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Cost-effective implementation of intelligent systems
Acta Astronautica Voi.24, pp. 23-31, 1991 P r i n t e d in G r e a t B r i t a i n
0094-5765/91 $3.00 + 0.00 Pergamon
Press plc
COST-EFFECTIVE IMPLEMENTATION OF INTELLIGENT SYSTEMS Henry Lure Jr Chief, Information Sciences Division NASA-Ames Research Center Moffett Field, CA 94035 Ewald Heer Heer Associates, Inc. La Canada, CA 91011 Abstract
Significant advances have occurred during the last decade in knowledge-based engineering research and knowledge-based system (KBS) demonstrations and evaluations using integrated intelligent system technologies. Performance and simulation data obtained to date in real-time operational environments suggest that cost-effective utilization of intelligent system technologies can be realized. In this paper the rationale and potential benefits for typical examples of application projects that demonstrate an increase in productivity through the use of intelligent system technologies are discussed. These demonstration projects have provided an insight into additional technology needs and cultural barriers which are currently impeding the transition of the technology into operational environments. Proposed methods which address technology evolution and implementation are also discussed. Introduction
As Space Station Freedom (SSF) moves from planning to hardware development and implementation, the National Aeronautics and Space Administration (NASA) has initiated the planning process for additional large space projects over the next few years (Fig. 1). The primary goals of this program are to return to the Moon and establish an outpost and to advance human exploration of Mars during the early 2000 time period. These projects involve complex infrastructures of transportation, habitability, and communication systems and place the highest demands on systems reliability and performance.
Fig. 1. America's Future in Space The potential and importance of automation and robotic technologies in space operations were recognized and supported by NASA since the early space flight ventures. During the last decade, automation and robotics have received progressively more attention with emphasis being placed on research in artificial intelligence which will lead to significant advances in the development of intelligent systems.
To ensure the success of these undertakings, the automation and robotics (A&R) technologies must reach a certain state of maturity to allow the assembly and construction of large-scale systems in space and the performance of tasks involving monitoring and maintenance over long operational periods. The resources that must be invoked to accomplish these tasks include astronauts' intravehicular activity (IVA) and extravehicular activity (EVA), remote ground operations and control, built-in system fault management, and telerobetics. WA and EVA are performed by astronauts whose time is most valuable and primarily needed for scientific projects. Thus, NASA's goals are to enhance and complement human functions with intelligent automation and robotics, e.g., tasks that can typically be clone automatically or by robots.
Today's state-of-the-art in intelligent systems technology is the result of many years of research, development, and evaluation toward application readiness. 1-4 The generic nature of the advanced automation research and development program sponsored by NASA's Office of Aeronautics, Exploration, and Technology (OAET) and Office of Space Flight (OSF) makes the results applicable in a broad spectrum of contexts, some of which will be discussed in this paper. In most of these cases, "conventional" technologies are integrated with artificial intelligence techniques leading to intelligent systems that can perform, to an appreciable degree, functions generally attributed to intelligent,
Copyright © 1990 by the American Institute of Aeronautics and Astronautics, Inc. No copyright is asserted in the United States under Title 17, U.S. Code. The U.S. Government has a royalty-free license to exercise all rights under the copyright claimed herein for Governmental purposes. All other rights are reserved by the owner.
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reasonable humans. Nevertheless, it should be remembered that these intelligent systems are only able to function under the direction and guidance of humans and cannot solve all problems autonomously. They tend to function as augmentations of human mental capabilities. Considerable advances have occurred in knowledge-based engineering research, knowledgebased systems (KBS) demonstrations, and evaluations using integrated intelligent systems technologies. Performance and simulation data obtained to date in real-time operational environments suggest that costeffective uses of intelligent systems can be made if the applications are focused in five areas to be introduced in the following section. The rationale and projected benefits for these specific application areas and typical examples of application projects that demonstrate the increase in productivity which are obtained through the use of KBS technologies are described. Finally, the incorporation of intelligent system technologies into robotic systems to provide significantly increased performance capabilities with the human operating at a high level of human-machine interaction is presented.
Avvlication Areas and Proiects In reviewing the planning documentation on the Space Station and later human exploration missions to the Moon and Mars, a broad spectrum of system functions that may be performed or may benefit from the incorporation and application of intelligent systems is identified. 5"6 Possible applications range from relatively simple knowledge-based expert systems assisting astronauts in quick decision making to complex autonomous robots performing complex diagnostics and repair tasks. In the following, a representative set of functional areas in which intelligent systems will play a particularly strong role is briefly discussed. Space and Aeronautical Operations Aircraft and spacecraft once had a much higher human-to-machine functional ratio than can be tolerated in today's complex missions and systems. Now there is an ever increasing need for automation to reduce the human's interaction in the control loop of operating systems, to improve critical decision-making capabilities of humans and machines, and to reduce the training time for humans still in the control loop but functioning at a higher level of supervision. These requirements for automated operations technology and, in particular for intelligent systems, are addressed within the context of application projects which include the development of: Principal Investigator in a Box (PI-in-a-Box): a knowledge-based system that provides, expert advice to crew members to allow them to conduct better "reactive" science. 7 Aircraft Descent Advisors: computer-decision aids which support air traffic controllers and
provide for the possibility to increase traffic volume in terminal areas. Planning Aids for Proximity Operations: knowledge-based systems based on human factors, control theory, and operational experience. On-orbit Fluid Transfer Systems: software systems which allow a ground-based experimenter to conduct research experiments while, at the same time, allowing the Space Shuttle crew to monitor and control the transfer of cryogenic superfluid helium in space. On-Board Monitoring, Diagnosis, and Control The performance of in-flight systems is subject to many unpredicted changes requiring close and timeconsuming attention by flight crew members. Automation here provides real-time capabilities which augment and complement human performance levels and enhance mission safety by the early discovery of incipient failures. Testing and qualifying intelligent system technologies relevant to on-board monitoring, diagnosis, and control are accomplished in application projects related to the demonstration of: Space Station Freedom Thermal Control System (TEXSYS): an advanced automation project for the development and validation of a rule- and model-based system to perform real-time control and fault detection, isolation, and recovery of a complex physical system, s Planetary Rovers: the development and validation of intelligent systems for on-board rover applications. Aids for Rotorcraft: the determination of quantitative measures and requirements for evaluations of pilots' information including the testing and validating of aids for computer vision and guidance in rotorcraft flight. Preservation and Utilization of Program Life-Cycle Knowledge At every stage of program and system development, factual data and information are created that are applicable to later system operations and maintenance and which are inputs to the development of knowledgebases for relevant expert systems. This requires that data and information are captured in a methodical way throughout the design, construction, test, and operation phases. Generally, the data and information must be integrated from many disparate sources and will provide focused problem-solving capabilities through the development of knowledge bases for intelligent systems. Specific application projects are currently addressing the problems of life-cycle knowledge capture and are contributing to the development of :
