Search NASA⌕ Search

SEARCH · Search NASA

Results for “human system interface”

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.

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

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Trusted Communication: Utilizing Speech Communication to Enhance Human-Machine Teaming Success

An area of increasing interest for the next generation of aircraft is autonomy and the integration of increasingly autonomous systems into the national airspace. Such an integration requires humans to work closely with autonomous systems, forming teams. Our hypothesis is that a team composed of both humans and autonomous systems will operate better than either entity alone. We have existing procedures for certifying pilots to operate in the national airspace and are currently working on methods for validating the function of autonomous systems, however we have no method in place for assessing the interaction of these two disparate systems. Communication is one avenue. This paper will examine the use of language as a metric for ascertaining human-machine teaming effectiveness. A proof-of-concept of the application of two communication-based analysis techniques, Linguistic Inquiry and Word Count (LIWC) and Latent Semantic Analysis (LSA), for the prediction of success in human/chatbot teaming was conducted. By running these analyses over data from the 2014 and 2015 Loebner Prize competitions of human/chatbot teaming, numerical scores were obtained that can be associated with scores provided by human judges during the competition. Correlating their LIWC and LSA data with the scores provided by the judges, and using linear regression over this correlation, formulae were obtained that predict the score of human/chatbot interaction. These formulae were tested over the 2013 Loebner Prize transcripts, determining that, though there was strong correlation between predicted and actual scores, the predictive success of this method was not strong. However, with specialized topic spaces and lexica, as well as larger data sets, the predictive power of these metrics will improve. Given the importance of providing metrics for human-machine system team success and given the promise shown by the communication-basedLIWCand LSAmethods, continuing research in this area is necessary. After examining the potential for using communication and spoken language as a metric for the success of human/autonomous system teaming, this paper then examines aspects inherent to communication systems that may contribute to unreliability and reduced trust. Modern natural language processing tools rely on deep learning algorithms to create language rules that produce accurate results, but these rules are uninterpretable. The resulting blackbox system lacks transparency necessary for full validation and complete trust. Additionally, speech-based interfaces pose other difficulties to developing coordinated teamwork between humans and autonomous systems. Human communication is infrequently limited to speech only, instead usually relying on a combination of verbal, gestural, and general body language communication. Reducing an analysis of team effectiveness to a study of spoken language alone is problematic as it leaves these other equally important forms of communication out. This paper will examine these problems and the general deficiencies in speech-based metrics for human-machine teaming.

E L Meszaros↗
NASA NTRS1987

Cooperative human-machine fault diagnosis

Current expert system technology does not permit complete automatic fault diagnosis; significant levels of human intervention are still required. This requirement dictates a need for a division of labor that recognizes the strengths and weaknesses of both human and machine diagnostic skills. Relevant findings from the literature on human cognition are combined with the results of reviews of aircrew performance with highly automated systems to suggest how the interface of a fault diagnostic expert system can be designed to assist human operators in verifying machine diagnoses and guiding interactive fault diagnosis. It is argued that the needs of the human operator should play an important role in the design of the knowledge base.

Remington, Roger↗
NASA NTRS1975

Clinical application of a light-pen computer system for quantitative angiography

The important features in a clinical system for quantitative angiography were examined. The human interface for data input, whether an electrostatic pen, sonic pen, or light-pen must be engineered to optimize the quality of margin definition. The computer programs which the technician uses for data entry and computation of ventriculographic measurements must be convenient to use on a routine basis in a laboratory performing multiple studies per day. The method used for magnification correction must be continuously monitored.

