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This invention is an adaptive neuron for use in neural network processors. The adaptive neuron participates in the supervised learning phase of operation on a co-equal basis with the synapse matrix elements by adaptively changing its gain in a similar manner to the change of weights in the synapse IO elements. In this manner, training time is decreased by as much as three orders of magnitude.
This paper describes the development status of a prototype supervised intelligent robot for space application for purposes of (1) helping the crew of a spacecraft such as the Space Station with various tasks, such as holding objects and retrieving/replacing tools and other objects from/into storage, and (2) for purposes of retrieving detached objects, such as equipment or crew, that have become separated from their spacecraft. In addition to this set of tasks in this low-Earth-orbiting spacecraft environment, it is argued that certain aspects of the technology can be viewed as generic in approach, thereby offering insight into intelligent robots for other tasks and environments. Candidate software architectures and their key technical issues which enable real work in real environments to be accomplished safely and robustly are addressed. Results of computer simulations of grasping floating objects are presented. Also described are characterization results on the usable reduced gravity environment in an aircraft flying parabola (to simulate weightlessness) and results on hardware performance there. These results show it is feasible to use that environment for evaluative testing of dexterous grasping based on real-time vision of freely rotating and translating objects.
A fuzzy-neural control system simulation was developed for the control of a camera platform used to observe aircraft on final approach to an aircraft carrier. The fuzzy-neural approach to control combines the structure of a fuzzy knowledge base with a supervised neural network's ability to adapt and improve. The performance characteristics of this hybrid system were compared to those of a fuzzy system and a neural network system developed independently to determine if the fusion of these two technologies offers any advantage over the use of one or the other. The results of this study indicate that the fuzzy-neural approach to control offers some advantages over either fuzzy or neural control alone.
The Air Force has several unique requirements that are being met through the development of construction robotic technology. The missions associated with these requirements place construction/repair equipment operators in potentially harmful situations. Additionally, force reductions require that human resources be leveraged to the maximum extent possible and that more stringent construction repair requirements push for increased automation. To solve these problems, the U.S. Air Force is undertaking a research and development effort at Tyndall AFB, FL to develop robotic teleoperation, telerobotics, robotic vehicle communications, automated damage assessment, vehicle navigation, mission/vehicle task control architecture, and associated computing environment. The ultimate goal is the fielding of robotic repair capability operating at the level of supervised autonomy. The authors of this paper will discuss current and planned efforts in construction/repair, explosive ordnance disposal, hazardous waste cleanup, fire fighting, and space construction.
The Georgia Tech portion of the Intelligent Control Center project includes several complementary activities. Two major activities entail thesis level research; the other activities are either support activities or preliminary explorations (e.g., task analyses) to support the research. The first research activity is the development of principles for the design of active interfaces to support monitoring during real-time supports. It is well known that as the operator's task becomes less active, i.e., more monitoring and less active control, there is concern that the operator will be less involved and less able to rapidly identify anomalous or failure situations. The research project to design active monitoring interfaces is an attempt to remediate this undesirable side-effect of increasingly automated control systems that still depend ultimately on operator supervision. The second research activity is the exploration of the use of case-based reasoning as a way to accumulate operator experience and make it available in computational form.
Real-time video presentations are provided in the field of operator-supervised automation and teleoperation, particularly in control stations having movable cameras for optimal viewing of a region of interest in robotics and teleoperations for performing different types of tasks. Movable monitors to match the corresponding camera orientations (pan, tilt, and roll) are provided in order to match the coordinate systems of all the monitors to the operator internal coordinate system. Automated control of the arrangement of cameras and monitors, and of the configuration of system parameters, is provided for optimal viewing and performance of each type of task for each operator since operators have different individual characteristics. The optimal viewing arrangement and system parameter configuration is determined and stored for each operator in performing each of many types of tasks in order to aid the automation of setting up optimal arrangements and configurations for successive tasks in real time. Factors in determining what is optimal include the operator's ability to use hand-controllers for each type of task. Robot joint locations, forces and torques are used, as well as the operator's identity, to identify the current type of task being performed in order to call up a stored optimal viewing arrangement and system parameter configuration.
It is known that an effective control system is the key condition for successful implementation of high-performance magnetic servo systems. Major issues to design such control systems are nonlinearity; unmodeled dynamics, such as secondary effects for copper resistance, stray fields, and saturation; and that disturbance rejection for the load effect reacts directly on the servo system without transmission elements. One typical approach to design control systems under these conditions is a special type of nonlinear feedback called gain scheduling. It accommodates linear regulators whose parameters are changed as a function of operating conditions in a preprogrammed way. In this paper, an on-line learning fuzzy control strategy is proposed. To inherit the wealth of linear control design, the relations between linear feedback and fuzzy logic controllers have been established. The exercise of engineering axioms of linear control design is thus transformed into tuning of appropriate fuzzy parameters. Furthermore, fuzzy logic control brings the domain of candidate control laws from linear into nonlinear, and brings new prospects into design of the local controllers. On the other hand, a self-learning scheme is utilized to automatically tune the fuzzy rule base. It is based on network learning infrastructure; statistical approximation to assign credit; animal learning method to update the reinforcement map with a fast learning rate; and temporal difference predictive scheme to optimize the control laws. Different from supervised and statistical unsupervised learning schemes, the proposed method learns on-line from past experience and information from the process and forms a rule base of an FLC system from randomly assigned initial control rules.