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Electronic Designer's Notebook: the development of software for automatically capturing formal and informal heuristic design knowledge such as the SIRTF Tertiary Mirror Assembly. 7 Corporate Memory Facility: the development and application of knowledge-based technologies for the management of the corporate memory. Management and Analysis of Science and Engineering Data The major reason for space missions is to collect scientific and engineering data and learn more about the world surrounding us. Current data acquisition capabilities are enormous and rapidly multiplying. It is, therefore, necessary to significantly increase the capabilities for analyzing large science databases on Earth and for improving the effective use of communication channel bandwidth capacity. In addition, it is often highly effective to conduct data analyses in-situ on lunar and planetary surfaces, and thus, avoid overloading the communication channels. Some of the means for management and analysis of science and engineering data from space are obtained through the development of: AutoClass: based on Bayesian classification techniques and applied, together with advanced reasoning technology, to the classification of large data sets. 9 Virtual Environment Workstation (VIEWS): full information display of integrated time-varying data in a virtual environment format. Automation of DTA/GC: the development of sof~vare for fault diagnosis and correction and in-situ analysis. Operations of Autonomous Robotic Systems The Space Station Program is currently developing a robotic system based on three primary elements. These include the Shuttle-based Remote Manipulator System (RMS), the Mobile Remote Manipulator System (MRMS), and the Flight Telerobotic Servicer (FTS), which will be used while mounted on appropriate mobility bases to perform assembly assistance, inspections, servicing, and maintenance functions. As now envisioned, these systems will be operated in the telerobotic mode, where the operator is located in a control station on the Space Shuttle, the Space Station, or an EVA station on the MRMS. Sensory feedback to the operator is accomplished by direct vision or video display. All three systems are programmable so that their end effectors move automatically to a specified location within acceptable accuracies. In addition, the FTS will include a hierarchical control architecture, which will provide the basis for adapting autonomous capabilities, i.e., intelligent systems technologies, at a later stage. It is
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expected that such capabilities will contribute considerably to cost-effective operations in space. From an intelligent system point of view, technically most demanding applications of robotic systems are science missions involving Mars sample return vehicles with local rovers and long-range Mars surface rovers: ° These unmanned missions perform the necessary scientific investigations to qualify planetary sites for subsequent human outpost construction. The Earthbased operation center and the remote robotic devices communicate with each other through a radio link. However, since the communication time delay between Earth and Mars varies between about 8 to 40 minutes, time and cost-effective operations require that the remote equipment on the planetary surface have substantial onboard intelligent system capabilities for autonomous navigation, site identification, sample acquisition and analysis, and other operations. In addition, there must be intelligent system capabilities to perform autonomous diagnoses of operations, fault isolation, and recovery from faulty behavior. The Lunar Outpost architectures include landing and launch site facilities, crew habitation facilities, in-situ resource mining, power production facilities, and the like. Similarly, the Martian Outpost architecture includes landing and launch facilities, habitation facilities, photovoltaic power systems, etc. The construction and operation of these facilities and the associated infrastructure call for an entire array of robotic equipment such as roving vehicles with manipulators, front loaders, cranes, and other machinery which require manipulative dexterity. The control of these systems is usually done from on-site control stations by telerobotic means of operation as indicated above for the Space Station Initial Operation Configuration (IOC). However, during the initial setup phase of the outposts when humans are not yet present, substantial autonomous machine capabilities, provided by intelligent systems, may be required to overcome, at least partially, the constraints of communication time delay. There are two major categories of intelligent system applications in future NASA space missions. The first category deals with expert and knowledge-based systems in support of system management functions including planning, scheduling, monitoring, control, diagnosis, fault isolation, and recovery. These functions are performed in support of human decision makers who employ the intelligent systems in a supporting role. In the second category, the telerobotic control mode of robotic devices is extended by intelligent systems to an autonomous control mode in which the humans act as supervisors of the robotic devices, and their level of communication with the intelligent machines is correspondingly high. In addition to the functions performed by the first category, the robotic devices are now also able to interact with the environment by virtue of sensory information feedback. This information, together with the resident knowledge-base and the planning, monitoring, simulation, and diagnostic
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systems, provides the means for autonomous behavior and operation. Cost-Effective I m o l e m e n t a t i o n
The applications of intelligent systems in the Space Station and later human exploration missions are motivated by potential benefits resulting from reduced total life-cycle cost, increased operational reliability, and technology transfer to industry. A system is considered cost effective if, over the operational life time, the present value of all benefits is equal or greater than the present value of all costs. It is expected that the application of intelligent systems in the space program will be cost effective because their application in business and industry generally bears this out. Although Earth-based technology developments and demonstrations point to the potential cost effectiveness of intelligent systems in future space missions, to date little applicable experience and information is available regarding actual space operations. Generally, the benefits of intelligent system applications are: fewer humans involved in complex operation processes; better and more consistent performance of recurring functions; enabled and more reliable system performance in dangerous environments; and, intelligent operations in areas not accessible by humans. For the formulation of quantitative productivity projections, the available data are usually incomplete and not comprehensive enough. The following estimations are, therefore, notably qualitative, arrived at primarily by heuristic processes.
Nevertheless, the simpler case to evaluate is ground support because there is comparative experimental data from NASA/Johnson Space Center's Mission Control Center applications. For example, the Integration Communications Officer Expert Systems Project11 has shown that at least 25% savings can be achieved in ground-based system monitoring operations with intelligent systems. With some technical improvements under development, this can probably be increased to 50%. Although, no comparative data are as yet available for planning and scheduling based on current developments, it is estimated that similar cost savings will be realized for ground mission operations, checkout, and training. Taking into account qualitative comparisons between conventional and knowledgebased thermal control systems for the Space Shuttle (Fig. 2), the operations with intelligent systems are expected to improve the cost effectiveness by up to 30% for operations from the ground. Using intelligent software for simulation and training usually shortens training time and contributes to savings of roughly 20% to 30% compared with current techniques.
Intelligent Management Systems Potential cost savings resulting from the application of intelligent systems will most likely be due to the possible reduction of manpower in system operations. In-space costs for every astronaut are estimated at $40,000 per EVA hour and $15,000 per IVA hour, which include support costs and other overhead costs. In comparison, the costs for ground mission support are about $40 to $60 per work hour, which also include support costs and overhead. Whatever the cumulative work hour savings, because of intelligent system applications, they must be traded against the costs of developing, installing, and operating the intelligent system itself. To realize any savings requires that the time value of the total operation and maintenance costs, the integration and implementation of the intelligent systems, and the time value of the related capital expenditures be less than the time value of the operation and maintenance costs using current techniques and procedures. The capital expenditures are usually up to an order of magnitude higher for space-qualified software systems than for equivalent systems applied in ground operations. Because of the large difference in hourly costs, it may be tentatively concluded from these considerations that reducing astronaut time by substituting intelligent systems, where possible, will be more cost effective than reducing human work hours on the ground.
