SEARCH · Search NASA

Results for “sequencing automation”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

All sources NASA NTRS DOE OSTI

NASA NTRS2006

Spotlight-8 Image Analysis Software

Spotlight is a cross-platform GUI-based software package designed to perform image analysis on sequences of images generated by combustion and fluid physics experiments run in a microgravity environment. Spotlight can perform analysis on a single image in an interactive mode or perform analysis on a sequence of images in an automated fashion. Image processing operations can be employed to enhance the image before various statistics and measurement operations are performed. An arbitrarily large number of objects can be analyzed simultaneously with independent areas of interest. Spotlight saves results in a text file that can be imported into other programs for graphing or further analysis. Spotlight can be run on Microsoft Windows, Linux, and Apple OS X platforms.

Klimek, Robert↗

NASA NTRS2009

Automation Interfaces of the Orion GNC Executive Architecture

This viewgraph presentation describes Orion mission's automation Guidance, Navigation and Control (GNC) architecture and interfaces. The contents include: 1) Orion Background; 2) Shuttle/Orion Automation Comparison; 3) Orion Mission Sequencing; 4) Orion Mission Sequencing Display Concept; and 5) Status and Forward Plans.

Hart, Jeremy↗

NASA NTRS2011

Design and Evaluation of the Terminal Area Precision Scheduling and Spacing System

This paper describes the design, development and results from a high fidelity human-in-the-loop simulation of an integrated set of trajectory-based automation tools providing precision scheduling, sequencing and controller merging and spacing functions. These integrated functions are combined into a system called the Terminal Area Precision Scheduling and Spacing (TAPSS) system. It is a strategic and tactical planning tool that provides Traffic Management Coordinators, En Route and Terminal Radar Approach Control air traffic controllers the ability to efficiently optimize the arrival capacity of a demand-impacted airport while simultaneously enabling fuel-efficient descent procedures. The TAPSS system consists of four-dimensional trajectory prediction, arrival runway balancing, aircraft separation constraint-based scheduling, traffic flow visualization and trajectory-based advisories to assist controllers in efficient metering, sequencing and spacing. The TAPSS system was evaluated and compared to today's ATC operation through extensive series of human-in-the-loop simulations for arrival flows into the Los Angeles International Airport. The test conditions included the variation of aircraft demand from a baseline of today's capacity constrained periods through 5%, 10% and 20% increases. Performance data were collected for engineering and human factor analysis and compared with similar operations both with and without the TAPSS system. The engineering data indicate operations with the TAPSS show up to a 10% increase in airport throughput during capacity constrained periods while maintaining fuel-efficient aircraft descent profiles from cruise to landing.

Swenson, Harry N.↗

NASA NTRS2018

Image Station Matching, Preprocessing, Spatial Registration and Change Detection with Multi-Temporal Remotely-Sensed Imagery

A method for collecting and processing remotely sensed imagery in order to achieve precise spatial co-registration (e.g., matched alignment) between multi-temporal image sets is presented. Such precise alignment or spatial co-registration of imagery can be used for change detection, image fusion, and temporal analysis/modeling. Further, images collected in this manner may be further processed in such a way that image frames or line arrays from corresponding photo stations are matched, co-aligned and if desired merged into a single image and/or subjected to the same processing sequence. A second methodology for automated detection of moving objects within a scene using a time series of remotely sensed imagery is also presented. Specialized image collection and preprocessing procedures are utilized to obtain precise spatial co-registration (image registration) between multitemporal image frame sets. In addition, specialized change detection techniques are employed in order to automate the detection of moving objects.

