spectrograph profile observations of the solar C I multiplets are presented, and the profile variations from center to limb and at various heights above the quiet solar limb are noted. These lines are of interest both because they are formed in the midchromosphere, thereby providing checks and constraints on chromospheric models, and because they are sensitive to the magnitude of the nonthermal microvelocities included in theoretical calculations. The present observations are compared with the C I profiles calculated by Shine et al (1978), discussing the many inconsistencies that emerge, notably between the observed and computed 1560/1657-A ratio and in the center-to-limb and above-the-limb variations of the integrated intensity. The multiplet central cores are discussed in terms of several microturbulent velocity structures.

Roussel-Dupre, D.↗
NASA NTRS1992

The EUVE proposal database and scheduling system

The proposal database and scheduling system for the Extreme Ultraviolet Explorer will be described. The proposal database has been implemented to take input for approved observations selected by the EUVE Peer Review Panel and output target information suitable for the scheduling system to digest. The scheduling system is a hybrid of the SPIKE program and EUVE software which checks spacecraft constraints, produces a proposed schedule and selects spacecraft orientations with optimal configurations for acquiring star trackers, etc. This system has been used to schedule the In Orbit Calibration activities that took place this summer, following the EUVE launch in early June 1992. The implemented strategy has implications for the selection of approved targets, which have impacted the Peer Review process. In addition, it will be discussed how the proposal database, founded on Sybase, controls the processing of EUVE Guest Observer data.

Christian, C.↗
NASA NTRS1994

SEQ-REVIEW: A tool for reviewing and checking spacecraft sequences

A key component of JPL's strategy to make space missions faster, better and cheaper is the Advanced Multi-Mission Operations System (AMMOS), a ground software intensive system currently in use and in further development. AMMOS intends to eliminate the cost of re-engineering a ground system for each new JPL mission. This paper discusses SEQ-REVIEW, a component of AMMOS that was designed to facilitate and automate the task of reviewing and checking spacecraft sequences. SEQ-REVIEW is a smart browser for inspecting files created by other sequence generation tools in the AMMOS system. It can parse sequence-related files according to a computer-readable version of a 'Software Interface Specification' (SIS), which is a standard document for defining file formats. It lets users display one or several linked files and check simple constraints using a Basic-like 'Little Language'. SEQ-REVIEW represents the first application of the Quality Function Development (QFD) method to sequence software development at JPL. The paper will show how the requirements for SEQ-REVIEW were defined and converted into a design based on object-oriented principles. The process starts with interviews of potential users, a small but diverse group that spans multiple disciplines and 'cultures'. It continues with the development of QFD matrices that related product functions and characteristics to user-demanded qualities. These matrices are then turned into a formal Software Requirements Document (SRD). The process concludes with the design phase, in which the CRC (Class, Responsibility, Collaboration) approach was used to convert requirements into a blueprint for the final product.

Maldague, Pierre F.↗
NASA NTRS2002

Universal Quantification in a Constraint-Based Planner

Constraints and universal quantification are both useful in planning, but handling universally quantified constraints presents some novel challenges. We present a general approach to proving the validity of universally quantified constraints. The approach essentially consists of checking that the constraint is not violated for all members of the universe. We show that this approach can sometimes be applied even when variable domains are infinite, and we present some useful special cases where this can be done efficiently.

Golden, Keith↗
NASA NTRS2010

Symbolic PathFinder: Symbolic Execution of Java Bytecode

Symbolic Pathfinder (SPF) combines symbolic execution with model checking and constraint solving for automated test case generation and error detection in Java programs with unspecified inputs. In this tool, programs are executed on symbolic inputs representing multiple concrete inputs. Values of variables are represented as constraints generated from the analysis of Java bytecode. The constraints are solved using off-the shelf solvers to generate test inputs guaranteed to achieve complex coverage criteria. SPF has been used successfully at NASA, in academia, and in industry.