ICO.PAR,SO. I TCS TEXSYS CONVENTIONAL CONTROL SYSTEM I KNOWLEDGE BASED SYSTEM I NOMINAL OPERATIONS
•
Displays data for real-time monitor and control by a human Prod/Idesautomated control routines for system parameter changes by e human
Displays and ANALYZES data for real-time operations AUTOMATICALLY controls nominal and off-nominal processes
FAULT DETECTION, iSOLATION, AND RECOVERY
•
Displays data of system health and status Alerts humansof detrimental system performance
•
Displays and ANALYZES data of system health and status • ACTS upon detrimental system status to recover and EXPLAINS actions to recover
Fig. 2. Performance Capabilities of Automated Thermal Control System vs. a "Conventional" System
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However, the greatest cost savings are expected from the systematic preservation and utilization of program life-cycle knowledge which will provide solutions for upcoming problems in a cost-effective manner without time-intensive translation of design information from design and mission operations documents a n d / o r lengthy consultation with experts. Current estimates are based on the Electronic Designer's Notebook. Although indications of possible future cost savings are very spotty, the ubiquitous applicability of program life-cycle knowledge in space system operations results in a conclusion that operational savings will be many times that of the development costs of the related intelligent systems. There is also a great potential to save costs in the analysis of science and engineering data by employing intelligent systems such as AutoClass. Many of these data, which come back to the ground-based operations center, often receive only cursory inspection or are not analyzed at all because of the large volume, the fading newsworthiness, and the high expense for analysis by humans. A review of the "lessons learned" from Skylab, Spacelab, and other Space Shuttle experiences gained through interviews with current and former astronauts and mission operations personnel as well as a review of the data from the Soviet Salyut and Mir space station operations, the U. S. nuclear submarine fleet, and the Antarctic research station indicates that there is strong support from the astronaut community for the use of advanced automation and robotics in a broad range of areas. 12 The application of intelligent systems allows astronauts to devote more time to the broader mission objectives while relegating the routine aspects of recordkeeping, planning, scheduling, monitoring, control, fault detection, fault isolation, and fault recovery to intelligent systems. The most cost-effective overation in svace takes place when the astronauts can devote a minimum of their time to the routine tasks and a maximum of their time to the ~cience and technoloe-¢ obiectives of the mission. Depending on the capital investment for the intelligent systems, the savings can be substantial as compared with operations by astronauts only. Estimated cost savings will be at least an order of magnitude greater for in-space operations than for ground operations if the reduction of work hours and astronaut hours due to intelligent systems are the same. Astronauts using PI-in-a-Box approaches may be as effective as an equivalent principal investigator (PI) on site, particularly if there is the possibility of intermittent communication with the PI on the ground. The cost effectiveness of such intelligent systems can only be estimated but is probably in the 90% range. Tables 1 and 2 indicate the potential cost savings from the use of advanced automation for ground-based mission operations and on-board operations, respectively. v
.
Table 1. Potential Cost Savings from Ground Support Advanced Automation 12
Activity
Potential Savings (% reduction in task time)
Operations Planningand Integration TrajectoryDesign and Dynamics Space StationControl Center Space StationTraining Facility Payload Planning Payload Operations Support
25-50 10-25 25-50 10-25 10-25 25-50
Table 2. Potential Savings from On-board Automation 12 Activity
Percent Savings (% reduction in task time)
ActivityPlanning System Monitoringand Control FlightControl FlightPlanning Training Inventory Management Internal Maintenanceand Servicing External Maintenanceand Servicing ProximateOperations Payload Operations Reboost
5-10 5-10 10-20 5-25 10-25 10-25 5-10 2.5-5 5-10 5-10 5-10
Autonomous Robotic Systems In this functional area, an assumption is made that telerobotic technology is available and that intelligent systems are added in order to provide autonomous capabilities to robotic devices and, thus, increase the cost effectiveness of intelligent in-space operations. However, the experience base of telerobotic operations in space is limited and primarily restricted to the Space Shuttlebased RMS. Estimates of the cost effectiveness of intelligent systems added to telerobotic devices are necessarily tenuous projections into the future and only indicative of their potential. To project potential cost-effectiveness increases through the use of intelligent systems, a situation is assumed where over a certain time interval all operations are done by EVA. A teleoperated FTS with the IVA performed by an on-board astronaut is then substituted. The FTS system will then be executing a fraction of the total previous EVA operations. Significant cost savings can be achieved when all-EVA activities are transitioned to the FTS and EVA mixed modes of operations. 13 An additional step can now be taken with the addition of intelligent systems, i.e., autonomous capabilities to the FTS, thus, reducing corresponding EVA and WA and further increasing the astronaut's productivity and system cost effectiveness as shown in Figure 3. Similar statements can also be made about the addition of autonomous capabilities to the RMS and MRMS.
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The only physical difference between these two modes of operation is that the second has incorporated the intelligent systems which provide the autonomous capabilities for the FTS to perform 80% of EVA maintenance work. Compared with the first mode of operation, this requires an initial, additional capital investment representing the cost of the intelligent systems. Neglecting minor additional costs and benefits and assuming the above-stated EVA and IVA hourly costs, the first approximation of the cost differences of the two modes of operation can be calculated. An estimated annual cost for the first approach, teleoperated mode of operation, results in $40 million and for the second, autonomous mode of operation, about $12.6 million plus the initial capital investment for the intelligent systems.
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Fig. 3. Astronaut Estimates of Productivity Impact of A&R Applications 12
Estimates show that of all the exterior maintenance tasks on the Space Station, approximately 90% must be devoted to inspection and 10% to the alleviation of trouble spots and other maintenance work. 14 Inspection tasks generally are done routinely and to a large degree repetitively. They are, therefore, prime candidates to be performed by the FTS in an autonomous mode of operation. To realize the full potential of the FTS, it should be equipped with intelligent systems which enable it to have unrestricted mobility about the Space Station exterior, accumulate inspection data, perform diagnostic inferences, and alert the astronaut crew for further decisions and actions, if required. Because of their general uniqueness, it is expected that most of the alleviating actions must still be done by EVA or by telerobotic operation of the FTS while a remaining few will be possible by autonomous FTS operations. Also, some routine inspections by the FTS will still be checked by EVA for increased reliability and safety. Recent estimates by W. F. Fisher and C. R. Price show that the total EVA maintenance time for the Space Station after IOC is 2284 hours per y e a r : s Of this time, about 90% is required for inspection and about 10% for fault alleviation and correction work. Based on the statements above, two modes of operation are considered for comparison and cost-effectiveness evaluation: first, 10% of the 2284 hours of total EVA work, or 228 hours, will actually be done by EVA, while the rest of the maintenance work, equivalent to 2056 hours of EVA, will be done by the teleoperated FTS; and, second, 10% of the 2284 hours of total EVA work, or 228 hours, will actually be clone by EVA, the equivalent of 10% of the total EVA work will be done by the teleoperated FTS, and the equivalent of 80% of the total EVA work will be done by the autonomous FTS.
Using the above costs, the present value at IOC of the annual savings of $27.7M ($40.3M - $12.6M) for a selected number of years of Space Shuttle operations using a uniform discount rate of 8%, is shown in Table 1. These dollar amounts, if invested at IOC for the required intelligent systems, will be paid back after the indicated number of years. For example, a reasonable estimate for the intelligent system cost is $70M at IOC, which amounts to 25% of the estimated cost of $280M for the teleoperated FTS. This will be paid back through savings after three years. For a total operational lifetime of 30 years for the Space Station, the value of all savings at IOC will then be $238.5M ($308.5M - $70.0M).
T a b l e 3. D i s c o u n t e d
Years of Operation after IOC
1 2 3 4 5 10 20 30
Future S a v i n g s Systems
Present Worth Factor, 8% D.R.
0.926 1.783 2.577 3.312 3.993 6.710 9.818 11.258
for I n t e l l i g e n t
Discounted Savings for $27,7M Ann'l. Rate
$ $ $ $ $ $ $ $
25.4M 48.9M 70.6M 90.7M 109.4M 183.9M 269.0M 308.5M
Technical progress is being made in the real-time control of intelligent robotic systems (Fig. 4). Current emphasis is being placed in the critical areas necessary for autonomous operations of intelligent robotic systems: end point control of flexible-link manipulators; objectbased control of dual cooperating manipulators; and object-based control of two cooperating mobile robots. The FTS is the application focus for the research effort currently being conducted at Stanford University's Autonomous Robotics Systems Laboratory. The evaluation of the cost effectiveness of intelligent for robotic devices on the Lunar Surface and Mars follows similar lines as shown above if astronauts are on site and the comparison can be made between EVA, teleoperation, and autonomous operations. A systems
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major aspect in such evaluations is to what degree the robotic functions to be performed are repetitive and can be standardized. Future designs must take these aspects into account to ensure the cost effectiveness of intelligent systems.
