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NASA NTRS1981

Automated Decision Making and Problem Solving. Volume 1: Executive Summary

The May 1980 conference is summarized. Related topics in artificial intelligence, operations research, and control theory were explored. Existing techniques were assessed, trends of development determined, and potential for application in NASA automation technology programs were identified. Formal presentations were made by experts in the three disciplines nd a workshop was held in which current technology in automation and possible NASA interfaces with the academic community to advance this technology were discussed.

Heer, E.↗
NASA NTRS2005

Expedition Memory: Towards Agent-based Web Services for Creating and Using Mars Exploration Data.

Explorers ranging over kilometers of rugged, sometimes "feature-less" terrain for over a year could be overwhelmed by tracking and sharing what they have done and learned. An automated system based on the existing Mobile Agents design [ I ] and Mars Exploration Rover experience [2], could serve as an "expedition memory" that would be indexed by voice as wel1 as a web interface, linking people, places, activities, records (voice notes, photographs, samples). and a descriptive scientific ontology. This database would be accessible during EVAs by astronauts, annotated by the remote science team, linked to EVA plans, and allow cross indexing between sites and expeditions. We consider the basic problem, our philosophical approach, technical methods, and uses of the expedition memory for facilitating long-term collaboration between Mars crews and Earth support teams. We emphasize that a "memory" does not mean a database per se, but an interactive service that combines different resources, and ultimately could be like a helpful librarian.

Clancey, William J.↗
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 NTRS1991

Human factors issues in the use of artificial intelligence in air traffic control. October 1990 Workshop

The objective of the workshop was to explore the role of human factors in facilitating the introduction of artificial intelligence (AI) to advanced air traffic control (ATC) automation concepts. AI is an umbrella term which is continually expanding to cover a variety of techniques where machines are performing actions taken based upon dynamic, external stimuli. AI methods can be implemented using more traditional programming languages such as LISP or PROLOG, or they can be implemented using state-of-the-art techniques such as object-oriented programming, neural nets (hardware or software), and knowledge based expert systems. As this technology advances and as increasingly powerful computing platforms become available, the use of AI to enhance ATC systems can be realized. Substantial efforts along these lines are already being undertaken at the FAA Technical Center, NASA Ames Research Center, academic institutions, industry, and elsewhere. Although it is clear that the technology is ripe for bringing computer automation to ATC systems, the proper scope and role of automation are not at all apparent. The major concern is how to combine human controllers with computer technology. A wide spectrum of options exists, ranging from using automation only to provide extra tools to augment decision making by human controllers to turning over moment-by-moment control to automated systems and using humans as supervisors and system managers. Across this spectrum, it is now obvious that the difficulties that occur when tying human and automated systems together must be resolved so that automation can be introduced safely and effectively. The focus of the workshop was to further explore the role of injecting AI into ATC systems and to identify the human factors that need to be considered for successful application of the technology to present and future ATC systems.

Hockaday, Stephen↗
NASA NTRS2008

Semi-Automated Diagnosis, Repair, and Rework of Spacecraft Electronics

NASA's Constellation Program for Exploration of the Moon and Mars places human crews in extreme isolation in resource scarce environments. Near Earth, the discontinuation of Space Shuttle flights after 2010 will alter the up- and down-mass capacity for the International Space Station (ISS). NASA is considering new options for logistics support strategies for future missions. Aerospace systems are often composed of replaceable modular blocks that minimize the need for complex service operations in the field. Such a strategy however, implies a robust and responsive logistics infrastructure with relatively low transportation costs. The modular Orbital Replacement Units (ORU) used for ISS requires relatively large blocks of replacement hardware even though the actual failed component may really be three orders of magnitude smaller. The ability to perform in-situ repair of electronics circuits at the component level can dramatically reduce the scale of spares and related logistics cost. This ability also reduces mission risk, increases crew independence and improves the overall supportability of the program. The Component-Level Electronics Assembly Repair (CLEAR) task under the NASA Supportability program was established to demonstrate the practicality of repair by first investigating widely used soldering materials and processes (M&P) performed by modest manual means. The work will result in program guidelines for performing manual repairs along with design guidance for circuit reparability. The next phase of CLEAR recognizes that manual repair has its limitations and some highly integrated devices are extremely difficult to handle and demand semi-automated equipment. Further, electronics repairs require a broad range of diagnostic capability to isolate the faulty components. Finally repairs must pass functional tests to determine that the repairs are successful and the circuit can be returned to service. To prevent equipment demands from exceeding spacecraft volume capacity and skill demands from exceeding crew time and training limits, the CLEAR project is examining options provided by non-real time tele-operations, robotics, and a new generation of diagnostic equipment. This paper outlines a strategy to create an effective repair environment where, with the support of ground based engineers, crewmembers can diagnose, repair and test flight electronics in-situ. This paper also discusses the implications of successful tele-robotic repairs when expanded to rework and reconfiguration of used flight assets for building Constellation infrastructure elements.