Coulter, Lloyd Lawrence Arthur↗

NASA NTRS2013

RECOVIR Software for Identifying Viruses

Most single-stranded RNA (ssRNA) viruses mutate rapidly to generate a large number of strains with highly divergent capsid sequences. Determining the capsid residues or nucleotides that uniquely characterize these strains is critical in understanding the strain diversity of these viruses. RECOVIR (an acronym for "recognize viruses") software predicts the strains of some ssRNA viruses from their limited sequence data. Novel phylogenetic-tree-based databases of protein or nucleic acid residues that uniquely characterize these virus strains are created. Strains of input virus sequences (partial or complete) are predicted through residue-wise comparisons with the databases. RECOVIR uses unique characterizing residues to identify automatically strains of partial or complete capsid sequences of picorna and caliciviruses, two of the most highly diverse ssRNA virus families. Partition-wise comparisons of the database residues with the corresponding residues of more than 300 complete and partial sequences of these viruses resulted in correct strain identification for all of these sequences. This study shows the feasibility of creating databases of hitherto unknown residues uniquely characterizing the capsid sequences of two of the most highly divergent ssRNA virus families. These databases enable automated strain identification from partial or complete capsid sequences of these human and animal pathogens.

Chakravarty, Sugoto↗

NASA NTRS2013

MPST Software: grl_suppdoc

Due to the nature of the GRAIL mission, the GRAIL Mission Planning and Sequence Team (MPST) is required to generate ground and uplink products faster than ever done before. The existing correct_transmitter_min_dur tool that provides a similar function to grl_suppdoc lacks the ability to operate accurately or quickly enough to support the rapid turnaround required of the GRAIL MPST. The GRAIL MPST was required to build this new tool to facilitate the ground and uplink generation processes to meet a tight sequence development timeline. The grl_suppdoc tool enables the GRAIL MPST to generate automatically Deep Space Network (DSN) transmitter suppressions based on short uplinks that are found in the ground/modeled Predicted Events File (PEF). The grl_suppdoc script automatically generates applicable DSN uplink suppressions in the form of a Spacecraft Activity Sequence File (SASF) to protect the GRAIL project from short DSN uplink windows, which can be cause for operator error at the DSN antennas. Currently, no software exists that provides this functionality at the efficiency required for GRAIL sequence team operations. Compared to a manual process, this script reduces human error and saves considerable man-hours by automating and streamlining the mission planning and sequencing task for the GRAIL mission.

Call, Jared A.↗

NASA NTRS1994

Fault Tree Based Diagnosis with Optimal Test Sequencing for Field Service Engineers

When field service engineers go to customer sites to service equipment, they want to diagnose and repair failures quickly and cost effectively. Symptoms exhibited by failed equipment frequently suggest several possible causes which require different approaches to diagnosis. This can lead the engineer to follow several fruitless paths in the diagnostic process before they find the actual failure. To assist in this situation, we have developed the Fault Tree Diagnosis and Optimal Test Sequence (FTDOTS) software system that performs automated diagnosis and ranks diagnostic hypotheses based on failure probability and the time or cost required to isolate and repair each failure. FTDOTS first finds a set of possible failures that explain exhibited symptoms by using a fault tree reliability model as a diagnostic knowledge to rank the hypothesized failures based on how likely they are and how long it would take or how much it would cost to isolate and repair them. This ordering suggests an optimal sequence for the field service engineer to investigate the hypothesized failures in order to minimize the time or cost required to accomplish the repair task. Previously, field service personnel would arrive at the customer site and choose which components to investigate based on past experience and service manuals. Using FTDOTS running on a portable computer, they can now enter a set of symptoms and get a list of possible failures ordered in an optimal test sequence to help them in their decisions. If facilities are available, the field engineer can connect the portable computer to the malfunctioning device for automated data gathering. FTDOTS is currently being applied to field service of medical test equipment. The techniques are flexible enough to use for many different types of devices. If a fault tree model of the equipment and information about component failure probabilities and isolation times or costs are available, a diagnostic knowledge base for that device can be developed easily.

Iverson, David L.↗

NASA NTRS1990

Spacecraft command verification: The AI solution

Recently, a knowledge-based approach was used to develop a system called the Command Constraint Checker (CCC) for TRW. CCC was created to automate the process of verifying spacecraft command sequences. To check command files by hand for timing and sequencing errors is a time-consuming and error-prone task. Conventional software solutions were rejected when it was estimated that it would require 36 man-months to build an automated tool to check constraints by conventional methods. Using rule-based representation to model the various timing and sequencing constraints of the spacecraft, CCC was developed and tested in only three months. By applying artificial intelligence techniques, CCC designers were able to demonstrate the viability of AI as a tool to transform difficult problems into easily managed tasks. The design considerations used in developing CCC are discussed and the potential impact of this system on future satellite programs is examined.