Similar arguments are valid for science missions to Mars involving robotic devices. Because of the communication delay, a Martian roving vehicle teleoperated from Earth may be able to operate, on the average, only about 5% of the time. With on-board intelligent systems it may increase its average useful operating time up to 80%, presumably, increasing the volume of science information by at least an order of magnitude. Considering the relative cost of the intelligent systems compared with the total mission cost, it can be concluded that the initial capital investment for the addition of intelligent systems is highly cost effective. Technology Challenges and Cultural Barriers
Fig. 4. Real-Time Control Capabilities for an Advanced FTS During the initial setup phase of the Lunar and Mars Outposts, the functions to be performed are essentially unique tasks with little repetitiveness and standardization. Correspondingly, intelligent systems will be incorporated where required to provide enablement of the operation rather than for economic reasons. The technology elements for a projected integrated space habitat infrastructure are being developed and will be evaluated in various testbeds to assess their overall cost effectiveness as depicted in Figure 5. If such unique operations can be accomplished, for example, by teleoperation from the Earth-based control center, the initial capital investment for more advanced technologies like intelligent systems will most likely not be made.
As indicated at the beginning of this paper, a broad spectrum of intelligent system technologies is under development within certain application contexts to ensure timely availability for future space applications. Nevertheless, there are technical areas which pose development barriers and require long-range research and development planning. Some of the important areas of technology challenges and their relative degrees of complexity are identified in Figure 6.
ITechnology ChallengesI .
Real T i m e Performance -
C o m p u t a t i o n a l S y s t e m S o f t w a r e Infrastructure Fault M a n a g e m e n t and Control
Systems Integration ( " C o n v e n t i o n a l " M o d e l s with AI-Based Models) •
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Fig. 6. Technology Challenges and Level of Complexity for Advanced Automation
Fig. 5. Evolution of Testbeds for a Space Habitat Infrastructure
In addition to developing the required technologies, the appropriate managerial environment to facilitate the acceptance and implementation of intelligent systems for practical applications in space systems must be in place.
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The realization that intelligent systems are in many application contexts either enabling the mission objectives or are highly cost effective, or both, is usually not enough to ensure that the necessary investments for their incorporation in space missions will be made. To foster a receptive environment and remove corresponding barriers require high-level and long-range managerial decisions. Figure 7 identifies recommended "cultural" changes for the implementation and incorporation of intelligent systems in space missions.
i for I i Implementation of Advanced Automation I
We also wish to acknowledge the many technical contributions made by our fellow colleagues in the automation sciences community, especially Mr. Gregg Swietek and Mr. David Weeks, which have been incorporated in this paper. References Heer, E., and H. Lure. Machine Intelligence and Autonomy for Aerospace Systems, American Institute of Aeronautics and Astronautics Progress in Astronautics and Aeronautics Series, Vol. 115, 1988.
Recommended"Cultural" Changes
•
• . • •
Integrate/Manage/Use all Agency Resources to Accomplish Project and Mission Goals and Objectives Implement Effective Team Collaboration between Centers Implement a Distributed Unified Information System for Project Management and Control L e v e r a g e / U s e Commercial/Industry,'DoD Standards and T e c h n o l o g i e s whenever Possible Accept/Use Advanced Automation and Expert Systems in Operational Environment Design and Manage for Evolutionary Growth and Technology Upgrades Incorporate System Fault Management from Design through Operations Use Life Cycle Design Costs for Determination of Return-on-Investment (ROI)
Fig. 7. Recommended "Cultural" Changes for Implementation of Advanced Automation
2.
3.
Lure, H., and E. Heer (1988)• Technology Forecast and Applications for Autonomous, Intelligent Systems. Acta Astronautica, Vol• 20.
4.
Lum, H., and Sonie Lau (1989). Intelligent Computational Systems for Space Applications, Acta Astronautica, Vol. 22.
5.
Bayer, S. E. (1989). Space Station Freedom Program Capabilities for the Development and Application of Advanced Automation. The MrI'RE Corporation, MTR-89W00279, NASA/OSS Contract No.: NAS918057, December 1989.
6.
Office of Exploration (1988). Exploration Studies Technical Report-FY 1988 Status, Vols. 1-3. NASA Technical Memorandum 4075, December 1988.
7.
Friedland, P., M. Zweben, and M. Compton, Artificial Intelligence Research Branch 1990 Progress Report and Future Plans, Report RIA-90-4-27-1, April 1990.
8.
Glass, B. J. A Model-Based Approach to the Symbolic Control of Space Subsystems. 1990 AIAA Guidance, Navigation and Control Conference, Portland, OR, August 1990 (AIAA Paper No. 903430).
9.
Cheeseman, P., et al. Automatic Classification of Spectra from the Infrared Astronomical Satellite (IRAS), NASA Reference Publication 1217, March 1989.
Conclusions The current NASA program for the development of intelligent systems addresses the needs of a wide range of application areas and projects. Investigations show that the application of intelligent systems is either cost effective and/or enables mission goals not otherwise possible• The potential return on investments for intelligent systems can be achieved through induced savings within a few years, as described in this paper• To ensure that the benefits of intelligent systems can be realized, specific technical areas must be addressed, particularly those involving system verification and validation. In addition, managerial changes are required to facilitate the acceptance and implementation of intelligent systems in space missions• Only then will we be able to pursue an aggressive exploration of space, realize uncompromised mission goals and objectives, and execute the overall program within the established time and cost constraints. Utilization of intelligent systems will effectively complement the human capabilities and NOT compete or replace the human. In summary, cost effective Lunar and Mars missions will only be accomplished with the total integration of the human and the intelligent computational environment. Acknowledizements v
The authors wish to thank Mrs. Leslie Hoffman and Ms. Dorothy Hammond for their dedication and patience in the organization and preparation of this paper, without whose assistance this paper would not have been completed.
Lure, H., and E. Heer (1988). Intelligent, Autonomous Systems in Space. Acta Astronautica, Vol. 17, No• 10, pp. 1081-1091.
10. NASA Report of the 90-Day Study on Human Exploration of the Moon and Mars, November 1989. 11. Muratore, J., T. A. Heindel, R. Z. McFarland, T. B. Murphy, and A. N. Rasmussen (1988). Applications of Artificial Intelligence to Space Shuttle Mission Control. SPIE, Cambridge, Massachusetts. 12. Space Station Freedom Automation and Robotics: An Assessment of the Potential for Increased Productivity, Mitre Corporation, March 1990.
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13. Smith, J. H., M. A. Gyamfi, K. Volkmer, and W. F. Zimmerman (1987). The Space Station Assembly Phase: Flight Telerobotic Servicer Feasibility Volume 2: Methodology and Case Study. JPL Publication 87-42, Vol. 2, September 1987. 14. McDonnell Douglas Astronautics Company (1986). Automation and Robotics Plans (DR-17). Document No. MDC H2036B, Huntington Beach, California, December 1986. 15. Asker, J. R. (1990). EVA Requirement Dispute Threatens to Disrupt Space Station Program. Aviation Week & Space Technology, March 26, 1990.