Alderman, E. L.↗
NASA NTRS2011

Evidence Report, Risk of Inadequate Design of Human and Automation/Robotic Integration

The success of future exploration missions depends, even more than today, on effective integration of humans and technology (automation and robotics). This will not emerge by chance, but by design. Both crew and ground personnel will need to do more demanding tasks in more difficult conditions, amplifying the costs of poor design and the benefits of good design. This report has looked at the importance of good design and the risks from poor design from several perspectives: 1) If the relevant functions needed for a mission are not identified, then designs of technology and its use by humans are unlikely to be effective: critical functions will be missing and irrelevant functions will mislead or drain attention. 2) If functions are not distributed effectively among the (multiple) participating humans and automation/robotic systems, later design choices can do little to repair this: additional unnecessary coordination work may be introduced, workload may be redistributed to create problems, limited human attentional resources may be wasted, and the capabilities of both humans and technology underused. 3) If the design does not promote accurate understanding of the capabilities of the technology, the operators will not use the technology effectively: the system may be switched off in conditions where it would be effective, or used for tasks or in contexts where its effectiveness may be very limited. 4) If an ineffective interaction design is implemented and put into use, a wide range of problems can ensue. Many involve lack of transparency into the system: operators may be unable or find it very difficult to determine a) the current state and changes of state of the automation or robot, b) the current state and changes in state of the system being controlled or acted on, and c) what actions by human or by system had what effects. 5) If the human interfaces for operation and control of robotic agents are not designed to accommodate the unique points of view and operating environments of both the human and the robotic agent, then effective human-robot coordination cannot be achieved.

Zumbado, Jennifer Rochlis↗
NASA NTRS2017

What Machines Need to Learn to Support Human Problem-Solving

In the development of intelligent systems that interact with humans, there is often confusion between how the system functions with respect to the humans it interacts with and how it interfaces with those humans. The former is a much deeper challenge than the latter it requires a system-level understanding of evolving human roles as well as an understanding of what humans need to know (and when) in order to perform their tasks. This talk will focus on some of the challenges in getting this right as well as on the type of research and development that results in successful human-autonomy teaming. Brief Bio: Dr. Alonso Vera is Chief of the Human Systems Integration Division at NASA Ames Research Center. His expertise is in human-computer interaction, information systems, artificial intelligence, and computational human performance modeling. He has led the design, development and deployment of mission software systems across NASA robotic and human space flight missions, including Mars Exploration Rovers, Phoenix Mars Lander, ISS, Constellation, and Exploration Systems. Dr. Vera received a Bachelor of Science with First Class Honors from McGill University in 1985 and a Ph.D. from Cornell University in 1991. He went on to a Post-Doctoral Fellowship in the School of Computer Science at Carnegie Mellon University from 1990-93.

intelligent systems↗
DOE OSTI2015

Metis Hub: The Development of an Intuitive Project Planning System

The goal is to develop an intuitive, dynamic, and consistent interface for the Metis Planning System by combining user requirements and human engineering concepts. The system is largely based upon existing systems so some tools already have working models that we can follow. However, the web-based interface is completely new.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Software systems for modeling articulated figures

Research in computer animation and simulation of human task performance requires sophisticated geometric modeling and user interface tools. The software for a research environment should present the programmer with a powerful but flexible substrate of facilities for displaying and manipulating geometric objects, yet insure that future tools have a consistent and friendly user interface. Jack is a system which provides a flexible and extensible programmer and user interface for displaying and manipulating complex geometric figures, particularly human figures in a 3D working environment. It is a basic software framework for high-performance Silicon Graphics IRIS workstations for modeling and manipulating geometric objects in a general but powerful way. It provides a consistent and user-friendly interface across various applications in computer animation and simulation of human task performance. Currently, Jack provides input and control for applications including lighting specification and image rendering, anthropometric modeling, figure positioning, inverse kinematics, dynamic simulation, and keyframe animation.

Phillips, Cary B.↗
NASA NTRS2009

Human-rating Automated and Robotic Systems - (How HAL Can Work Safely with Astronauts)

Long duration human space missions, as planned in the Vision for Space Exploration, will not be possible without applying unprecedented levels of automation to support the human endeavors. The automated and robotic systems must carry the load of routine housekeeping for the new generation of explorers, as well as assist their exploration science and engineering work with new precision. Fortunately, the state of automated and robotic systems is sophisticated and sturdy enough to do this work - but the systems themselves have never been human-rated as all other NASA physical systems used in human space flight have. Our intent in this paper is to provide perspective on requirements and architecture for the interfaces and interactions between human beings and the astonishing array of automated systems; and the approach we believe necessary to create human-rated systems and implement them in the space program. We will explain our proposed standard structure for automation and robotic systems, and the process by which we will develop and implement that standard as an addition to NASA s Human Rating requirements. Our work here is based on real experience with both human system and robotic system designs; for surface operations as well as for in-flight monitoring and control; and on the necessities we have discovered for human-systems integration in NASA's Constellation program. We hope this will be an invitation to dialog and to consideration of a new issue facing new generations of explorers and their outfitters.