Fesq, Lorraine M.↗

NASA NTRS2000

Iterative Repair Planning for Spacecraft Operations Using the Aspen System

This paper describes the Automated Scheduling and Planning Environment (ASPEN). ASPEN encodes complex spacecraft knowledge of operability constraints, flight rules, spacecraft hardware, science experiments and operations procedures to allow for automated generation of low level spacecraft sequences. Using a technique called iterative repair, ASPEN classifies constraint violations (i.e., conflicts) and attempts to repair each by performing a planning or scheduling operation. It must reason about which conflict to resolve first and what repair method to try for the given conflict. ASPEN is currently being utilized in the development of automated planner/scheduler systems for several spacecraft, including the UFO-1 naval communications satellite and the Citizen Explorer (CX1) satellite, as well as for planetary rover operations and antenna ground systems automation. This paper focuses on the algorithm and search strategies employed by ASPEN to resolve spacecraft operations constraints, as well as the data structures for representing these constraints.

Rabideau, G.↗

NASA NTRS2017

Application of Human-Autonomy Teaming to an Advanced Ground Station for Reduced Crew Operations

Within human factors there is burgeoning interest in the "human-autonomy teaming" (HAT) concept as a way to address the challenges of interacting with complex, increasingly autonomous systems. The HAT concept comes out of an aspiration to interact with increasingly autonomous systems as a team member, rather than simply use automation as a tool. The authors, and others, have proposed core tenets for HAT that include bi-directional communication, automation and system transparency, and advanced coordination between human and automated teammates via predefined, dynamic task sequences known as "plays." It is believed that, with proper implementation, HAT should foster appropriate teamwork, thus increasing trust and reliance on the system, which in turn will reduce workload, increase situation awareness, and improve performance. To this end, HAT has been demonstrated and/or studied in multiple applications including search and rescue operations, healthcare and medicine, autonomous vehicles, photography, and aviation. The current paper presents one such effort to apply HAT. It details the design of a HAT agent, developed by Human Automation Teaming Solutions, Inc., to facilitate teamwork between the automation and the human operator of an advanced ground dispatch station. This dispatch station was developed to support a NASA project investigating a concept called Reduced Crew Operations (RCO); consequently, we have named the agent R-HATS. Part of the RCO concept involves a ground operator providing enhanced support to a large number of aircraft with a single pilot on the flight deck. When assisted by R-HATS, operators can monitor and support or manage a large number of aircraft and use plays to respond in real-time to complicated, workload-intensive events (e.g., an airport closure). A play is a plan that encapsulates goals, tasks, and a task allocation strategy appropriate for a particular situation. In the current implementation, when a play is initiated by a user, R-HATS determines what tasks need to be completed and has the ability to autonomously execute them (e.g., determining diversion options and uplinking new routes to aircraft) when it is safe and appropriate. R-HATS has been designed to both support end users and researchers in RCO and HAT. Additionally, R-HATS and its underlying architecture were developed with generalizability in mind as a modular software applicable outside of RCO/aviation domains. This paper will also discuss future further development and testing of RHATS.

automation↗

NASA NTRS2017

Flight Deck Surface Trajectory-Based Operations (STBO): A Four-Dimensional Trajectory (4DT) Simulation