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0094-5765/91 $3.00 + 0.00 Pergamon
Press plc
COST-EFFECTIVE IMPLEMENTATION OF INTELLIGENT SYSTEMS Henry Lure Jr Chief, Information Sciences Division NASA-Ames Research Center Moffett Field, CA 94035 Ewald Heer Heer Associates, Inc. La Canada, CA 91011 Abstract
Significant advances have occurred during the last decade in knowledge-based engineering research and knowledge-based system (KBS) demonstrations and evaluations using integrated intelligent system technologies. Performance and simulation data obtained to date in real-time operational environments suggest that cost-effective utilization of intelligent system technologies can be realized. In this paper the rationale and potential benefits for typical examples of application projects that demonstrate an increase in productivity through the use of intelligent system technologies are discussed. These demonstration projects have provided an insight into additional technology needs and cultural barriers which are currently impeding the transition of the technology into operational environments. Proposed methods which address technology evolution and implementation are also discussed. Introduction
As Space Station Freedom (SSF) moves from planning to hardware development and implementation, the National Aeronautics and Space Administration (NASA) has initiated the planning process for additional large space projects over the next few years (Fig. 1). The primary goals of this program are to return to the Moon and establish an outpost and to advance human exploration of Mars during the early 2000 time period. These projects involve complex infrastructures of transportation, habitability, and communication systems and place the highest demands on systems reliability and performance.
Fig. 1. America's Future in Space The potential and importance of automation and robotic technologies in space operations were recognized and supported by NASA since the early space flight ventures. During the last decade, automation and robotics have received progressively more attention with emphasis being placed on research in artificial intelligence which will lead to significant advances in the development of intelligent systems.
To ensure the success of these undertakings, the automation and robotics (A&R) technologies must reach a certain state of maturity to allow the assembly and construction of large-scale systems in space and the performance of tasks involving monitoring and maintenance over long operational periods. The resources that must be invoked to accomplish these tasks include astronauts' intravehicular activity (IVA) and extravehicular activity (EVA), remote ground operations and control, built-in system fault management, and telerobetics. WA and EVA are performed by astronauts whose time is most valuable and primarily needed for scientific projects. Thus, NASA's goals are to enhance and complement human functions with intelligent automation and robotics, e.g., tasks that can typically be clone automatically or by robots.
Today's state-of-the-art in intelligent systems technology is the result of many years of research, development, and evaluation toward application readiness. 1-4 The generic nature of the advanced automation research and development program sponsored by NASA's Office of Aeronautics, Exploration, and Technology (OAET) and Office of Space Flight (OSF) makes the results applicable in a broad spectrum of contexts, some of which will be discussed in this paper. In most of these cases, "conventional" technologies are integrated with artificial intelligence techniques leading to intelligent systems that can perform, to an appreciable degree, functions generally attributed to intelligent,
Copyright © 1990 by the American Institute of Aeronautics and Astronautics, Inc. No copyright is asserted in the United States under Title 17, U.S. Code. The U.S. Government has a royalty-free license to exercise all rights under the copyright claimed herein for Governmental purposes. All other rights are reserved by the owner.
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reasonable humans. Nevertheless, it should be remembered that these intelligent systems are only able to function under the direction and guidance of humans and cannot solve all problems autonomously. They tend to function as augmentations of human mental capabilities. Considerable advances have occurred in knowledge-based engineering research, knowledgebased systems (KBS) demonstrations, and evaluations using integrated intelligent systems technologies. Performance and simulation data obtained to date in real-time operational environments suggest that costeffective uses of intelligent systems can be made if the applications are focused in five areas to be introduced in the following section. The rationale and projected benefits for these specific application areas and typical examples of application projects that demonstrate the increase in productivity which are obtained through the use of KBS technologies are described. Finally, the incorporation of intelligent system technologies into robotic systems to provide significantly increased performance capabilities with the human operating at a high level of human-machine interaction is presented.
Avvlication Areas and Proiects In reviewing the planning documentation on the Space Station and later human exploration missions to the Moon and Mars, a broad spectrum of system functions that may be performed or may benefit from the incorporation and application of intelligent systems is identified. 5"6 Possible applications range from relatively simple knowledge-based expert systems assisting astronauts in quick decision making to complex autonomous robots performing complex diagnostics and repair tasks. In the following, a representative set of functional areas in which intelligent systems will play a particularly strong role is briefly discussed. Space and Aeronautical Operations Aircraft and spacecraft once had a much higher human-to-machine functional ratio than can be tolerated in today's complex missions and systems. Now there is an ever increasing need for automation to reduce the human's interaction in the control loop of operating systems, to improve critical decision-making capabilities of humans and machines, and to reduce the training time for humans still in the control loop but functioning at a higher level of supervision. These requirements for automated operations technology and, in particular for intelligent systems, are addressed within the context of application projects which include the development of: Principal Investigator in a Box (PI-in-a-Box): a knowledge-based system that provides, expert advice to crew members to allow them to conduct better "reactive" science. 7 Aircraft Descent Advisors: computer-decision aids which support air traffic controllers and
provide for the possibility to increase traffic volume in terminal areas. Planning Aids for Proximity Operations: knowledge-based systems based on human factors, control theory, and operational experience. On-orbit Fluid Transfer Systems: software systems which allow a ground-based experimenter to conduct research experiments while, at the same time, allowing the Space Shuttle crew to monitor and control the transfer of cryogenic superfluid helium in space. On-Board Monitoring, Diagnosis, and Control The performance of in-flight systems is subject to many unpredicted changes requiring close and timeconsuming attention by flight crew members. Automation here provides real-time capabilities which augment and complement human performance levels and enhance mission safety by the early discovery of incipient failures. Testing and qualifying intelligent system technologies relevant to on-board monitoring, diagnosis, and control are accomplished in application projects related to the demonstration of: Space Station Freedom Thermal Control System (TEXSYS): an advanced automation project for the development and validation of a rule- and model-based system to perform real-time control and fault detection, isolation, and recovery of a complex physical system, s Planetary Rovers: the development and validation of intelligent systems for on-board rover applications. Aids for Rotorcraft: the determination of quantitative measures and requirements for evaluations of pilots' information including the testing and validating of aids for computer vision and guidance in rotorcraft flight. Preservation and Utilization of Program Life-Cycle Knowledge At every stage of program and system development, factual data and information are created that are applicable to later system operations and maintenance and which are inputs to the development of knowledgebases for relevant expert systems. This requires that data and information are captured in a methodical way throughout the design, construction, test, and operation phases. Generally, the data and information must be integrated from many disparate sources and will provide focused problem-solving capabilities through the development of knowledge bases for intelligent systems. Specific application projects are currently addressing the problems of life-cycle knowledge capture and are contributing to the development of :
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Electronic Designer's Notebook: the development of software for automatically capturing formal and informal heuristic design knowledge such as the SIRTF Tertiary Mirror Assembly. 7 Corporate Memory Facility: the development and application of knowledge-based technologies for the management of the corporate memory. Management and Analysis of Science and Engineering Data The major reason for space missions is to collect scientific and engineering data and learn more about the world surrounding us. Current data acquisition capabilities are enormous and rapidly multiplying. It is, therefore, necessary to significantly increase the capabilities for analyzing large science databases on Earth and for improving the effective use of communication channel bandwidth capacity. In addition, it is often highly effective to conduct data analyses in-situ on lunar and planetary surfaces, and thus, avoid overloading the communication channels. Some of the means for management and analysis of science and engineering data from space are obtained through the development of: AutoClass: based on Bayesian classification techniques and applied, together with advanced reasoning technology, to the classification of large data sets. 9 Virtual Environment Workstation (VIEWS): full information display of integrated time-varying data in a virtual environment format. Automation of DTA/GC: the development of sof~vare for fault diagnosis and correction and in-situ analysis. Operations of Autonomous Robotic Systems The Space Station Program is currently developing a robotic system based on three primary elements. These include the Shuttle-based Remote Manipulator System (RMS), the Mobile Remote Manipulator System (MRMS), and the Flight Telerobotic Servicer (FTS), which will be used while mounted on appropriate mobility bases to perform assembly assistance, inspections, servicing, and maintenance functions. As now envisioned, these systems will be operated in the telerobotic mode, where the operator is located in a control station on the Space Shuttle, the Space Station, or an EVA station on the MRMS. Sensory feedback to the operator is accomplished by direct vision or video display. All three systems are programmable so that their end effectors move automatically to a specified location within acceptable accuracies. In addition, the FTS will include a hierarchical control architecture, which will provide the basis for adapting autonomous capabilities, i.e., intelligent systems technologies, at a later stage. It is