A program was initiated within the past several years to develop operational procedures for automated assembly of truss structures suitable for large-aperture antennas. The assembly operations require the use of a robotic manipulator and are based on the principle of supervised autonomy to minimize crew resources. A hardware testbed was established to support development and evaluation testing. A brute-force automation approach was used to develop the baseline assembly hardware and software techniques. As the system matured and an operation was proven, upgrades were incorprated and assessed against the baseline test results. This paper summarizes the developmental phases of the program, the results of several assembly tests, the current status, and a series of proposed developments for additional hardware and software control capability. No problems that would preclude automated in-space assembly of truss structures have been encountered. The current system was developed at a breadboard level and continued development at an enhanced level is warranted.
Several proposed space missions include precision reflectors that are larger in diameter than any current or proposed launch vehicle. Most of these reflectors will require a truss structure to accurately position the reflector panels and these reflectors will likely require assembly in orbit. A research program has been conducted at the NASA Langley Research Center to develop the technology required for the robotic assembly of truss structures. The focus of this research has been on hardware concepts, computer software control systems, and operator interfaces necessary to perform supervised autonomous assembly. A special facility was developed and four assembly and disassembly tests of a 102-strut tetrahedral truss have been conducted. The test procedures were developed around traditional 'pick-and-place' robotic techniques that rely on positioning repeatability for successful operation. The data from two of the four tests were evaluated and are presented in this report. All operations in the tests were controlled by predefined sequences stored in a command file, and the operator intervened only when the system paused because of the failure of an actuator command. The tests were successful in identifying potential pitfalls in a telerobotic system, many of which would not have been readily anticipated or incurred through simulation studies. Addressing the total integrated task, instead of bench testing the component parts, forced all aspects of the task to be evaluated. Although the test results indicate that additional developments should be pursued, no problems were encountered that would preclude automated assembly in space as a viable construction method.
This paper presents an overview of the proposed Lyndon B. Johnson Space Center (JSC) precompetitive, dual-use technology investment project in robotics. New robotic technology in advanced robots, which can recognize and respond to their environments and to spoken human supervision so as to perform a variety of combined mobility and manipulation tasks in various sectors, is an obejective of this work. In the U.S. economy, such robots offer the benefits of improved global competitiveness in a critical industrial sector; improved productivity by the end users of these robots; a growing robotics industry that produces jobs and profits; lower cost health care delivery with quality improvements; and, as these 'intelligent' robots become acceptable throughout society, an increase in the standard of living for everyone. In space, such robots will provide improved safety, reliability, and productivity as Space Station evolves, and will enable human space exploration (by human/robot teams). The proposed effort consists of partnerships between manufacturers, universities, and JSC to develop working production prototypes of these robots by leveraging current development by both sides. Currently targeted applications are in the manufacturing, health care, services, and construction sectors of the U.S. economy and in the inspection, servicing, maintenance, and repair aspects of space exploration. But the focus is on the generic software architecture and standardized interfaces for custom modules tailored for the various applications allowing end users to customize a robot as PC users customize PC's. Production prototypes would be completed in 5 years under this proposal.
An extensive review of the literature and studies relating to performance, medical, operational, and legal data regarding pilot aging issues was performed in order to determine what evidence there is, if any, to support mandatory pilot retirement. Popular misconceptions about aging, including the failure to distinguish between the normal aging process and disease processes that occur more frequently in older individuals, continue to contribute to much of the misunderstanding and controversy that surround this issue. Results: Review of medical data related to the pilot aging issue indicate that recent improvement in medical diagnostics and treatment technology have made it possible to identify to a high degree individuals who are at risk for developing sudden incapacitating illness and for treating those with disqualifying medical conditions. Performance studies revealed that after controlling for the presence of disease states, older pilots are able to perform as well as younger pilots on many performance tasks. Review of accident data showed that older, healthy pilots do not have higher accident rates than younger pilots, and indeeed, evidence suggests that older pilots have an advantage in the cockpit due to higher experience levels. The Man-Machine-Mission-Environment interface of factors can be managed through structured, supervised, and enhanced operations, maintenance, flight reviews, and safety procedures in order to ensure safe and productive operations by reducing the margin of error and by increasing the margin of safety. Conclusions: There is no evidence indicating any specific age as an arbitrary cut-off point for pilots to perform their fight duties. A combination of regular medical screening, performance evaluation, enhanced operational maintenance, and safety procedures can most effectively ensure a safe pilot population than can a mandatory retirement policy based on arbitrary age restrictions.
