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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Arm DevSummit Keynote: Environment for Data Engineering in Virtual Reality: Ethical Considerations

Currently, the US Government is going through a large-scale data Transformation effort, where the GSA playbook is guiding all agencies to make their processes data-driven with the help of emerging technologies. To address concerns about algorithm sharing, AI adoption, and vendor lock-in, the NASA Langley Research Center Digital Transformation Group has developed the Environment for Data Engineering in Virtual Reality (EnDEVR), a data science ecosystem that allows users to command and investigate customizable data analyses from a VR environment. The system has been evaluated in the Oculus Rift S and Quest environments, two popular VR systems powered by the ARM architecture. Current and future development will employ several AI capabilities to guide research and automation within the environment and to facilitate algorithm sharing. In this talk, we will discuss the results of an initial ethical investigation and recommended considerations for the use of AI within the system.

Artificial Intelligence↗
NASA NTRS2021

NASA in Silicon Valley

Whether looking back only a few years or more than a century, our world has been changing. Communication networks are more widespread and interconnected than at any other time in human history. Computing power that was only imagined a generation ago is now widely available and can fit in the palm of a hand. The miniaturization of the integrated circuit has brought us close to the limit of what is possible with silicon as we explore new possibilities in the quantum realm. For over 80 years, NASA’s Ames Research Center in California’s Silicon Valley has held a special place amidst such change. With change, there also is continuity. Since 1939, Ames contributions have fundamentally shaped fields of study related to aeronautics and space. The ingenuity and problem-solving capabilities of personnel at Ames have affected all our lives in numerous ways, from everyday air travel to how we envision the possibility of life on other worlds. This publication is a mere hint at the rich history of Ames, told primarily through images that capture some of the recurring threads that have intertwined over that time. A bibliography points the reader to more detailed histories of Ames published over the years. They are excellent resources and, like all historical work, unavoidably incomplete. Our standing invitation in the present is to preserve what we can to help us understand where we are and how we arrived.

History↗
NASA NTRS2022

Cockpit Interface for Locomotion and Manipulation Control of the NASA Valkyrie Humanoid in Virtual Reality (VR)

A virtual reality (VR) interface is presented for controlling NASA’s Valkyrie humanoid robot with flexible locomotion control options and intuitive teleoperation. Locomotion modes include navigating to a specified waypoint, sending desired velocities with a joystick, or manually placing a sequence of footsteps. On the other hand, teleoperation modes include voice commands to toggle relative whole-body tracking or high-level commandeering, and key bindings for common stored poses such as power grasps. The primary novelties of the interface are in the implementation of the cockpit mode and a floating augmented reality (AR) screen fixed with respect to the robot. The former enables embodied teleoperation and increased awareness during navigation in a mixed-reality setting. The latter preserves depth perception without the disparity clutter from a stereo point cloud. The interface is demonstrated on two real humanoids performing common explosive ordnance disposal (EOD) tasks such as door opening, vehicle inspection, and disruptor placement. Notably, the interface enables a single operator to control multiple humanoids. While the interface is motivated by EOD missions, the presented ideas are usable for other robots employing VR-based control.

Virtual-reality↗
NASA NTRSDate not supplied

Enabling Communication Between Astronauts and Ground Teams for Space Exploration Missions

Over the last four years, Playbook’s Mission Log has evolved to become an enabling capability for analog missions that simulate deep space, exploration missions with communication transmission latency. Playbook is a planning and execution web-application for mission operations, aggregating multiple sources of information for astronauts to execute the mission in one place: timeline, procedures, chat interface. Playbook’s Mission Log provides a multimedia chat software interface with unique features and functionalities that support asynchronous communication between analog astronauts and ground support teams. This paper describes the iterative design the Mission Log has undergone based on user observations and solicited feedback. Key features include indicators that help users cope with asynchronous communication as well as aids that assist teams coordinate work. Future work and capabilities are outlined, which build upon the increased use of the Mission Log as a communication and coordination tool for space exploration.

communication↗
NASA NTRSDate not supplied

Inferring Collaboration Strategies and Usability from Remote Observations in a Spaceflight Analog Environment