Baroff, Lynn↗
NASA NTRS1993

Integration of advanced teleoperation technologies for control of space robots

Teleoperated robots require one or more humans to control actuators, mechanisms, and other robot equipment given feedback from onboard sensors. To accomplish this task, the human or humans require some form of control station. Desirable features of such a control station include operation by a single human, comfort, and natural human interfaces (visual, audio, motion, tactile, etc.). These interfaces should work to maximize performance of the human/robot system by streamlining the link between human brain and robot equipment. This paper describes development of a control station testbed with the characteristics described above. Initially, this testbed will be used to control two teleoperated robots. Features of the robots include anthropomorphic mechanisms, slaving to the testbed, and delivery of sensory feedback to the testbed. The testbed will make use of technologies such as helmet mounted displays, voice recognition, and exoskeleton masters. It will allow tor integration and testing of emerging telepresence technologies along with techniques for coping with control link time delays. Systems developed from this testbed could be applied to ground control of space based robots. During man-tended operations, the Space Station Freedom may benefit from ground control of IVA or EVA robots with science or maintenance tasks. Planetary exploration may also find advanced teleoperation systems to be very useful.

Stagnaro, Michael J.↗
NASA NTRS1990

NASA systems autonomy demonstration project: Advanced automation demonstration of Space Station Freedom thermal control system

The NASA Systems Autonomy Demonstration Project (SADP) was initiated in response to Congressional interest in Space station automation technology demonstration. The SADP is a joint cooperative effort between Ames Research Center (ARC) and Johnson Space Center (JSC) to demonstrate advanced automation technology feasibility using the Space Station Freedom Thermal Control System (TCS) test bed. A model-based expert system and its operator interface were developed by knowledge engineers, AI researchers, and human factors researchers at ARC working with the domain experts and system integration engineers at JSC. Its target application is a prototype heat acquisition and transport subsystem of a space station TCS. The demonstration is scheduled to be conducted at JSC in August, 1989. The demonstration will consist of a detailed test of the ability of the Thermal Expert System to conduct real time normal operations (start-up, set point changes, shut-down) and to conduct fault detection, isolation, and recovery (FDIR) on the test article. The FDIR will be conducted by injecting ten component level failures that will manifest themselves as seven different system level faults. Here, the SADP goals, are described as well as the Thermal Control Expert System that has been developed for demonstration.

Dominick, Jeffrey↗
NASA NTRS1991

Guideline requirements for serviceable spacecraft grasping/berthing/docking interfaces based on simulations and flight experience (survey paper)

As space vehicles and structures become larger and more complex, the development of systems to assist humans in assembling, operating, maintaining, and performing space rescue or retrieval of these vehicles and structures becomes increasingly important. With the diversity of international spacecraft, both manned and unmanned, planned to be in orbit in the future, a set of guidelines for berthing and docking subsystems is mandatory if servicing, resupply, and retrieval is to become practical on an international level. Successful interaction between these space systems and ground and/or space-based humans requires standardized and effective operational interface designs, particularly with respect to space grasping/berthing/docking interface mechanisms. This paper defines the spacecraft mechanical interfaces necessary to create a standard dynamic envelope for joining two free-flying spacecraft in a 'hard' berth or dock with each other in space. A review was made of past space flights and dynamics simulations dating back to 1962 to obtain necessary parameters and their values for successful manually controlled and autonomous spacecraft docking/berthing. The various spacecraft docking/berthing mechanisms and concepts are illustrated along with their dynamic capture and impact tolerances including maximum contact velocity along the approach axis and in the y-z plane; capture linear misalignment tolerances; and maximum capture roll, pitch, and yaw angles. From this data sets of recommended guidelines parameters were developed for autonomous and manual impact docking tolerances, non-impact grasping/berthing tolerances (end effectors), berthing contact conditions, and alignment tolerances after rigidizing. Also, detailed requirements were developed for mechanical design interface features, as well as latching, unlatching, and separation tolerances. This data was drafted in the form of a proposed ANSI Standard guideline, reviewed, and added to by members of the committee representing several spacecraft manufacturers, NASA, and the USAF, and a consensus was reached.