AA 24--~
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expected that such capabilities will contribute considerably to cost-effective operations in space. From an intelligent system point of view, technically most demanding applications of robotic systems are science missions involving Mars sample return vehicles with local rovers and long-range Mars surface rovers: ° These unmanned missions perform the necessary scientific investigations to qualify planetary sites for subsequent human outpost construction. The Earthbased operation center and the remote robotic devices communicate with each other through a radio link. However, since the communication time delay between Earth and Mars varies between about 8 to 40 minutes, time and cost-effective operations require that the remote equipment on the planetary surface have substantial onboard intelligent system capabilities for autonomous navigation, site identification, sample acquisition and analysis, and other operations. In addition, there must be intelligent system capabilities to perform autonomous diagnoses of operations, fault isolation, and recovery from faulty behavior. The Lunar Outpost architectures include landing and launch site facilities, crew habitation facilities, in-situ resource mining, power production facilities, and the like. Similarly, the Martian Outpost architecture includes landing and launch facilities, habitation facilities, photovoltaic power systems, etc. The construction and operation of these facilities and the associated infrastructure call for an entire array of robotic equipment such as roving vehicles with manipulators, front loaders, cranes, and other machinery which require manipulative dexterity. The control of these systems is usually done from on-site control stations by telerobotic means of operation as indicated above for the Space Station Initial Operation Configuration (IOC). However, during the initial setup phase of the outposts when humans are not yet present, substantial autonomous machine capabilities, provided by intelligent systems, may be required to overcome, at least partially, the constraints of communication time delay. There are two major categories of intelligent system applications in future NASA space missions. The first category deals with expert and knowledge-based systems in support of system management functions including planning, scheduling, monitoring, control, diagnosis, fault isolation, and recovery. These functions are performed in support of human decision makers who employ the intelligent systems in a supporting role. In the second category, the telerobotic control mode of robotic devices is extended by intelligent systems to an autonomous control mode in which the humans act as supervisors of the robotic devices, and their level of communication with the intelligent machines is correspondingly high. In addition to the functions performed by the first category, the robotic devices are now also able to interact with the environment by virtue of sensory information feedback. This information, together with the resident knowledge-base and the planning, monitoring, simulation, and diagnostic
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systems, provides the means for autonomous behavior and operation. Cost-Effective I m o l e m e n t a t i o n
The applications of intelligent systems in the Space Station and later human exploration missions are motivated by potential benefits resulting from reduced total life-cycle cost, increased operational reliability, and technology transfer to industry. A system is considered cost effective if, over the operational life time, the present value of all benefits is equal or greater than the present value of all costs. It is expected that the application of intelligent systems in the space program will be cost effective because their application in business and industry generally bears this out. Although Earth-based technology developments and demonstrations point to the potential cost effectiveness of intelligent systems in future space missions, to date little applicable experience and information is available regarding actual space operations. Generally, the benefits of intelligent system applications are: fewer humans involved in complex operation processes; better and more consistent performance of recurring functions; enabled and more reliable system performance in dangerous environments; and, intelligent operations in areas not accessible by humans. For the formulation of quantitative productivity projections, the available data are usually incomplete and not comprehensive enough. The following estimations are, therefore, notably qualitative, arrived at primarily by heuristic processes.
Nevertheless, the simpler case to evaluate is ground support because there is comparative experimental data from NASA/Johnson Space Center's Mission Control Center applications. For example, the Integration Communications Officer Expert Systems Project11 has shown that at least 25% savings can be achieved in ground-based system monitoring operations with intelligent systems. With some technical improvements under development, this can probably be increased to 50%. Although, no comparative data are as yet available for planning and scheduling based on current developments, it is estimated that similar cost savings will be realized for ground mission operations, checkout, and training. Taking into account qualitative comparisons between conventional and knowledgebased thermal control systems for the Space Shuttle (Fig. 2), the operations with intelligent systems are expected to improve the cost effectiveness by up to 30% for operations from the ground. Using intelligent software for simulation and training usually shortens training time and contributes to savings of roughly 20% to 30% compared with current techniques.
Intelligent Management Systems Potential cost savings resulting from the application of intelligent systems will most likely be due to the possible reduction of manpower in system operations. In-space costs for every astronaut are estimated at $40,000 per EVA hour and $15,000 per IVA hour, which include support costs and other overhead costs. In comparison, the costs for ground mission support are about $40 to $60 per work hour, which also include support costs and overhead. Whatever the cumulative work hour savings, because of intelligent system applications, they must be traded against the costs of developing, installing, and operating the intelligent system itself. To realize any savings requires that the time value of the total operation and maintenance costs, the integration and implementation of the intelligent systems, and the time value of the related capital expenditures be less than the time value of the operation and maintenance costs using current techniques and procedures. The capital expenditures are usually up to an order of magnitude higher for space-qualified software systems than for equivalent systems applied in ground operations. Because of the large difference in hourly costs, it may be tentatively concluded from these considerations that reducing astronaut time by substituting intelligent systems, where possible, will be more cost effective than reducing human work hours on the ground.
ICO.PAR,SO. I TCS TEXSYS CONVENTIONAL CONTROL SYSTEM I KNOWLEDGE BASED SYSTEM I NOMINAL OPERATIONS
•
Displays data for real-time monitor and control by a human Prod/Idesautomated control routines for system parameter changes by e human
Displays and ANALYZES data for real-time operations AUTOMATICALLY controls nominal and off-nominal processes
FAULT DETECTION, iSOLATION, AND RECOVERY
•
Displays data of system health and status Alerts humansof detrimental system performance
•
Displays and ANALYZES data of system health and status • ACTS upon detrimental system status to recover and EXPLAINS actions to recover
Fig. 2. Performance Capabilities of Automated Thermal Control System vs. a "Conventional" System
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However, the greatest cost savings are expected from the systematic preservation and utilization of program life-cycle knowledge which will provide solutions for upcoming problems in a cost-effective manner without time-intensive translation of design information from design and mission operations documents a n d / o r lengthy consultation with experts. Current estimates are based on the Electronic Designer's Notebook. Although indications of possible future cost savings are very spotty, the ubiquitous applicability of program life-cycle knowledge in space system operations results in a conclusion that operational savings will be many times that of the development costs of the related intelligent systems. There is also a great potential to save costs in the analysis of science and engineering data by employing intelligent systems such as AutoClass. Many of these data, which come back to the ground-based operations center, often receive only cursory inspection or are not analyzed at all because of the large volume, the fading newsworthiness, and the high expense for analysis by humans. A review of the "lessons learned" from Skylab, Spacelab, and other Space Shuttle experiences gained through interviews with current and former astronauts and mission operations personnel as well as a review of the data from the Soviet Salyut and Mir space station operations, the U. S. nuclear submarine fleet, and the Antarctic research station indicates that there is strong support from the astronaut community for the use of advanced automation and robotics in a broad range of areas. 12 The application of intelligent systems allows astronauts to devote more time to the broader mission objectives while relegating the routine aspects of recordkeeping, planning, scheduling, monitoring, control, fault detection, fault isolation, and fault recovery to intelligent systems. The most cost-effective overation in svace takes place when the astronauts can devote a minimum of their time to the routine tasks and a maximum of their time to the ~cience and technoloe-¢ obiectives of the mission. Depending on the capital investment for the intelligent systems, the savings can be substantial as compared with operations by astronauts only. Estimated cost savings will be at least an order of magnitude greater for in-space operations than for ground operations if the reduction of work hours and astronaut hours due to intelligent systems are the same. Astronauts using PI-in-a-Box approaches may be as effective as an equivalent principal investigator (PI) on site, particularly if there is the possibility of intermittent communication with the PI on the ground. The cost effectiveness of such intelligent systems can only be estimated but is probably in the 90% range. Tables 1 and 2 indicate the potential cost savings from the use of advanced automation for ground-based mission operations and on-board operations, respectively. v
.
