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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.

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Human Centered Autonomous and Assistant Systems Testbed for Exploration Operations

The Engineering and Mission Operations Directorates at NASA Johnson Space Center are combining laboratories and expertise to establish the Human Centered Autonomous and Assistant Systems Testbed for Exploration Operations. This is a testbed for human centered design, development and evaluation of intelligent autonomous and assistant systems that will be needed for human exploration and development of space. This project will improve human-centered analysis, design and evaluation methods for developing intelligent software. This software will support human-machine cognitive and collaborative activities in future interplanetary work environments where distributed computer and human agents cooperate. We are developing and evaluating prototype intelligent systems for distributed multi-agent mixed-initiative operations. The primary target domain is control of life support systems in a planetary base. Technical approaches will be evaluated for use during extended manned tests in the target domain, the Bioregenerative Advanced Life Support Systems Test Complex (BIO-Plex). A spinoff target domain is the International Space Station (ISS) Mission Control Center (MCC). Prodl}cts of this project include human-centered intelligent software technology, innovative human interface designs, and human-centered software development processes, methods and products. The testbed uses adjustable autonomy software and life support systems simulation models from the Adjustable Autonomy Testbed, to represent operations on the remote planet. Ground operations prototypes and concepts will be evaluated in the Exploration Planning and Operations Center (ExPOC) and Jupiter Facility.

Malin, Jane T.↗

Considerations for Implementing Voice-Controlled Spacecraft Systems Through a Human-Centered Design Approach

As computational power and speech recognition algorithms improve, the consumer market will see better-performing speech recognition applications. The cell phone and Internet-related service industry have further enhanced speech recognition applications using artificial intelligence and statistical data-mining techniques. These improvements to speech recognition technology (SRT) may one day help astronauts on future deep space human missions that require control of complex spacecraft systems or spacesuit applications by voice. Though SRT and more advanced speech recognition techniques show promise, use of this technology for a space application such as vehicle/habitat/spacesuit requires careful considerations. There are still recognition challenges to overcome such as background noise, human speech variability, and task loading. However, implemented correctly, a voice-controlled spacecraft system (VCSS) can provide a useful, natural and efficient form of human-machine communications during complex tasks such as when the hands and eyes are busy or as an aid for vehicle situational awareness inquiries or collaborative human-robot tasks. This document provides considerations and guidance for the use of SRT in VCSS applications for space missions, specifically in command-and-control (C2) applications where the commanding is user-initiated. First, current SRT limitations as known at the time of this report are given. Then, highlights of SRT used in the space program provide the reader with a history of some of the human spaceflight applications and research. Next, an overview of the speech production process and the intrinsic variations of speech are provided. Finally, general guidance and considerations are given for development of a VCSS using a human-centered design approach for space applications that includes vocabulary selection and performance testing, as well as VCSS considerations for C2 dialogue management design, feedback, error handling, and evaluation/usability testing. Available from

Salazar, George A.↗

Defining Collaborative Control Interactions Using Systems Theory

Human teams collaborate by establishing roles, changing functional authorities, maintaining team cognition, coordinating, and mutually helping one another close control loops. These complex inter-actions are inspiring novel concepts to improve human-machine and multi-machine collaboration. However, these new systems face engineering gaps in modeling, analysis, design, and assurance. As such, few have been fielded in safety-critical domains like aerospace. To analyze safety, this paper introduces a system-theoretic framework to describe interactions that are—or are planned to be—used in multi-controller systems. It outlines a taxonomy of seven structural dimensions that influence controller interactions and nine dynamics observed in collaborative control that are defined using Systems Theory. An analyzed set of 101 controller interactions in aerospace systems demonstrates how to apply the framework and that designers are trying to create more sophisticated systems. This framework provides the foundation to extend system-theoretic hazard analysis techniques to systematically find collabora-tive-control causal factors.

Human machine teaming↗

What to Do Until the Money Runs Out: A Refinement Framework for Cognitive Engineering in the Real World

A case study is presented to illustrate some of the problems of applying cognitive science to complex human-machine systems. Disregard for facts about human cognition often undermines the safety, reliability, and cost-effectiveness of complex systems. Yet single-point methods (for example, better user-interface design), whether rooted in computer science or in experimental psychology, fall far short of addressing systems-level problems in a timely way using realistic resources. A model-based methodology is proposed for organizing and prioritizing the cognitive engineering effort, focusing appropriate expertise on major problems first, then moving to more sophisticated refinements if time and resources permit. This case study is based on a collaborative effort between the Human Factors Division at NASA-Ames and the Spaceborne Imaging Radar SIR-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) Project at the Jet Propulsion Laboratory (JPL), California institute of Technology. The first SIR-C/X-SAR Shuttle mission flew successfully in April, 1994. A series of such missions is planned to provide radar data to study Earth's ecosystems, climatic and geological processes, hydrologic cycle, and ocean circulation. In addition to JPL and NASA personnel, the SIR-C/X-SAR operations team included Scientists and engineers from the German and Italian space agencies.