Struk, Peter M.↗
NASA NTRS2011

Demonstration of a Particle Impact Monitoring System for Crewed Space Exploration Modules

When micrometeorite or debris impacts occur on a space habitat, crew members need to be quickly informed of the likely extent of damage, and be directed to the impact location for possible repairs. The goal of the Habitat Particle Impact Monitoring System (HIMS) is to develop a fully automated, end-to-end particle impact detection system for crewed space exploration modules, both in space and on the surfaces of Solar System bodies. The HIMS uses multiple thin film piezo-polymer vibration sensors to detect impacts on a surface, and computer processing of the acoustical signals to characterize the impacts. Development and demonstration of the HIMS is proceeding in concert with NASA's Habitat Demonstration Unit (HDU) Project. The HDU Project is designed to develop and test various technologies, configurations, and operational concepts for exploration habitats. This paper describes the HIMS development, initial testing, and HDU integration efforts. Initial tests of the system on the HDU were conducted at NASA?s 2010 Desert Research and Technologies Studies (Desert-RATS). Four sensor locations were assigned near the corners of a rectangular pattern. To study the influence of wall thickness, three sets of four sensors were installed at different layer depths: on the interior of the PEM wall, on the exterior of the same wall, and on the exterior of a layer of foam insulation applied to the exterior wall. Once the system was activated, particle impacts were periodically applied by firing a pneumatic pellet gun at the exterior wall section. Impact signals from the sensors were recognized by a data acquisition system when they occurred, and recorded on a computer for later analysis. Preliminary analysis of the results found that the HIMS system located the point of impact to within 8 cm, provided a measure of the impact energy / damage produced, and was insensitive to other acoustic events. Based on this success, a fully automated version of this system will be completed and demonstrated as part of a crew "Caution/Warning" system at the 2011 Desert-RATS, along with a crew response procedure.

Opiela, J. N.↗
NASA NTRS1990

Shared direct memory access on the Explorer 2-LX

Advances in Expert System technology and Artificial Intelligence have provided a framework for applying automated Intelligence to the solution of problems which were generally perceived as intractable using more classical approaches. As a result, hybrid architectures and parallel processing capability have become more common in computing environments. The Texas Instruments Explorer II-LX is an example of a machine which combines a symbolic processing environment, and a computationally oriented environment in a single chassis for integrated problem solutions. This user's manual is an attempt to make these capabilities more accessible to a wider range of engineers and programmers with problems well suited to solution in such an environment.

Musgrave, Jeffrey L.↗
NASA NTRS2017

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools I: Human-Autonomy Teaming Fundamentals and State of the Art

Recent advances in artificial intelligence, machine learning, data mining and extraction, and especially in sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the first of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explore fundamental issues associated with the development of an integrated, dynamic, flight information and automation management system. We discuss human factors issues pertaining to information automation and review the current state of the art of pilot information management and decision support tools. We also explore how effective human-human team behavior and expectations could be extended to teams involving humans and automation or autonomous systems.

context-sensitive↗
NASA NTRS1969

Use of man in space.

Tradeoff criteria between man machine and automated space systems applied to lunar and cosmic ray explorations

Howard, B.↗
NASA NTRS1991

Software fault tolerance using data diversity

Research on data diversity is discussed. Data diversity relies on a different form of redundancy from existing approaches to software fault tolerance and is substantially less expensive to implement. Data diversity can also be applied to software testing and greatly facilitates the automation of testing. Up to now it has been explored both theoretically and in a pilot study, and has been shown to be a promising technique. The effectiveness of data diversity as an error detection mechanism and the application of data diversity to differential equation solvers are discussed.