Within human factors there is burgeoning interest in the Human-Autonomy Teaming (HAT) concept as away to address the challenges of interacting with complex, increasingly autonomous systems. The HAT concept comes out of an aspiration to interact with increasingly autonomous automation as a team member, rather than simply use automation as a tool. The authors, and others, have proposed core tenets for HAT that include bi-directional communication, automation and system transparency, and advanced coordination between human and automated teammates via predefined, dynamic task sequences known as plays (Shively et al., 2017). It is believed that, with proper implementation, HAT should foster appropriate teamwork, thus increasing trust and reliance on the system, which in turn will reduce workload, increase situation awareness, and improve performance. To this end, HAT has been demonstrated and/or studied in multiple applications including search and rescue operations (Nourbakhsh et al., 2005), healthcare and medicine (Tsui Yanco, 2007), autonomous vehicles (Parasuraman, Barnes, Cosenzo, Mulgund, 2007), photography (Lachter, Brandt, Sadler, Shively, in press), and aviation (Shively et al., in press). The current paper presents one such effort to apply HAT. It details the design of a R-HAT Agent developed as part of a NASA Research Agreement awarded to Human-Autonomy Teaming Solutions Inc. (HATS Inc), and developed in collaboration with the Human-Autonomy Teaming Laboratory at NASA Ames Research Center. The role of this Agent is to mediate interaction between the automation and the human operator of an advanced ground dispatch station, with this mediation based upon previously mentioned core tenets for HAT and the many lessons learned from the HAT research literature. This dispatch station was developed to support a NASA project investigating a concept called Reduced Crew Operations (RCO; Lachter, Brandt, Battiste, Matessa, Johnson, in press). Part of the RCO concept involves a ground operator providing enhanced support to a large number of aircraft with a single pilot on the flight deck. When assisted by the Agent, operators can monitor and support or manage a large number of aircraft and use plays to respond in real-time to complicated, workload-intensive events (e.g., an airport closure). A play is a plan that encapsulates goals, tasks, and a task allocation strategy appropriate for a particular situation. In the current implementation, when a play is initiated by a user, the Agent determines what tasks need to be done and has the ability to autonomously execute them (e.g., determining diversion options and uplinking new routes to aircraft) when it is safe and appropriate. The R-HAT Agent has been designed to both support end users and research in RCO and HAT. Additionally, the Agent and its underlying architecture were developed with generalizability in mind as a modular piece of software applicable outside of RCO aviation in domains such as those mentioned above. This paper will also discuss future further development and testing of the R-HAT Agent.

Bakowski, Deborah L.↗

NASA NTRS1988

Benchmarking and performance analysis of the CM-2

A suite of benchmarking routines testing communication, basic arithmetic operations, and selected kernel algorithms written in LISP and PARIS was developed for the CM-2. Experiment runs are automated via a software framework that sequences individual tests, allowing for unattended overnight operation. Multiple measurements are made and treated statistically to generate well-characterized results from the noisy values given by cm:time. The results obtained provide a comparison with similar, but less extensive, testing done on a CM-1. Tests were chosen to aid the algorithmist in constructing fast, efficient, and correct code on the CM-2, as well as gain insight into what performance criteria are needed when evaluating parallel processing machines.

Myers, David W.↗

NASA NTRS1991

LinkFinder: An expert system that constructs phylogenic trees

An expert system has been developed using the C Language Integrated Production System (CLIPS) that automates the process of constructing DNA sequence based phylogenies (trees or lineages) that indicate evolutionary relationships. LinkFinder takes as input homologous DNA sequences from distinct individual organisms. It measures variations between the sequences, selects appropriate proportionality constants, and estimates the time that has passed since each pair of organisms diverged from a common ancestor. It then designs and outputs a phylogenic map summarizing these results. LinkFinder can find genetic relationships between different species, and between individuals of the same species, including humans. It was designed to take advantage of the vast amount of sequence data being produced by the Genome Project, and should be of value to evolution theorists who wish to utilize this data, but who have no formal training in molecular genetics. Evolutionary theory holds that distinct organisms carrying a common gene inherited that gene from a common ancestor. Homologous genes vary from individual to individual and species to species, and the amount of variation is now believed to be directly proportional to the time that has passed since divergence from a common ancestor. The proportionality constant must be determined experimentally; it varies considerably with the types of organisms and DNA molecules under study. Given an appropriate constant, and the variation between two DNA sequences, a simple linear equation gives the divergence time.

