Intelligent Long Endurance Observing System (ILEOS)
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high altitude long endurance↗
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Space robot simulator vehicle
A Space Robot Simulator Vehicle (SRSV) was constructed to model a free-flying robot capable of doing construction, manipulation and repair work in space. The SRSV is intended as a test bed for development of dynamic and static control methods for space robots. The vehicle is built around a two-foot-diameter air-cushion vehicle that carries batteries, power supplies, gas tanks, computer, reaction jets and radio equipment. It is fitted with one or two two-link manipulators, which may be of many possible designs, including flexible-link versions. Both the vehicle body and its first arm are nearly complete. Inverse dynamic control of the robot's manipulator has been successfully simulated using equations generated by the dynamic simulation package SDEXACT. In this mode, the position of the manipulator tip is controlled not by fixing the vehicle base through thruster operation, but by controlling the manipulator joint torques to achieve the desired tip motion, while allowing for the free motion of the vehicle base. One of the primary goals is to minimize use of the thrusters in favor of intelligent control of the manipulator. Ways to reduce the computational burden of control are described.
Cannon, R. H., Jr.↗
The role of robotics in space system operations
The role of automation and robotics in support of man's activities in space is discussed, with emphasis given to satellite servicing functions on board the NASA Space Station (SS) or at remote locations. Consideration is given to four satellite servicing mission scenarios, including: low-earth-orbit (LEO) servicing of satellite in situ or on the Space Station following orbital transfer by means of an Orbital Maneuvering Vehicle (OMV); in situ servicing of a free-flying coorbiting materials processing platform; repair/refurbishment of Space Station payloads of substations; an in situ servicing of geostationary satellites by means of an Orbital Transfer Vehicle (OTV). The potential applications of three different automation technologies are examined, including: teleoperation; robotics; and artificial intelligence. Consideration is also given to the potential applications of the Space Station data system in support of servicing activities. A list of the more common terms of automation technology is provided.
Meissinger, H. F.↗
Intelligent control and adaptive systems; Proceedings of the Meeting, Philadelphia, PA, Nov. 7, 8, 1989
Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.
Rodriguez, Guillermo↗
Expert knowledge techniques applied to the analysis of electric field mill data
NASA operates a network of ground-based electric field mills at Kennedy Space Center (KSC) to identify clouds which might be an electrical hazard to space vehicle prior to and during launch or to the various ground operations performed at the center. Artificial intelligence has been used to develop an expert system for analyzing electric field mill data. The application of the system to expert system to small thunderstorms at KSC is shown.
Nicholson, James R.↗
The smart highway project: Smart highways, smart vehicles, smart engineering
The Smart Highway project is a six mile, limited access roadway being built between Interstate 81 and Blacksburg, Virginia. The initial construction segment will be two miles long and is designed to serve as a test bed and test track for Intelligent Transportation Systems (ITS) research. The Center for Transportation Research (CTR) at Virginia Tech is developing three evaluation tools for its ITS research including DYNAVIMTS (a software framework), and the FLASH Lab (a 1/15th scale model highway and vehicle system). The Smart Highway rounds out the Center's evaluation methodology by allowing full scale operational tests, evaluations, and research under both experimental and conventional traffic conditions. Currently under development is a concept for a fully automated highway using a 'Cooperative Infrastructure Managed System' which involves ultra wide band communication beacons installed in the infrastructure with appropriate sensors, receivers and processors on board the vehicles. The project is part of the research program funded by the National Automated Highway System Consortium. The CTR hopes to develop the automated concept to prototype status by 1997. Other smart transportation and smart engineering concepts are proposed. This presentation will address the goals and objectives of the Smart Highway project, overview its status and importance to the region, and identify some of the transportation technology now under development and planned in the future.
Pethtel, Ray D.↗
Trusted Autonomy for Space Flight Systems
NASA has long supported research on intelligent control technologies that could allow space systems to operate autonomously or with reduced human supervision. Proposed uses range from automated control of entire space vehicles to mobile robots that assist or substitute for astronauts to vehicle systems such as life support that interact with other systems in complex ways and require constant vigilance. The potential for pervasive use of such technology to extend the kinds of missions that are possible in practice is well understood, as is its potential to radically improve the robustness, safety and productivity of diverse mission systems. Despite its acknowledged potential, intelligent control capabilities are rarely used in space flight systems. Perhaps the most famous example of intelligent control on a spacecraft is the Remote Agent system flown on the Deep Space One mission (1998 - 2001). However, even in this case, the role of the intelligent control element, originally intended to have full control of the spacecraft for the duration of the mission, was reduced to having partial control for a two-week non-critical period. Even this level of mission acceptance was exceptional. In most cases, mission managers consider intelligent control systems an unacceptable source of risk and elect not to fly them. Overall, the technology is not trusted. From the standpoint of those who need to decide whether to incorporate this technology, lack of trust is easy to understand. Intelligent high-level control means allowing software io make decisions that are too complex for conventional software. The decision-making behavior of these systems is often hard to understand and inspect, and thus hard to evaluate. Moreover, such software is typically designed and implemented either as a research product or custom-built for a particular mission. In the former case, software quality is unlikely to be adequate for flight qualification and the functionality provided by the system is likely driven largely by the need to publish innovative work. In the latter case, the mission represents the first use of the system, a risky proposition even for relatively simple software.