Knight, John C.↗
NASA NTRS1996

Spacecraft control center automation using the generic inferential executor (GENIE)

The increasing requirement to dramatically reduce the cost of mission operations led to increased emphasis on automation technology. The expert system technology used at the Goddard Space Flight Center (MD) is currently being applied to the automation of spacecraft control center activities. The generic inferential executor (GENIE) is a tool which allows pass automation applications to be constructed. The pass script templates constructed encode the tasks necessary to mimic flight operations team interactions with the spacecraft during a pass. These templates can be configured with data specific to a particular pass. Animated graphical displays illustrate the progress during the pass. The first GENIE application automates passes of the solar, anomalous and magnetospheric particle explorer (SAMPEX) spacecraft.

Hartley, Jonathan↗
NASA NTRS2008

Next Generation Advanced Video Guidance Sensor

The first autonomous rendezvous and docking in the history of the U.S. Space Program was successfully accomplished by Orbital Express, using the Advanced Video Guidance Sensor (AVGS) as the primary docking sensor. The United States now has a mature and flight proven sensor technology for supporting Crew Exploration Vehicles (CEV) and Commercial Orbital Transport. Systems (COTS) Automated Rendezvous and Docking (AR&D). AVGS has a proven pedigree, based on extensive ground testing and flight demonstrations. The AVGS on the Demonstration of Autonomous Rendezvous Technology (DART)mission operated successfully in "spot mode" out to 2 km. The first generation rendezvous and docking sensor, the Video Guidance Sensor (VGS), was developed and successfully flown on Space Shuttle flights in 1997 and 1998. Parts obsolescence issues prevent the construction of more AVGS. units, and the next generation sensor must be updated to support the CEV and COTS programs. The flight proven AR&D sensor is being redesigned to update parts and add additional. capabilities for CEV and COTS with the development of the Next, Generation AVGS (NGAVGS) at the Marshall Space Flight Center. The obsolete imager and processor are being replaced with new radiation tolerant parts. In addition, new capabilities might include greater sensor range, auto ranging, and real-time video output. This paper presents an approach to sensor hardware trades, use of highly integrated laser components, and addresses the needs of future vehicles that may rendezvous and dock with the International Space Station (ISS) and other Constellation vehicles. It will also discuss approaches for upgrading AVGS to address parts obsolescence, and concepts for minimizing the sensor footprint, weight, and power requirements. In addition, parts selection and test plans for the NGAVGS will be addressed to provide a highly reliable flight qualified sensor. Expanded capabilities through innovative use of existing capabilities will also be discussed.

Lee, Jimmy↗
NASA NTRSDate not supplied

A Hybrid Approach to Labeling Datasets in Earth Science Publications

NASA Data Centers provide the public with thousands of datasets that result in published papers, reports, and conference proceedings. Collecting accurate metrics on usage of these datasets is key to connecting different areas of knowledge and evaluating the datasets’ impact. While most of the datasets have Digital Object Identifiers (DOIs) assigned, most publications do not cite them hampering the automated search of these publications. Instead, articles mention attributes like organization, instrument, mission, variable, or a publication describing the dataset. Often only domain experts can deduce the dataset that was used in the publication text. The lack of a citation slows the spread of information and reduces the research’s impact. With thousands of papers produced each year, an automated means of labeling datasets is critical. This paper explores a hybrid approach of heuristics and a Natural Language Processing (NLP) Named Entity Recognition (NER) model to find and label the datasets used within Earth Science papers. Heuristics are used to produce the labelled sentences and any potential dataset candidates that can be derived from a sentence. The heuristic labels the sentences with the names of mission, instrument, re-analysis models, and science keywords taken from the Global Change Master Directory (GCMD) ontology. Additionally, it uses those labels to generate the dataset citation candidates. If the mission, instrument, and variable are sufficient to create the citation for the dataset the citation and the label the domain expert reviews the output without going through the NLP model. If the extracted label is not sufficient to label the dataset on its own, the sentence and its associated dataset labels will be inputted into the NER model. The model outputs the labeled sentence and the potential dataset candidates with their associated probabilities. The domain expert then reviews the NER model’s output and the correct labels are determined. The newly labelled papers can then be used as additional training data. This creates an iterative process for the approach to continuously improve. Because all the possible mentions are gathered by the model, the domain expert can quickly and easily label the papers resulting in large time savings.