Table 1. Potential Cost Savings from Ground Support Advanced Automation 12
Activity
Potential Savings (% reduction in task time)
Operations Planningand Integration TrajectoryDesign and Dynamics Space StationControl Center Space StationTraining Facility Payload Planning Payload Operations Support
25-50 10-25 25-50 10-25 10-25 25-50
Table 2. Potential Savings from On-board Automation 12 Activity
Percent Savings (% reduction in task time)
ActivityPlanning System Monitoringand Control FlightControl FlightPlanning Training Inventory Management Internal Maintenanceand Servicing External Maintenanceand Servicing ProximateOperations Payload Operations Reboost
5-10 5-10 10-20 5-25 10-25 10-25 5-10 2.5-5 5-10 5-10 5-10
Autonomous Robotic Systems In this functional area, an assumption is made that telerobotic technology is available and that intelligent systems are added in order to provide autonomous capabilities to robotic devices and, thus, increase the cost effectiveness of intelligent in-space operations. However, the experience base of telerobotic operations in space is limited and primarily restricted to the Space Shuttlebased RMS. Estimates of the cost effectiveness of intelligent systems added to telerobotic devices are necessarily tenuous projections into the future and only indicative of their potential. To project potential cost-effectiveness increases through the use of intelligent systems, a situation is assumed where over a certain time interval all operations are done by EVA. A teleoperated FTS with the IVA performed by an on-board astronaut is then substituted. The FTS system will then be executing a fraction of the total previous EVA operations. Significant cost savings can be achieved when all-EVA activities are transitioned to the FTS and EVA mixed modes of operations. 13 An additional step can now be taken with the addition of intelligent systems, i.e., autonomous capabilities to the FTS, thus, reducing corresponding EVA and WA and further increasing the astronaut's productivity and system cost effectiveness as shown in Figure 3. Similar statements can also be made about the addition of autonomous capabilities to the RMS and MRMS.
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APPLICATION ChcckllsLs Rec~d keeplnildocu~nC~lion
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The only physical difference between these two modes of operation is that the second has incorporated the intelligent systems which provide the autonomous capabilities for the FTS to perform 80% of EVA maintenance work. Compared with the first mode of operation, this requires an initial, additional capital investment representing the cost of the intelligent systems. Neglecting minor additional costs and benefits and assuming the above-stated EVA and IVA hourly costs, the first approximation of the cost differences of the two modes of operation can be calculated. An estimated annual cost for the first approach, teleoperated mode of operation, results in $40 million and for the second, autonomous mode of operation, about $12.6 million plus the initial capital investment for the intelligent systems.
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Fig. 3. Astronaut Estimates of Productivity Impact of A&R Applications 12
Estimates show that of all the exterior maintenance tasks on the Space Station, approximately 90% must be devoted to inspection and 10% to the alleviation of trouble spots and other maintenance work. 14 Inspection tasks generally are done routinely and to a large degree repetitively. They are, therefore, prime candidates to be performed by the FTS in an autonomous mode of operation. To realize the full potential of the FTS, it should be equipped with intelligent systems which enable it to have unrestricted mobility about the Space Station exterior, accumulate inspection data, perform diagnostic inferences, and alert the astronaut crew for further decisions and actions, if required. Because of their general uniqueness, it is expected that most of the alleviating actions must still be done by EVA or by telerobotic operation of the FTS while a remaining few will be possible by autonomous FTS operations. Also, some routine inspections by the FTS will still be checked by EVA for increased reliability and safety. Recent estimates by W. F. Fisher and C. R. Price show that the total EVA maintenance time for the Space Station after IOC is 2284 hours per y e a r : s Of this time, about 90% is required for inspection and about 10% for fault alleviation and correction work. Based on the statements above, two modes of operation are considered for comparison and cost-effectiveness evaluation: first, 10% of the 2284 hours of total EVA work, or 228 hours, will actually be done by EVA, while the rest of the maintenance work, equivalent to 2056 hours of EVA, will be done by the teleoperated FTS; and, second, 10% of the 2284 hours of total EVA work, or 228 hours, will actually be clone by EVA, the equivalent of 10% of the total EVA work will be done by the teleoperated FTS, and the equivalent of 80% of the total EVA work will be done by the autonomous FTS.
Using the above costs, the present value at IOC of the annual savings of $27.7M ($40.3M - $12.6M) for a selected number of years of Space Shuttle operations using a uniform discount rate of 8%, is shown in Table 1. These dollar amounts, if invested at IOC for the required intelligent systems, will be paid back after the indicated number of years. For example, a reasonable estimate for the intelligent system cost is $70M at IOC, which amounts to 25% of the estimated cost of $280M for the teleoperated FTS. This will be paid back through savings after three years. For a total operational lifetime of 30 years for the Space Station, the value of all savings at IOC will then be $238.5M ($308.5M - $70.0M).
T a b l e 3. D i s c o u n t e d
Years of Operation after IOC
1 2 3 4 5 10 20 30
Future S a v i n g s Systems
Present Worth Factor, 8% D.R.
0.926 1.783 2.577 3.312 3.993 6.710 9.818 11.258
for I n t e l l i g e n t
Discounted Savings for $27,7M Ann'l. Rate
$ $ $ $ $ $ $ $
25.4M 48.9M 70.6M 90.7M 109.4M 183.9M 269.0M 308.5M
Technical progress is being made in the real-time control of intelligent robotic systems (Fig. 4). Current emphasis is being placed in the critical areas necessary for autonomous operations of intelligent robotic systems: end point control of flexible-link manipulators; objectbased control of dual cooperating manipulators; and object-based control of two cooperating mobile robots. The FTS is the application focus for the research effort currently being conducted at Stanford University's Autonomous Robotics Systems Laboratory. The evaluation of the cost effectiveness of intelligent for robotic devices on the Lunar Surface and Mars follows similar lines as shown above if astronauts are on site and the comparison can be made between EVA, teleoperation, and autonomous operations. A systems
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major aspect in such evaluations is to what degree the robotic functions to be performed are repetitive and can be standardized. Future designs must take these aspects into account to ensure the cost effectiveness of intelligent systems.