Freed, Michael↗
Effects of simplifying assumptions on optimal trajectory estimation for a high-performance aircraft
When analyzing the performance of an aircraft, certain simplifying assumptions, which decrease the complexity of the problem, can often be made. The degree of accuracy required in the solution may determine the extent to which these simplifying assumptions are incorporated. A complex model may yield more accurate results if it describes the real situation more thoroughly. However, a complex model usually involves more computation time, makes the analysis more difficult, and often requires more information to do the analysis. Therefore, to choose the simplifying assumptions intelligently, it is important to know what effects the assumptions may have on the calculated performance of a vehicle. Several simplifying assumptions are examined, the effects of simplified models to those of the more complex ones are compared, and conclusions are drawn about the impact of these assumptions on flight envelope generation and optimal trajectory calculation. Models which affect an aircraft are analyzed, but the implications of simplifying the model of the aircraft itself are not studied. The examples are atmospheric models, gravitational models, different models for equations of motion, and constraint conditions.
Kern, Lura E.↗
Assessing the impact of modeling limits on intelligent systems
The knowledge bases underlying intelligent systems are validated. A general conceptual framework is provided for considering the roles in intelligent systems of models of physical, behavioral, and operational phenomena. A methodology is described for identifying limits in particular intelligent systems, and the use of the methodology is illustrated via an experimental evaluation of the pilot-vehicle interface within the Pilot's Associate. The requirements and functionality are outlined for a computer based knowledge engineering environment which would embody the approach advocated and illustrated in earlier discussions. Issues considered include the specific benefits of this functionality, the potential breadth of applicability, and technical feasibility.
Rouse, William B.↗
Assessing the impact of modeling limits on intelligent systems
The knowledge bases underlying intelligent systems are validated. A general conceptual framework is provided for considering the roles in intelligent systems of models of physical, behavioral, and operational phenomena. A methodology is described for identifing limits in particular intelligent systems, and the use of the methodology is illustrated via an experimental evaluation of the pilot-vehicle interface within the Pilot's Associate. The requirements and functionality are outlined for a computer based knowledge engineering environment which would embody the approach advocated and illustrated in earlier discussions. Issues considered include the specific benefits of this functionality, the potential breadth of applicability, and technical feasibility.
Rouse, William B.↗
Structures and Materials Experimental Facilities and Capabilities Catalog
The NASA Center of Excellent for Structures and Materials at Langley Research Center is responsible for conducting research and developing useable technology in the areas of advanced materials and processing technologies, durability, damage tolerance, structural concepts, advanced sensors, intelligent systems, aircraft ground operations, reliability, prediction tools, performance validation, aeroelastic response, and structural dynamics behavior for aerospace vehicles. Supporting the research activities is a complementary set of facilities and capabilities documented in this report. Because of the volume of information, the information collected was restricted in most cases to one page. Specific questions from potential customers or partners should be directed to the points of contacts provided with the various capabilities. Grouping of the equipment is by location as opposed to function. Geographical information of the various buildings housing the equipment is also provided. Since this is the first time that such an inventory is ever collected at Langley it is by no means complete. It is estimated that over 90 percent of the equipment capabilities at hand are included but equipment is continuously being updated and will be reported in the future.
Horta, Lucas G.↗
Situation Awareness of Onboard System Autonomy
We have developed intelligent agent software for onboard system autonomy. Our approach is to provide control agents that automate crew and vehicle systems, and operations assistants that aid humans in working with these autonomous systems. We use the 3 Tier control architecture to develop the control agent software that automates system reconfiguration and routine fault management. We use the Distributed Collaboration and Interaction (DCI) System to develop the operations assistants that provide human services, including situation summarization, event notification, activity management, and support for manual commanding of autonomous system. In this paper we describe how the operations assistants aid situation awareness of the autonomous control agents. We also describe our evaluation of the DCI System to support control engineers during a ground test at Johnson Space Center (JSC) of the Post Processing System (PPS) for regenerative water recovery.