Shafto, Michael G.↗

Helicopter Human Factors

Even under optimal conditions, helicopter flight is a most demanding form of human-machine interaction, imposing continuous manual, visual, communications, and mental demands on pilots. It is made even more challenging by small margins for error created by the close proximity of terrain in NOE flight and missions flown at night and in low visibility. Although technology advances have satisfied some current and proposed requirements, hardware solutions alone are not sufficient to ensure acceptable system performance and pilot workload. However, human factors data needed to improve the design and use of helicopters lag behind advances in sensor, display, and control technology. Thus, it is difficult for designers to consider human capabilities and limitations when making design decisions. This results in costly accidents, design mistakes, unrealistic mission requirements, excessive training costs, and challenge human adaptability. NASA, in collaboration with DOD, industry, and academia, has initiated a program of research to develop scientific data bases and design principles to improve the pilot/vehicle interface, optimize training time and cost, and maintain pilot workload and system performance at an acceptable level. Work performed at Ames, and by other research laboratories, will be reviewed to summarize the most critical helicopter human factors problems and the results of research that has been performed to: (1) Quantify/model pilots use of visual cues for vehicle control; (2) Improve pilots' performance with helmet displays of thermal imagery and night vision goggles for situation awareness and vehicle control; (3) Model the processes by which pilots encode maps and compare them to the visual scene to develop perceptually and cognitively compatible electronic map formats; (4) Evaluate the use of spatially localized auditory displays for geographical orientation, target localization, radio frequency separation; (5) Develop and flight test control/display concepts; (6) Quantify, model, predict, and improve pilots, workload-management strategies; and (7) Design computer-game trainers to reduce training time and cost.

Hart, Sandra G.↗

Aviation Simulators for the Desktop: Panel and Demonstrations

Panel Members are: Christine M. Mitchell (Georgia Tech), Michael T. Palmer (NASA Langley), Greg Pisani (NASA Ames), and Amy R. Pritchett (MIT). The Panel members are affiliated with aviation human factors groups from NASA Ames, NASA Langley, MITCHELL Department of Aerospace and Aeronautical Engineering, and Georgia Technics Center for Human-Machine Systems Research. Panelists will describe the simulator(s) used in their respective institutions including a description of the FMS aircraft models, software, hardware, and displays. Panelists will summarize previous, on-going, and planned empirical studies conducted with the simulators. Greg Pisanich will describe two NASA Ames simulation systems: the Stone Soup Simulator (SSS), and the Airspace Operations Human Factors Simulation Laboratory. The the Stone Soup Simulator is a desktop-based, research flight simulator that includes mode control, flight management, and datalink functionality. It has been developed as a non-proprietary simulator that can be easily distributed to academic and industry researchers who are collaborating on NASA research projects. It will be used and extended by research groups represented by at least two panelists (Mitchell and Palmer). The Airspace Operations Simulator supports the study of air traffic control in conjunction with the flight deck. This simulator will be used provide an environment in which many AATT and free flight concepts can be demonstrated and evaluated. Mike Palmer will describe two NASA Langley efforts: The Langley Simulator and MD-11 extensions to the NASA Amesbury simulator. The first simulator is publicly available and combines a B-737 model with a high fidelity flight management system. The second simulator enhances the S3 simulator with MD-11 electronic flight displays together with modifications to the flight and FMS models to emulate MD-11 dynamics and operations. Chris Mitchell will describe GT-EFIRT (Georgia Tech-Electronic Flight Instrument Research Tool) and B-757 enhancements to the NASA Ames S3. GT-EFIRT is a medium fidelity simulator used to conduct preliminary studies of the CATS (crew activity tracking system). Like the Langley efforts with S3, the Georgia Tech enhancements will allow it to emulate the dynamics and operations of a widely used glass cockpit. Amy Pritchett will describe the MIT simulator(s) that have been used in a range of research investigating cockpit displays, warning devices, and flight deck-ATC interaction.

Pisanich, Greg↗

The Naturalistic Flight Deck System: An Integrated System Concept for Improved Single-Pilot Operations

This paper reviews current and emerging operational experiences, technologies, and human-machine interaction theories to develop an integrated flight system concept designed to increase the safety, reliability, and performance of single-pilot operations in an increasingly accommodating but stringent national airspace system. This concept, know as the Naturalistic Flight Deck (NFD), uses a form of human-centered automation known as complementary-automation (or complemation) to structure the relationship between the human operator and the aircraft as independent, collaborative agents having complimentary capabilities. The human provides commonsense knowledge, general intelligence, and creative thinking, while the machine contributes specialized intelligence and control, extreme vigilance, resistance to fatigue, and encyclopedic memory. To support the development of the NFD, an initial Concept of Operations has been created and selected normal and non-normal scenarios are presented in this document.

Schutte, Paul C.↗