Thompson, Allen B.↗
NASA NTRS2013

Modeling Complex Cross-Systems Software Interfaces Using SysML

The complex flight and ground systems for NASA human space exploration are designed, built, operated and managed as separate programs and projects. However, each system relies on one or more of the other systems in order to accomplish specific mission objectives, creating a complex, tightly coupled architecture. Thus, there is a fundamental need to understand how each system interacts with the other. To determine if a model-based system engineering approach could be utilized to assist with understanding the complex system interactions, the NASA Engineering and Safety Center (NESC) sponsored a task to develop an approach for performing cross-system behavior modeling. This paper presents the results of applying Model Based Systems Engineering (MBSE) principles using the System Modeling Language (SysML) to define cross-system behaviors and how they map to crosssystem software interfaces documented in system-level Interface Control Documents (ICDs).

Earth orbit↗
NASA NTRS2007

Robotics

Lunar robotic functions include: 1. Transport of crew and payloads on the surface of the moon; 2. Offloading payloads from a lunar lander; 3. Handling the deployment of surface systems; with 4. Human commanding of these functions from inside a lunar vehicle, habitat, or extravehicular (space walk), with Earth-based supervision. The systems that will perform these functions may not look like robots from science fiction. In fact, robotic functions may be automated trucks, cranes and winches. Use of this equipment prior to the crew s arrival or in the potentially long periods without crews on the surface, will require that these systems be computer controlled machines. The public release of NASA's Exploration plans at the 2nd Space Exploration Conference (Houston, December 2006) included a lunar outpost with as many as four unique mobility chassis designs. The sequence of lander offloading tasks involved as many as ten payloads, each with a unique set of geometry, mass and interface requirements. This plan was refined during a second phase study concluded in August 2007. Among the many improvements to the exploration plan were a reduction in the number of unique mobility chassis designs and a reduction in unique payload specifications. As the lunar surface system payloads have matured, so have the mobility and offloading functional requirements. While the architecture work continues, the community can expect to see functional requirements in the areas of surface mobility, surface handling, and human-systems interaction as follows: Surface Mobility 1. Transport crew on the lunar surface, accelerating construction tasks, expanding the crew s sphere of influence for scientific exploration, and providing a rapid return to an ascent module in an emergency. The crew transport can be with an un-pressurized rover, a small pressurized rover, or a larger mobile habitat. 2. Transport Extra-Vehicular Activity (EVA) equipment and construction payloads. 3. Transport habitats and power modules over long distances, pre-positioning them for the arrival of crew on a subsequent lander. Surface Handling 1. Offload surface system payloads from the lander, breaking launch restraints and power/data connections. Payloads may be offloaded to a wheeled vehicle for transport. 2. Deploy payloads from a wheeled vehicle at a field site, placing the payloads in their final use site on the ground or mating them with existing surface systems. 3. Support regolith collection, site preparation, berm construction, or other civil engineering tasks using tools and implements attached to rovers. Human-Systems Interaction 1. Provide a safe command and control interface for suited EVA to ride on and drive the vehicles, making sure that the systems are also safe for working near dismounted crew. 2. Provide an effective control system for IV crew to tele-operate vehicles, cranes and other equipment from inside the surface habitats with evolving independence from Earth. .. Provide a supervisory system that allows machines to be commanded from the ground, working across the Earth-Lunar time delays on the order of 5-10 seconds (round trip) to support operations when crew are not resident on the surface. Technology Development Needs 1. Surface vehicles that can dock, align and mate with outpost equipment such as landers, habitats and fluid/power interfaces. 2. Long life motors, drive trains, seals, motor electronics, sensors, processors, cable harnesses, and dash board displays. 3. Active suspension control, localization, high speed obstacle avoidance, and safety systems for operating near dismounted crew. 4. High specific energy and specific power batteries that are safe, rechargeable, and long lived.