Schreckenghost, Debra↗
NASA Dryden Status
This viewgraph document reviews the status of several Dryden projects. They are: the Ikhana Project, development of the F-15 Intelligent Flight Control System, the development of a C-20A Precision Autopilot for use in Unmanned Aerial Vehicle Synthetic Aperture Radar (UAVSAR), the development of the X-48B Blended Wing Body aircraft, and development of Stratospheric Observatory for Infrared Astronomy (SOFIA).
Cox, Timothy H.↗
Automation of vehicle processing at Space Station Freedom
A methodology for applying the Kennedy Space Center vehicle processing experience to similar operations at Space Station Freedom is described. First, the required on-orbit processing tasks are identified. These tasks are then evaluated for automation suitability, and robotic manipulator and artificial intelligence technologies are investigated to automate selected physical and cognitive tasks. Effects on processing times, extra-vehicular activity savings, and required resources for incorporating these automation enhancements are identified. Results of the following case studies are included: Phobos Gateway Vehicle On-Orbit Assembly and Launch, Lunar Evolution Vehicle On-Orbit Refurbishment, and Mars Mission Vehicle On-Orbit Assembly and Launch.
Vargo, Rick↗
Remotely manned systems: Exploration and operation in space; Proceedings of the First National Conference, California Institute of Technology, Pasadena, Calif., September 13-15, 1972.
Free-flying teleoperator systems are discussed, giving attention to earth-orbit mission considerations and Space Tug requirements, free-flying teleoperator requirements and conceptual design, system requirements for a free-flying teleoperator to despin, and the experimental evaluation of remote manipulator systems. Shuttle-Attached Manipulator Systems are considered, together with remote surface vehicle systems, manipulator systems technology, remote sensor and display technology, the man-machine interface, and control and machine intelligence. Nonspace applications are also explored, taking into account implications of nonspace applications, naval applications of remote manipulators, and hand tools and mechanical accessories for a deep submersible. Individual items are announced in this issue.
Heer, E.↗
Automated rendezvous and docking with video imagery
For rendezvous and docking, assessing and tracking relative orientation is necessary within a minimum approach distance. Special target light patterns have previously been considered for use with video sensors for ease of determining relative orientation. A generalization of those approaches is addressed. At certain ranges, the entire structure of the target vehicle constitutes an acceptable target; at closer ranges, substructures will suffice. Acting on the same principle as the human intelligence, these structures can be compared with a memory model to assess the relative orientation and range. Models for comparison are constructed from a CAD facet model and current imagery. This approach requires fast image handling, projection, and comparison techniques which rely on rapidly developing parallel processing technology. Relative orientation and range assessment consists of successful comparison of the perceived target aspect with a known aspect. Generating a known projection from a model within required times, say subsecond times, is only now approaching feasibility. With this capability, rates of comparison used by the human brain can be approached and arbitrary known structures can be compared in reasonable times. Future space programs will have access to powerful computation devices which far exceed even this capability. For example, the possibility will exist to assess unknown structures and then control rendezvous and docking, all at very fast rates. The first step which has the current utility, namely applying this to known structures, is taken.
Rodgers, Mike↗
Gyro-based Maximum-Likelihood Thruster Fault Detection and Identification
When building smaller, less expensive spacecraft, there is a need for intelligent fault tolerance vs. increased hardware redundancy. If fault tolerance can be achieved using existing navigation sensors, cost and vehicle complexity can be reduced. A maximum likelihood-based approach to thruster fault detection and identification (FDI) for spacecraft is developed here and applied in simulation to the X-38 space vehicle. The system uses only gyro signals to detect and identify hard, abrupt, single and multiple jet on- and off-failures. Faults are detected within one second and identified within one to five accords,
Wilson, Edward↗
NASA's Vision for 21st Century Aircraft
This paper presents NASA's Vision for the 21st Century Aircraft. The contents include: 1) NASA Vision; 2) NASA Installations; 3) Research and Technology Products; 4) Future Plans; 5) Revolutionary Vehicles; 6) Aeropropulsion-NASA's Future Direction; 7) Gas Turbine Revolution; 8) Variable Capability, Ultra High Bypass Ratio Intelligent Engines: Fundamental Technologies; 9) Distributed Vectored Propulsion; and 10) Alternative Energy Propulsion. This paper is in viewgraph form.
Whitlow, Woodrow, Jr.↗