Mission Influences on Advanced Computers
Computer application to aerospace missions, discussing operation and equipment parameters, reliability, man-machine interaction, etc
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Computer application to aerospace missions, discussing operation and equipment parameters, reliability, man-machine interaction, etc
An algorithm employing a modified sequential random perturbation, or creeping random search, was applied to the problem of optimizing the parameters of a high-energy beam transport system. The stochastic solution of the mathematical model for first-order magnetic-field expansion allows the inclusion of state-variable constraints, and the inclusion of parameter constraints allowed by the method of algorithm application eliminates the possibility of infeasible solutions. The mathematical model and the algorithm were programmed for a real-time simulation facility; thus, two important features are provided to the beam designer: (1) a strong degree of man-machine communication (even to the extent of bypassing the algorithm and applying analog-matching techniques), and (2) extensive graphics for displaying information concerning both algorithm operation and transport-system behavior. Chromatic aberration was also included in the mathematical model and in the optimization process. Results presented show this method as yielding better solutions (in terms of resolutions) to the particular problem than those of a standard analog program as well as demonstrating flexibility, in terms of elements, constraints, and chromatic aberration, allowed by user interaction with both the algorithm and the stochastic model. Example of slit usage and a limited comparison of predicted results and actual results obtained with a 600 MeV cyclotron are given.
It has been demonstrated that classical probabilities, and in particular, probabilistic Turing machine, can be simulated by combining chaos and non-Lipschitz dynamics, without utilization of any man-made devices(such as random number generators). Self-orgainizing properties of systems coupling simulated and calculated probabilities and their link to quantum computations are discussed. Special attention was focused upon coupled stochastic processes, defined in terms of conditional probabilities, for which joint probability does not exist. Simulations of quantum probabilities are also discussed.
The influence and utilization of computers in space science investigations greatly enhances the ability to address difficult and complicated questions about the Universe. Space Science is wholly dependent on computers because the data acquired from instruments on the spacecraft are not only complicated in form but also voluminous. Athough a great deal of attention has been paid to develop efficient and powerful computing systems on-ground, research in the area of spaceborne computing is far from satisfactory. On-board processing of data will be important in future planetary missions where telemetry rates constrain the total amount of data which can be returned and decisions may have to be made in real time. Little thought has been given to a dynamic man-machine interface with regard to scientific real-time interactive control of flight experiments. Careful thinking is therefore essential to define appropriate spaceborne computing requirements for the future. It is imperative that powerful multiprocessing systems for on-board processing be experimentally impleneted and evaluated in selected application missions. The presentation addresses key issues and attempts to define the requirements for such processing with some of NASA's future missions in perspective. The resulting architectural and performance issues and possible developments are also addressed.
Sophisticated man machine interaction often requires the human operator to perform a stereotyped scan of various instruments in order to monitor and/or control a system. For situations in which this type of stereotyped behavior exists, such as certain phases of instrument flight, scan pattern was shown to be altered by the imposition of simultaneous verbal tasks. A study designed to examine the relationship between pilot visual scan of instruments and mental workload is described. It was found that a verbal loading task of varying difficulty causes pilots to stare at the primary instrument as the difficulty increases and to shed looks at instruments of less importance. The verbal loading task also affected the rank ordering of scanning sequences. By examining the behavior of pilots with widely varying skill levels, it was suggested that these effects occur most strongly at lower skill levels and are less apparent at high skill levels. A graphical interpretation of the hypothetical relationship between skill, workload, and performance is introduced and modelling results are presented to support this interpretation.
This report contains information on the activities of the Artificial Intelligence Research Branch (FIA) at NASA Ames Research Center (ARC) in 1992, as well as planned work in 1993. These activities span a range from basic scientific research through engineering development to fielded NASA applications, particularly those applications that are enabled by basic research carried out in FIA. Work is conducted in-house and through collaborative partners in academia and industry. All of our work has research themes with a dual commitment to technical excellence and applicability to NASA short, medium, and long-term problems. FIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at the Jet Propulsion Laboratory (JPL) and AI applications groups throughout all NASA centers. This report is organized along three major research themes: (1) Planning and Scheduling: deciding on a sequence of actions to achieve a set of complex goals and determining when to execute those actions and how to allocate resources to carry them out; (2) Machine Learning: techniques for forming theories about natural and man-made phenomena; and for improving the problem-solving performance of computational systems over time; and (3) Research on the acquisition, representation, and utilization of knowledge in support of diagnosis design of engineered systems and analysis of actual systems.