Collecting usability and user evaluations of novel software in spaceflight analog missions is challenging. For one such analog mission, we collected audio recordings of crew members as they completed their assigned self-scheduling task using novel software. Conversation analysis provided insight about collaborative nature of task and potential new evaluation measures.

human computer interaction↗
NASA NTRS2022

Virtual Assistant for First Responders Using Natural Language Understanding and Optical Character Recognition

Commercial deep learning capabilities are available for many applications such as computer vision processing and intelligent chat bots. The Google Cloud Platform product Google Dialogflow provides lifelike conversational artificial intelligence (AI) using machine learning (ML) to generate natural conversations between computers and humans. This ML utilizes natural language understanding (NLU) to recognize a user’s intent and extracts key information into a form of entities. We have developed a user-friendly application through understanding the hazardous material database, first aid safety guidelines and observing the process of first responders who access this information in the field. We created the Trusted and Explainable Artificial Intelligence for Saving Lives (TruePAL) virtual assistant using Dialogflow1 and TensorFlow2 paired with EasyOCR.3 The chatbot supports first responders by providing voice interaction which helps limit additional steps such as browsing through multiple categories when searching for information. Using feedback from our field interviews, the voice interface has been developed to enable the first responder to focus on the immediate emergency. With less distractions, the first responder is able to engage the incident more effectively. The partial hands-free TruePAL chatbot assistant improves the accessibility to the correct guidance by an average of 1.9 seconds compared to the widely used application, NIH WISER, which requires full attention to operate. We combined this intelligent chatbot with a separate visual processing capability to produce hazardous signage analysis and generate the proper guidance for first responders. With the evolving functionality of AI tools, the use of virtual assistants in first responder technology will be an advancement, benefiting the safety of both first responders and civilians.

Chow, Edward↗
NASA NTRS2024

Usability Evaluation of NASA TOPS Open Science 101

This report presents a usability evaluation of NASA’s Open Science 101 (OS101) interface. It offers design recommendations for improving the user experience (UX) and user interface (UI) of the initial self-paced OS101 release. The author initially conducted an independent heuristic evaluation, followed by an analysis of written user feedback to corroborate findings. Overall, the usability evaluation found that the OS101 interface offers a linear and interactive UX, with areas for improvement across five major, three minor, and two cosmetic aspects of usability.

Human-Computer Interaction↗
NASA NTRSDate not supplied

Informing NLP Learning Tasks by Tracking User Features: An ASRS Use Case using Kaona

There has been growing interest in utilizing natural language processing (NLP) algorithms in Aviation Safety. This interest has extended to leveraging the decades of records publicly available on the Aviation Safety Reporting System (ASRS). While related literature has given more emphasis in lessons learned from the narratives, our prior work has focused on using NLP to support narrative search in the ASRS. Specifically, we evaluated if the use of alternative search mechanisms to keyword search, such as the retrieval of related narratives even without matching keywords could improve narrative discovery. A difficulty in experimenting alternative search mechanisms in any information retrieval task is the lack of ground truth. To address this limitation, we propose Kaona, a lightweight interface which enables the prototyping of alternative search retrieval tasks, by tracking user experience both explicitly (user-specified feedback), or implicitly (user navigation through interface affordances). Differently from distracting requests for feedback during user navigation, Kaona collects explicit feedback from users by mapping them to affordances which support the user workflow, while obtaining ground truth information for learning tasks.

human-computer-interaction↗
NASA NTRSDate not supplied

Kaona: Deep Searching and Curating Data from Aviation Safety Reporting Systems

Context: Several works in the literature have examined how safety narrative databases can be leveraged to share lessons learned. However, less attention has been given to augmenting existing processes for mining these safety reporting system databases. Aim: In this work, we introduce Kaona: An interface that weaves machine learning in existing aviation safety database mining activities. Method: We provide a use case of search, curation and newsletter writing to showcase how Kaona features build on existing processes and on its own to enhance information retrieval, curation and synthesis of narratives. Results: We created two instances of Kaona internally for evaluation, one using publicly available NASA’s ASRS narratives and another using publicly available C3RS narratives. Data ranged from 1998 to 2024. Conclusion: Our tool provides a new way to explore safety narratives, serving to re-imagine how text databases can benefit of novel information retrieval mechanisms in the era of large language models.