Inglehart, James↗

NASA NTRS1992

Learning class descriptions from a data base of spectral reflectance with multiple view angles

A learning program has been developed which combines 'learning by example' with the generate-and-test paradigm to furnish a robust learning environment capable of handling error-prone data. The problem is shown to be capable of learning class descriptions from positive and negative training examples of spectral and directional reflectance data taken from soil and vegetation. The program, which used AI techniques to automate very tedious processes, found the sequence of relationships that contained the most important information which could distinguish the classes.

Kimes, Daniel S.↗

NASA NTRS2020

A Flight Rule Checker for the LADEE Lunar Spacecraft

As part of the design of a space mission, an important part is the design of so-called flight rules. Flight rules express constraints on various parts and processes of the mission, that if followed, will reduce the risk of failure. One such set of flight rules constrain the format of command sequences regularly (e.g. daily) sent to the spacecraft to con- trol its next near term behavior. We present a high-level view of the automated flight rule checker Frc for checking command sequences sent to NASA’s LADEE Lunar mission spacecraft, used throughout its entire mission. A command sequence is in this case essentially a program (a sequence of commands) with no loops or conditionals, and it can there- fore be verified with a trace analysis tool. Frc is implemented using the TraceContract runtime verification tool, an internal Scala DSL for checking event sequences against “formal specifications”. The paper illustrates this untraditional use of runtime verification in a real con- text, with strong demands on the expressiveness and flexibility of the specification language, illustrating the advantages of an internal DSL.

Kurklu, Elif↗

NASA NTRS2020

A Flight Rule Checker for the LADEE Lunar Spacecraft

As part of the design of a space mission, an important part is the design of so-called flight rules. Flight rules express constraints on various parts and processes of the mission, that if followed, will reduce the risk of failure. One such set of flight rules constrain the format of command sequences regularly (e.g. daily) sent to the spacecraft to con-trol its next near term behavior. We present a high-level view of the automated flight rule checker FRC for checking command sequences sent to NASA’s LADEE Lunar mission spacecraft, used throughout its entire mission. A command sequence is in this case essentially a program (a sequence of commands) with no loops or conditionals, and it can there-fore be verified with a trace analysis tool. FRC is implemented using the TraceContract runtime verification tool, an internal Scala DSL for checking event sequences against “formal specifications”. The paper illustrates this untraditional use of runtime verification in a real con-text, with strong demands on the expressiveness and flexibility of the specification language, illustrating the advantages of an internal DSL.

LADEE↗

NASA NTRS1994

Engineering Analysis Subsystem Environment for Spacecraft Engineering Subsystem Mission Operations

The Engineering Analysis Subsystem Environment (EASE) prototype is a collection of computer programs on networked workstations providing a multimission, multisubsystem environment that enables the operation of several spacecraft simultaneously with fewer analysts. Through the use of automated tools, graphical data visualization and information management, EASE has achieved an increase in mission operations productivity. Recently, a database, a trending tool, and a power sequence expansion tool have been added to EASE. This paper discusses these enhancements and provides an update of the operation experience with the realtime Galileo telemetry data.

EASE↗

NASA NTRS1988

Observation of sea-ice dynamics using synthetic aperture radar images: Automated analysis

The European Space Agency's ERS-1 satellite, as well as others planned to follow, is expected to carry synthetic-aperture radars (SARs) over the polar regions beginning in 1989. A key component in utilization of these SAR data is an automated scheme for extracting the sea-ice velocity field from a time sequence of SAR images of the same geographical region. Two techniques for automated sea-ice tracking, image pyramid area correlation (hierarchical correlation) and feature tracking, are described. Each technique is applied to a pair of Seasat SAR sea-ice images. The results compare well with each other and with manually tracked estimates of the ice velocity. The advantages and disadvantages of these automated methods are pointed out. Using these ice velocity field estimates it is possible to construct one sea-ice image from the other member of the pair. Comparing the reconstructed image with the observed image, errors in the estimated velocity field can be recognized and a useful probable error display created automatically to accompany ice velocity estimates. It is suggested that this error display may be useful in segmenting the sea ice observed into regions that move as rigid plates of significant ice velocity shear and distortion.

Vesecky, John F.↗