Pasareanu, Corina S.↗
NASA NTRS2005

APGEN Version 5.0

Activity Plan Generator (APGEN), now at version 5.0, is a computer program that assists in generating an integrated plan of activities for a spacecraft mission that does not oversubscribe spacecraft and ground resources. APGEN generates an interactive display, through which the user can easily create or modify the plan. The display summarizes the plan by means of a time line, whereon each activity is represented by a bar stretched between its beginning and ending times. Activities can be added, deleted, and modified via simple mouse and keyboard actions. The use of resources can be viewed on resource graphs. Resource and activity constraints can be checked. Types of activities, resources, and constraints are defined by simple text files, which the user can modify. In one of two modes of operation, APGEN acts as a planning expert assistant, displaying the plan and identifying problems in the plan. The user is in charge of creating and modifying the plan. In the other mode, APGEN automatically creates a plan that does not oversubscribe resources. The user can then manually modify the plan. APGEN is designed to interact with other software that generates sequences of timed commands for implementing details of planned activities.

Maldague, Pierre↗
NASA NTRSDate not supplied

What is the Role of Usability and Trust in Autonomy?

Usability encompasses learnability, efficiency, memorability, effectiveness, and satisfaction. NASA’s standards for usability acceptance criteria focus on interfaces that help operators achieve their tasks efficiently, effectively, and with satisfaction. However, discussions on usability, especially regarding future highly automated and autonomous systems, rarely include trust. As NASA plans for long-duration exploration missions, it envisions astronauts operating more independently from Mission Control on Earth. This independence will drive the development of these highly automated and autonomous systems that astronauts will use daily. To prepare for this future, our team has developed a scheduling and execution software tool that facilitates self-scheduling, allowing astronauts to independently manage their own schedule without Mission Control’s involvement. Over many years, we have developed, matured, and evaluated our software tool in extreme environments, prioritizing user-centered design and high usability. These evaluations have included multiple campaigns in NASA analogs, including NEEMO, BASALT, and HERA, as well as technology demonstrations onboard the International Space Station. Our recent research on software interfaces for future astronaut autonomy revealed a strong correlation between usability and trust measures. In a controlled lab experiment, we asked novice users to perform a complex scheduling task, during which the software immediately validated the schedule’s constraints and checked for violations. We collected usability (User Experience Questionnaire, UEQ) and trust (Trust in Automated Systems scale, TAS) measures; significant, strong, and moderate correlations emerged between several of the UEQ metrics and TAS. These results support the argument for investing in usability early to enable and sustain trust in highly automated and autonomous systems.

usability↗
NASA NTRS2022

Flight Rule Design, Implementation, Verification, and Validation for the Psyche Mission

NASA Jet Propulsion Lab (JPL)’s upcoming mission Psyche will begin its journey to the asteroid (16) Psyche in late 2022 in an effort to better understand its origins and, in turn, better understand our own. Operating the spacecraft safely will require the dedicated efforts of a small team that understands the spacecraft’s operational constraints, as well as a set of powerful spacecraft models designed to catch command errors that can pose risks to mission success. One of the responsibilities of the operations team is to ensure adherence to a set of Flight Rules written by spacecraft and instrument experts that are designed to mitigate these risks. Psyche’s innovations in Flight Rule design principles and advancements in the tools and processes used to implement and check Flight Rules are discussed. A comparison of Psyche’s approach to Flight Rules to other JPL missions will provide lessons learned for future missions that must perform constraint checking during operations. Flight Rule development faces several major challenges. First, flight rule developers must work with Subject Matter Experts (SME) to write the rules in a way that captures the intent of the constraint in a straightforward, enforceable manner. Second, software implementers must correctly interpret flight rules into code so that it meets the original intent of the SME. Finally, a means must be provided for SMEs to validate flight rule implementations without requiring them to understand the underlying software. Innovative processes intended to efficiently close the loop between stakeholders and software developers are described, such as the use of test-driven development to provide stakeholders with easy-to-review implementations. New guidelines for flight rule writing, designed to address these challenges, are described for future missions to adopt and build upon. Psyche Mission System has a variety of new and heritage tools that improve in the Flight Rule validation and checking process. Psyche developed a powerful, new tool called RandSEQ and made significant improvements to Octopusjam, two valuable tools that aid the development of Flight Rule unit tests. Advancements in the models and processes for performing sequence validation with SEQuence GENerator (SEQGEN), the primary, high-heritage tool used for automated flight rule checks on Psyche, are described. The development of new software and the advancements to existing software put Psyche at the forefront of Flight Rule technology. All missions must perform detailed constraint checking, so a comparison of Psyche’s approach to some of these items to the approaches taken by other missions such as Dawn, M2020, and Europa Clipper is done, specifically to examine SME-developer communication, tools used, and development process. Lessons learned from this comparison will be provided.

Weise, Tim↗