ASRS↗
NASA NTRSDate not supplied

Kaona: Deep Searching and Curating Aviation Safety Reporting Systems

Context: Several works in the literature have examined how safety narrative databases can be leveraged to share lessons learned. However, less attention has been given in augmenting existing processes of safety reporting systems. Aim: In this work, we introduce Kaona: An interface that weaves machine learning in existing aviation safety reporting systems activities. Method: We provide a use case of search, curation and newsletter writing to showcase how Kaona features build on existing processes and on its own to enhance information retrieval, curation and synthesis of narratives. Results: We created two instances of Kaona internally for evaluation, one using all public NASA's ASRS narratives and another using all public C3RS narratives. Data ranged from 1998 to 2024. Conclusion: Our tool provides a new way to explore safety narratives, serving to re-imagine how text databases can benefit of novel information retrieval mechanisms in the era of large language models.

asrs↗
NASA NTRSDate not supplied

Kaona: Deep Searching and Curating Safety Reporting Systems

Context: Several works in the literature have examined how safety narrative databases can be leveraged to share lessons learned. However, less attention has been given in augmenting existing processes of safety reporting systems. Aim: In this work, we introduce Kaona: An interface that weaves machine learning in existing aviation safety reporting systems activities. Method: We provide a use case of search, curation and newsletter writing to showcase how Kaona features build on existing processes and on its own to enhance information retrieval, curation and synthesis of narratives. Results: We created two instances of Kaona internally for evaluation, one using all public NASA's ASRS narratives and another using all public C3RS narratives. Data ranged from 1998 to 2024. Conclusion: Our tool provides a new way to explore safety narratives, serving to re-imagine how text databases can benefit of novel information retrieval mechanisms in the era of large language models.

asrs↗
NASA NTRS1994

Application Reuse Library for Software, Requirements, and Guidelines

Better designs are needed for expert systems and other operations automation software, for more reliable, usable and effective human support. A prototype computer-aided Application Reuse Library shows feasibility of supporting concurrent development and improvement of advanced software by users, analysts, software developers, and human-computer interaction experts. Such a library expedites development of quality software, by providing working, documented examples, which support understanding, modification and reuse of requirements as well as code. It explicitly documents and implicitly embodies design guidelines, standards and conventions. The Application Reuse Library provides application modules with Demo-and-Tester elements. Developers and users can evaluate applicability of a library module and test modifications, by running it interactively. Sub-modules provide application code and displays and controls. The library supports software modification and reuse, by providing alternative versions of application and display functionality. Information about human support and display requirements is provided, so that modifications will conform to guidelines. The library supports entry of new application modules from developers throughout an organization. Example library modules include a timer, some buttons and special fonts, and a real-time data interface program. The library prototype is implemented in the object-oriented G2 environment for developing real-time expert systems.

Malin, Jane T.↗
NASA NTRS1993

Development of biomechanical models for human factors evaluations

Computer aided design (CAD) techniques are now well established and have become the norm in many aspects of aerospace engineering. They enable analytical studies, such as finite element analysis, to be performed to measure performance characteristics of the aircraft or spacecraft long before a physical model is built. However, because of the complexity of human performance, CAD systems for human factors are not in widespread use. The purpose of such a program would be to analyze the performance capability of a crew member given a particular environment and task. This requires the design capabilities to describe the environment's geometry and to describe the task's requirements, which may involve motion and strength. This in turn requires extensive data on human physical performance which can be generalized to many different physical configurations. PLAID is developing into such a program. Begun at Johnson Space Center in 1977, it was started to model only the geometry of the environment. The physical appearance of a human body was generated, and the tool took on a new meaning as fit, access, and reach could be checked. Specification of fields-of-view soon followed. This allowed PLAID to be used to predict what the Space Shuttle cameras or crew could see from a given point.