Ambrose, Robert O.↗
NASA NTRS1999

Human Engineering Operations and Habitability Assessment: A Process for Advanced Life Support Ground Facility Testbeds

Design and Human Engineering (HE) processes strive to ensure that the human-machine interface is designed for optimal performance throughout the system life cycle. Each component can be tested and assessed independently to assure optimal performance, but it is not until full integration that the system and the inherent interactions between the system components can be assessed as a whole. HE processes (which are defining/app lying requirements for human interaction with missions/systems) are included in space flight activities, but also need to be included in ground activities and specifically, ground facility testbeds such as Bio-Plex. A unique aspect of the Bio-Plex Facility is the integral issue of Habitability which includes qualities of the environment that allow humans to work and live. HE is a process by which Habitability and system performance can be assessed.

Connolly, Janis H.↗
NASA NTRS2003

Enhancing the Human Factors Engineering Role in an Austere Fiscal Environment

An austere fiscal environment in the aerospace community creates pressures to reduce program costs, often minimizing or sometimes even deleting the human interface requirements from the design process. With an assumption that the flight crew can recover real time from a poorly human factored space vehicle design, the classical crew interface requirements have been either not included in the design or not properly funded, though carried as requirements. Cost cuts have also affected quality of retained human factors engineering personnel. In response to this concern, planning is ongoing to correct the acting issues. Herein are techniques for ensuring that human interface requirements are integrated into a flight design, from proposal through verification and launch activation. This includes human factors requirements refinement and consolidation across flight programs; keyword phrases in the proposals; closer ties with systems engineering and other classical disciplines; early planning for crew-interface verification; and an Agency integrated human factors verification program, under the One NASA theme. Importance is given to communication within the aerospace human factors discipline, and utilizing the strengths of all government, industry, and academic human factors organizations in an unified research and engineering approach. A list of recommendations and concerns are provided in closing.

Stokes, Jack W.↗
NASA NTRS1979

Considerations for design of future research and development interactive image analysis systems

Future interactive image analysis systems must provide for the increased processing requirements imposed by a thermal channel to LANDSAT-3 and the increased number of spectral channels with significantly higher spatial resolution provided by the LANDSAT-D thematic mapper. Other design considerations must include the rapidly changing technology in memories and special purpose processors, as well as the analyst-machine interface and the human factors involved. The centralized and distributed system approaches are examined in relation to the optimum design configuration of future systems.

Wilkinson, T. B.↗
NASA NTRS1990

Man-systems integration and the man-machine interface

Viewgraphs on man-systems integration and the man-machine interface are presented. Man-systems integration applies the systems' approach to the integration of the user and the machine to form an effective, symbiotic Man-Machine System (MMS). A MMS is a combination of one or more human beings and one or more physical components that are integrated through the common purpose of achieving some objective. The human operator interacts with the system through the Man-Machine Interface (MMI).

Hale, Joseph P.↗
NASA NTRSDate not supplied

Development of a Human Systems Integration Plan

NASA defines Human Systems Integration (HSI) as part of the overall systems engineering and acquisition strategy for space systems. The HSI Plan defines how HSI activities will be implemented across the lifecycle of the mission, as required by NPR 7123.1C, NASA Systems Engineering Processes and Requirements, and NPR 8705.2C Human-Rating Requirements for Space Systems. The goal of this presentation is to share with government and industry how an HSI Plan can be implemented. The presentation will cover HSI implementation for flight systems, vehicle processing, and interfaces. These are divided into six NASA HSI Domains: human factors engineering, operations resources, safety, training, maintainability and supportability, habitability and environment. HSI activities go across the mission’s lifecycle from pre-formulation and acquisition through design, development, operations, maintenance, and decommissioning. The HSI Plan includes a description of the HSI activities and products that are essential for human rating, operability, maintainability, supportability, and affordability of the mission systems. It also describes the role of the HSI Team required as part of the Human Rating process. The HSI Plan utilizes the operational expertise within NASA to ensure designs and testing are successful, leading to acceptable human spaceflight vehicles.

Jackelynne Silva-Martinez↗