A human factors evaluation of the MH-53J helicopter cockpit is described. This evaluation was an application and futher development of Tools for Automated Knowledge Engineering (TAKE). TAKE is used to acquire and analyze knowledge from domain experts (aircrew members, system designers, maintenance personnel, human factors engineers, or others). TAKE was successfully utilized for the purpose of recommending improvements for the man-machine interfaces (MMI) in the MH-53J cockpit.
The training performed for flights of the Space Shuttle is intensive and extremely complicated. The training is totally dependent on computer generated training situations in both cockpit simulations and in integrated simulations between the simulators and the Mission Control Center (MCC). These simulations form a complex set of dress rehearsals of the actual spaceflight allowing the participants to address problems in a real world situation and utilize problem solving rationale just as they will be called upon to do during the real flight. The benefits of this type of training have been demonstrated during the flights of the Shuttle as individual flight controllers and whole teams have been tested by various untoward situations. This system of integrated simulation and training, more complex than ever, will be continued in use in the future using even more intricate man-machine interactions required to initialize, control, and operate it.
Fire protection of critical space assets, including launch and fueling facilities and manned flight hardware, demands automatic sensors for continuous monitoring, and in certain high-threat areas, fast-reacting automatic suppression systems. Perhaps the most essential characteristic for these fire detection and suppression systems is high reliability; in other words, fire detectors should alarm only on actual fires and not be falsely activated by extraneous sources. Existing types of fire detectors have been greatly improved in the past decade; however, fundamental limitations of their method of operation leaves open a significant possibility of false alarms and restricts their usefulness. At the Civil Engineering Laboratory at Tyndall Air Force Base in Florida, a new type of fire detector is under development which 'sees' a fire visually, like a human being, and makes a reliable decision based on known visual characteristics of flames. Hardware prototypes of the Machine Vision (MV) Fire Detection System have undergone live fire tests and demonstrated extremely high accuracy in discriminating actual fires from false alarm sources. In fact, this technology promises to virtually eliminate false activations. This detector could be used to monitor fueling facilities, launch towers, clean rooms, and other high-value and high-risk areas. Applications can extend to space station and in-flight shuttle operations as well; fiber optics and remote camera heads enable the system to see around obstructed areas and crew compartments. The capability of the technology to distinguish fires means that fire detection can be provided even during maintenance operations, such as welding.
In this paper, the prime objective is to describe a custom 4-dof (degree-of-freedom) robotic arm capable of autonomously or telerobotically performing systematic HEPA filter inspection and certification in the Shuttle Launch Pad Payload Changeout Rooms (PCR's) on pads A and B at the Kennedy Space Center, Florida. This HEPA filter inspection robot (HFIR) has been designed to be easily deployable and is equipped with the necessary sensory devices, control hardware, software and man-machine interfaces needed to implement HEPA filter inspection reliably and efficiently without damaging the filters or colliding with existing PCR structures or filters. The main purpose of the HFIR is to implement an automated positioning system to move special inspection sensors in pre-defined or manual patterns for the purpose of verifying filter integrity and efficiency. This will ultimately relieve NASA Payload Operations from significant problems associated with time, cost and personnel safety, impacts realized during non-automated PCR HFIR filter certification.
Assembly robots combine the benefits of speed and accuracy with the capability of adaptation to changes in the work environment. However, an impediment to the use of robots is the complexity of the man-machine interface. This interface can be improved by providing a means of using a priori-knowledge and reasoning capabilities for controlling and monitoring the tasks performed by robots. Robots ought to be able to perform complex assembly tasks with the help of only supervisory guidance from human operators. For such supervisory quidance, it is important to express the commands in terms of the effects desired, rather than in terms of the motion the robot must undertake in order to achieve these effects. A suitable knowledge representation can facilitate the conversion of task level descriptions into explicit instructions to the robot. Such a system would use symbolic relationships describing the a priori information about the robot, its environment, and the tasks specified by the operator to generate the commands for the robot.
The challenge of the concept of a reusable, cargo carrying space vehicle, and how those challenges were met for the Space Shuttle are discussed. The complexity of the vehicle, the ground support systen, the onboard computer system, ramifications of a reusable vehicle, and the turn around objectives for Shuttle flights are outlined. The Apollo and the space transportation system (STS) are compared.