Woolford, Barbara↗
NASA NTRS1980

Computer measurement of arterial disease

Image processing technique quantifies human atherosclerosis by computer analysis of arterial angiograms. X-ray film images are scanned and digitized, arterial shadow is tracked, and several quantitative measures of lumen irregularity are computed. In other tests, excellent agreement was found between computer evaluation of femoral angiograms on living subjects and evaluation by teams of trained angiographers.

Armstrong, J.↗
NASA NTRS1977

Multi-attribute subjective evaluations of manual tracking tasks vs. objective performance of the human operator

A computational method to deal with the multidimensional nature of tracking and/or monitoring tasks is developed. Operator centered variables, including the operator's perception of the task, are considered. Matrix ratings are defined based on multidimensional scaling techniques and multivariate analysis. The method consists of two distinct steps: (1) to determine the mathematical space of subjective judgements of a certain individual (or group of evaluators) for a given set of tasks and experimental conditionings; and (2) to relate this space with respect to both the task variables and the objective performance criteria used. Results for a variety of second-order trackings with smoothed noise-driven inputs indicate that: (1) many of the internally perceived task variables form a nonorthogonal set; and (2) the structure of the subjective space varies among groups of individuals according to the degree of familiarity they have with such tasks.

Siapkaras, A.↗
NASA NTRS1995

Simulating Human Cognition in the Domain of Air Traffic Control

Experiments intended to assess performance in human-machine interactions are often prohibitively expensive, unethical or otherwise impractical to run. Approximations of experimental results can be obtained, in principle, by simulating the behavior of subjects using computer models of human mental behavior. Computer simulation technology has been developed for this purpose. Our goal is to produce a cognitive model suitable to guide the simulation machinery and enable it to closely approximate a human subject's performance in experimental conditions. The described model is designed to simulate a variety of cognitive behaviors involved in routine air traffic control. As the model is elaborated, our ability to predict the effects of novel circumstances on controller error rates and other performance characteristics should increase. This will enable the system to project the impact of proposed changes to air traffic control procedures and equipment on controller performance.

Freed, Michael↗
NASA NTRS2001

Where to look? Automating attending behaviors of virtual human characters

This research proposes a computational framework for generating visual attending behavior in an embodied simulated human agent. Such behaviors directly control eye and head motions, and guide other actions such as locomotion and reach. The implementation of these concepts, referred to as the AVA, draws on empirical and qualitative observations known from psychology, human factors and computer vision. Deliberate behaviors, the analogs of scanpaths in visual psychology, compete with involuntary attention capture and lapses into idling or free viewing. Insights provided by implementing this framework are: a defined set of parameters that impact the observable effects of attention, a defined vocabulary of looking behaviors for certain motor and cognitive activity, a defined hierarchy of three levels of eye behavior (endogenous, exogenous and idling) and a proposed method of how these types interact.

NASA Discipline Space Human Factors↗
NASA NTRS2018

Do You See What I See? Interactive Visualization of Mission Design and Navigation

Mission Design and Navigation (MDNav) is an intensive process requiring advanced computational resources, expert human intuition, and many successive human-in-the-loop iterations to converge on acceptable trajectory designs or navigation solutions. The current bottleneck in MDNav is not the underlying computational algorithms but the human cognitive capacity to prune through a multitude of simulated results to select high-value candidates. One approach to alleviate this burden is through the judicious application of visualizations that allow humans to interactively filter data in multiple dimensions to reveal salient patterns and highlight divergences. When designed efficiently, such interactive visualizations should aid human operators to get familiar with data faster, visually observe correlations, and communicate findings more effortlessly. In this work, we present three visualization case studies that have the potential to increase human operator efficiency in MDNav. While identifying the most critical “pain points” that operators face, and also working on potential solutions, we followed a human-centered design approach. We started with a series of interviews with potential users, and then rapidly created prototypes for alternative solutions, validated outcomes with feedback from users through out development of these proof of concept visualizations. With this survey of our current efforts, we demonstrate the transformative capability of interactive data visualizations for improving mission development and operations, enabling operators to grow intuition, and communicating key concepts across diverse mission teams.

Arora, Nitin↗