Jacob Atkins↗
NASA NTRS1993

Toward an Autonomous Feature-based Pointing System for Planetary Missions

Although the analytical groundwork for understanding two-dimensional object images and various aspects of computer vision has been laid, we have not yet applied these concepts to automating the process of obtaining science images during space exploration missions. Our current approach in specifying pointing-command sequences relies heavily on target predicts, based on predicted target and spacecraft ephemerides, that propagate the target position as a function of time during pointing operations.

Computer↗
NASA NTRS2022

NASA System-Wide Safety Wildland Firefighting Operations Workshop Report

On March 9-11, 2022, NASA’s System-Wide Safety Wildland Firefighting Operations Workshop engaged the broader wildland firefighting management ecosystem in a safety-oriented discussion via a virtual platform. This enabled a better understanding of how NASA and community expertise can be leveraged in the safe development of current and future firefighting systems and operations. The goals of the workshop were to: (1) identify and prioritize the top safety-oriented risks, gaps in capabilities, and emerging technologies to enhance wildland firefighting for both near-term and far-term concepts, with a specific focus on aviation operations and (2) engage the stakeholder community in defining emergent safety-oriented scope, roles, responsibilities, and procedures for agents undergoing increasingly complex wildland firefighting operations in information-rich, but uncertain environments. Workshop participants were solicited from wildland firefighting stakeholders across government, industry, and academia. All levels of government were engaged, as NASA sought attendees from federal, state, local, and tribal government agencies. Industry participants from traditional wildland firefighting domains such as data visualization and equipment manufacturers were invited, and corporate attendees from novel application domains such as aerial robotics and autonomous systems were present as well. The top three findings were as follows: (1) Enhancing situation awareness is a safety priority, especially in the use of aerial assets; (2) Timely access to information along with data fusion and integrated displays will enhance safety-critical decision-making both inside and outside aviation contexts; and (3) Tailorable standards and common operating pictures in the field will enhance inter-agency cooperation in the wildland firefighting lifecycle and enable the optimal use of limited resources such as aerial assets. The workshop helped inform NASA of the relevant safety-related wildland firefighting concerns and aided the broader ecosystem in understanding the potential safety-oriented role NASA might play in this community. Increased engagement with crucial governmental stakeholders (e.g., U.S. Forest Service, CAL FIRE, etc.) along with industry partners in cutting- edge information -centric domains is a fundamental next step. Additionally, the workshop findings will help define the first of a series of operationally challenging demonstrations, held in concert with strategic ecosystem partners, known as the Safety Demonstrator Series for NASA’s System-Wide Safety project. The first demonstration is set in the wildland firefighting application domain and will: (1) examine high risk operational scenarios to reduce their overall risk via services, functions or capabilities that act as risk mitigators (or transfer that risk to automated systems better able to tolerate it) and (2) explore novel tools and technologies that will enhance safety margins by enabling non-traditional or neoteric operational paradigms.

wildland firefighting↗
NASA NTRSDate not supplied

The Role of Trust and Usability in Enabling Spaceflight Crew Autonomy

Future long duration exploration missions will require an increased use of onboard automated systems as spaceflight crews venture further than before and have longer communications delays with ground support. The design of these systems must support appropriate crew trust and have sufficient usability to enable spaceflight crew autonomy or risk being misused while crews wait to communicate with ground support. We evaluated trust & usability in our self-scheduling tool, Playbook, for crew mission timelines. Data was collected in a controlled lab experiment with 31 participants. Participants in the study conducted two tasks: scheduling, where participants were responsible for scheduling a majority of a day's operational tasks, and rescheduling, where participants were provided a schedule and asked to reschedule higher priority activities. We found a significant correlation between system trust and usability, irrespective of self-scheduling tasks. We conclude that system usability may play a bigger role in how trust is learned while conducting novel crew autonomy tasks such as self-scheduling. Future research should investigate the role of usability to encourage appropriate trust in onboard automated crew systems and enable crew autonomy.

crew autonomy↗
NASA NTRS1975

Automation in space

The effective use of automatic machines and equipment in space exploration is discussed. Special attention was given to the problem of interacting people and automatic devices. Data are given on computer data processing, planet rovers, and long term orbital stations.

Petrov, B.↗