Potential applications for autonomous space platforms (SP) are discussed. The platforms are assumed to have long in-service lifetimes and therefore be flexible as to configuration modification and payload changeout. Higher degrees of autonomy, particularly from ground control, are made possible because of the rapid increase of microprocessor power and artificial intelligence advances. Functioning independently, the platforms are to rely only on periodic refurbishment visits by, e.g., the Orbiter. The Manned Space Station (MSS) will be the most complex structure, involving multifacted man-machine interfaces. The SP can be subsystems of the MSS (or other platforms), handling communications enunciation, data acquisition, analysis and telemetry, fault detection and isolation, systems monitoring and control, etc. The SP adopted will depend in all cases on costs vs benefits analyses to determine the worth of removing the function(s) from direct, regular human intervention.
Numerous factors impact on the efficiency of tele-operative manipulative work. Generally, these are related to the physical environment of the tele-operator and how he interfaces with robotic control consoles. The capabilities of the operator can be influenced by considerations such as temperature, eye strain, body fatigue, and boredom created by repetitive work tasks. In addition, the successful combination of man and machine will, in part, be determined by the configuration of the visual and physical interfaces available to the teleoperator. The design and operation of system components such as full-scale and mini-master manipulator controllers, servo joysticks, and video monitors will have a direct impact on operational efficiency. As a result, the local environment and the interaction of the operator with the robotic control console have a substantial effect on mission productivity.
Since 1974, CNES has been involved in geostationary positioning. Among different entities participating in operations and their preparation, the Flight Dynamics Center (FDC) is in charge of performing the following tasks: orbit determination; attitude determination; computation, monitoring, and calibration of orbit maneuvers; computation, monitoring, and calibration of attitude maneuvers; and operational predictions. In order to fulfill this mission, the FDC receives telemetry from the satellite and localization measurements from ground stations (e.g., CNES, NASA, INTELSAT). These data are processed by space dynamics programs integrated in the MERCATOR system which is run on SUN workstations (UNIX O.S.). The main features of MERCATOR are redundancy, modularity, and flexibility: efficient, flexible, and user friendly man-machine interface; and four identical SUN stations redundantly linked in an Ethernet network. Each workstation can perform all the tasks from data acquisition to computation results dissemination through a video network. A team of four engineers can handle the space mechanics aspects of a complete geostationary positioning from the injection into a transfer orbit to the final maneuvers in the station-keeping window. MERCATOR has been or is to be used for operations related to more than ten geostationary positionings. Initially developed for geostationary satellites, MERCATOR's methodology was also used for satellite control centers and can be applied to a wide range of satellites and to future manned missions.
NASA's Johnson Space Center in Houston, Texas, is active in several aspects of hybrid image processing. (The term hybrid image processing refers to a system that combines digital and photonic processing). The major thrusts are autonomous space operations such as planetary landing, servicing, and rendezvous and docking. By processing images in non-Cartesian geometries to achieve shift invariance to canonical distortions, researchers use certain aspects of the human visual system for machine vision. That technology flow is bidirectional; researchers are investigating the possible utility of video-rate coordinate transformations for human low-vision patients. Man-in-the-loop teleoperations are also supported by the use of video-rate image-coordinate transformations, as researchers plan to use bandwidth compression tailored to the varying spatial acuity of the human operator. Technological elements being developed in the program include upgraded spatial light modulators, real-time coordinate transformations in video imagery, synthetic filters that robustly allow estimation of object pose parameters, convolutionally blurred filters that have continuously selectable invariance to such image changes as magnification and rotation, and optimization of optical correlation done with spatial light modulators that have limited range and couple both phase and amplitude in their response.
A design concept for the construction of a permanent manned space station is developed and discussed. The main considerations examined in developing the design concept are: (1) the support structure of the station be stiff enough to preclude the need for an elaborate on-orbit system to control structural response, (2) the station support structure and solar power system be compatible with existing technology, and (3) the station be capable of growing in a systematic modular fashion. The concept is developed around the assembly of truss platforms by pressure-suited astronauts operating in extravehicular activity (EVA), assisted by a machine (Assembly and Transport Vehicle, ATV) to position the astronauts at joint locations where they latch truss members in place. The ATV is a mobile platform that is attached to and moves on the station support structure using pegs attached to each truss joint. The operation of the ATV is described and a number of conceptual configurations for potential space stations are developed.
Design and development of a prosthetic device fitted to an above elbow amputee is reported that derives control information from the human to modulate power to an actuator to drive the substitute limb. In turn, the artificial limb generates sensory information feedback to the human nervous system and brain. This synergetic unity feeds efferent or motor control information from the human to the machine, and the machine responds, delivering afferent or sensory information back to the man.