Similar arguments are valid for science missions to Mars involving robotic devices. Because of the communication delay, a Martian roving vehicle teleoperated from Earth may be able to operate, on the average, only about 5% of the time. With on-board intelligent systems it may increase its average useful operating time up to 80%, presumably, increasing the volume of science information by at least an order of magnitude. Considering the relative cost of the intelligent systems compared with the total mission cost, it can be concluded that the initial capital investment for the addition of intelligent systems is highly cost effective. Technology Challenges and Cultural Barriers
Fig. 4. Real-Time Control Capabilities for an Advanced FTS During the initial setup phase of the Lunar and Mars Outposts, the functions to be performed are essentially unique tasks with little repetitiveness and standardization. Correspondingly, intelligent systems will be incorporated where required to provide enablement of the operation rather than for economic reasons. The technology elements for a projected integrated space habitat infrastructure are being developed and will be evaluated in various testbeds to assess their overall cost effectiveness as depicted in Figure 5. If such unique operations can be accomplished, for example, by teleoperation from the Earth-based control center, the initial capital investment for more advanced technologies like intelligent systems will most likely not be made.
As indicated at the beginning of this paper, a broad spectrum of intelligent system technologies is under development within certain application contexts to ensure timely availability for future space applications. Nevertheless, there are technical areas which pose development barriers and require long-range research and development planning. Some of the important areas of technology challenges and their relative degrees of complexity are identified in Figure 6.
ITechnology ChallengesI .
Real T i m e Performance -
C o m p u t a t i o n a l S y s t e m S o f t w a r e Infrastructure Fault M a n a g e m e n t and Control
Systems Integration ( " C o n v e n t i o n a l " M o d e l s with AI-Based Models) •
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Development E n v i r o n m e n t v s O p e r a t i o n a l E n v i r o n m e n t Validation Metrics Design K n o w l e d g e A c q u i s i t i o n t h r o u g h o u t Life Cycle Intelligent Human Interfaces (Human P e r f o r m a n c e Parameters)
D E G R E E OF C O M P L E X I T Y
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FOR I TYPICAL ADVANCED AUTOMATION CAPABILITIES I
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Fig. 6. Technology Challenges and Level of Complexity for Advanced Automation
Fig. 5. Evolution of Testbeds for a Space Habitat Infrastructure
In addition to developing the required technologies, the appropriate managerial environment to facilitate the acceptance and implementation of intelligent systems for practical applications in space systems must be in place.
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The realization that intelligent systems are in many application contexts either enabling the mission objectives or are highly cost effective, or both, is usually not enough to ensure that the necessary investments for their incorporation in space missions will be made. To foster a receptive environment and remove corresponding barriers require high-level and long-range managerial decisions. Figure 7 identifies recommended "cultural" changes for the implementation and incorporation of intelligent systems in space missions.
i for I i Implementation of Advanced Automation I
We also wish to acknowledge the many technical contributions made by our fellow colleagues in the automation sciences community, especially Mr. Gregg Swietek and Mr. David Weeks, which have been incorporated in this paper. References Heer, E., and H. Lure. Machine Intelligence and Autonomy for Aerospace Systems, American Institute of Aeronautics and Astronautics Progress in Astronautics and Aeronautics Series, Vol. 115, 1988.
Recommended"Cultural" Changes
•
• . • •
Integrate/Manage/Use all Agency Resources to Accomplish Project and Mission Goals and Objectives Implement Effective Team Collaboration between Centers Implement a Distributed Unified Information System for Project Management and Control L e v e r a g e / U s e Commercial/Industry,'DoD Standards and T e c h n o l o g i e s whenever Possible Accept/Use Advanced Automation and Expert Systems in Operational Environment Design and Manage for Evolutionary Growth and Technology Upgrades Incorporate System Fault Management from Design through Operations Use Life Cycle Design Costs for Determination of Return-on-Investment (ROI)
Fig. 7. Recommended "Cultural" Changes for Implementation of Advanced Automation
2.
3.
Lure, H., and E. Heer (1988)• Technology Forecast and Applications for Autonomous, Intelligent Systems. Acta Astronautica, Vol• 20.
4.
Lum, H., and Sonie Lau (1989). Intelligent Computational Systems for Space Applications, Acta Astronautica, Vol. 22.
5.
Bayer, S. E. (1989). Space Station Freedom Program Capabilities for the Development and Application of Advanced Automation. The MrI'RE Corporation, MTR-89W00279, NASA/OSS Contract No.: NAS918057, December 1989.
6.
Office of Exploration (1988). Exploration Studies Technical Report-FY 1988 Status, Vols. 1-3. NASA Technical Memorandum 4075, December 1988.
7.
Friedland, P., M. Zweben, and M. Compton, Artificial Intelligence Research Branch 1990 Progress Report and Future Plans, Report RIA-90-4-27-1, April 1990.
8.
Glass, B. J. A Model-Based Approach to the Symbolic Control of Space Subsystems. 1990 AIAA Guidance, Navigation and Control Conference, Portland, OR, August 1990 (AIAA Paper No. 903430).
9.
Cheeseman, P., et al. Automatic Classification of Spectra from the Infrared Astronomical Satellite (IRAS), NASA Reference Publication 1217, March 1989.
Conclusions The current NASA program for the development of intelligent systems addresses the needs of a wide range of application areas and projects. Investigations show that the application of intelligent systems is either cost effective and/or enables mission goals not otherwise possible• The potential return on investments for intelligent systems can be achieved through induced savings within a few years, as described in this paper• To ensure that the benefits of intelligent systems can be realized, specific technical areas must be addressed, particularly those involving system verification and validation. In addition, managerial changes are required to facilitate the acceptance and implementation of intelligent systems in space missions• Only then will we be able to pursue an aggressive exploration of space, realize uncompromised mission goals and objectives, and execute the overall program within the established time and cost constraints. Utilization of intelligent systems will effectively complement the human capabilities and NOT compete or replace the human. In summary, cost effective Lunar and Mars missions will only be accomplished with the total integration of the human and the intelligent computational environment. Acknowledizements v
The authors wish to thank Mrs. Leslie Hoffman and Ms. Dorothy Hammond for their dedication and patience in the organization and preparation of this paper, without whose assistance this paper would not have been completed.
Lure, H., and E. Heer (1988). Intelligent, Autonomous Systems in Space. Acta Astronautica, Vol. 17, No• 10, pp. 1081-1091.
10. NASA Report of the 90-Day Study on Human Exploration of the Moon and Mars, November 1989. 11. Muratore, J., T. A. Heindel, R. Z. McFarland, T. B. Murphy, and A. N. Rasmussen (1988). Applications of Artificial Intelligence to Space Shuttle Mission Control. SPIE, Cambridge, Massachusetts. 12. Space Station Freedom Automation and Robotics: An Assessment of the Potential for Increased Productivity, Mitre Corporation, March 1990.
41st IAF Congress
13. Smith, J. H., M. A. Gyamfi, K. Volkmer, and W. F. Zimmerman (1987). The Space Station Assembly Phase: Flight Telerobotic Servicer Feasibility Volume 2: Methodology and Case Study. JPL Publication 87-42, Vol. 2, September 1987. 14. McDonnell Douglas Astronautics Company (1986). Automation and Robotics Plans (DR-17). Document No. MDC H2036B, Huntington Beach, California, December 1986. 15. Asker, J. R. (1990). EVA Requirement Dispute Threatens to Disrupt Space Station Program. Aviation Week & Space Technology, March 26, 1990.
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