In the context of the CNES SPOT4 program CISI is particularly responsible for the development of the SPOT4 Management Centre, part of the SPOT4 ground control system located at CNES Toulouse (France) designed to provide simultaneous control over two satellites. The main operational activities are timed to synchronize with satellite visibilities (ten usable passes per day). The automatic capability of this system is achieved through agenda services (sequence of operations as defined and planned by operator). Therefore, the SPOT4 Management Centre offers limited, efficient and secure human interventions for supervision and decision making. This paper emphasizes the main system characteristics as degree of automation, level of dependability and system parameterization.
A new generation of Mini All-purpose Satellite Control Centers (MASCC) has been developed by CNES (F). They turn out to be easily adaptable to different kinds of satellites, both Low Earth Orbital or Geostationary. The features of MASCC allow both standard satellite control activities, and checking of passengers experiments hosted on a space platform. In the different environments in which it may be used, MASCC provides standard broadcasting of telemetry parameters on animated synoptics (curves, bar graphs, alphanumeric displays, ...), which turns out to be a very useful and ergonomic medium for operational teams or satellite specialists. Special care has been taken during the MASCC development about two points: - automation of all routine tasks, allowing automated operation, and limiting human commitment to system supervision and decision making, - software adaptability. To reach these two main objectives, the MASCC design provides:(1) a simple, robust and flexible hardware architecture, based on powerful distributed workstations; and (2) a table-driven software architecture, easily adapted to various operational needs. Satellite characteristics are described in a central Data Base. Hence, the processing of telemetry and commands is largely independent from the satellite itself. In order to validate these capabilities, the MASCC has been customized to several types of satellites and orbital platforms: (1) SPOT4, the French new generation of remote sensing satellites; (2) TELECOM2, the French geostationary TV and telecommunication satellite; and (3) MIR, the Russian orbital platform. MASCC development has been completed by the third quarter of 1993. This paper will provide first a description of the MASCC basic functions, of its hardware and software design. It will then detail the increased automation capability, along with the easy adaptation of the MASCC to new satellites with minimal software modifications.
Operational deep space navigation has been in the past, and is currently, performed using systems whose architecture requires constant human supervision and intervention. A prototype for a system which allows relatively automated processing of radio metric data received in near real-time from NASA's Deep Space Network (DSN) without any redesign of the existing operational data flow has been developed. This system can allow for more rapid response as well as much reduced staffing to support mission navigation operations.
Since 1964, the National Aeronautics and Space Administration (NASA) has supported a program of summer faculty fellowships for engineering and science educators. In a series of collaborations between NASA research and development centers and nearby universities, engineering faculty members spend 10 weeks working with professional peers on research. The Summer Faculty Program Committee of the American Society for Engineering Education supervises the programs. Objectives: (1) To further the professional knowledge of qualified engineering and science faculty members; (2) To stimulate and exchange ideas between participants and NASA; (3) To enrich and refresh the research and teaching activities of participants' institutions; (4) To contribute to the research objectives of the NASA center.
This study represents the implementation phase of an organizational development project which was initiated last year in the Management Support Division (MSD) at Langley Research Center to diagnose organizational functioning. As a result of MSD survey data from last year's effort, a Quality Action Team was created to address the responses compiled from the MSD Organizational Assessment Questionnaire and Follow-Up Questionnaire. The team was officially named the MSD Employee Relations Improvement Team (MERIT). MERIT's goal was to analyze major concerns generated by the questionnaires and to present feasible solutions to management which would improve supervisory performance, promote process improvement; and ultimately, lead to a better organization. The team met weekly and was very disciplined in following guidelines needed to ensure a fully functioning team. Several TQM tools were used during the team process, including brainstorming and the cause and effect diagram. One of the products produced by MERIT was a 'report card', more formally known as an upward appraisal system, to evaluate supervisory performance in the division office, its three branches, and in teams. Major areas of emphasis on the 47 item report card were those identified by employees through the previously administered questionnaires as needing to be improved; specifically, training, recognition, teamwork, supervision and leadership, and communication. MERIT created an enlarged and modified version of the report card which enabled scores for each individual supervisor to be recorded on a separate form, along with summary results and employee comments. Report card results have been compiled and fed back to the Division Chief and Assistant Division Chief. These individuals will in turn, feed the results back to the remaining supervisors and the team leaders. Although results differ among supervisors, some similarities exist. Communication generally appears to be adequate, which represents an improvement over last year. In contrast, recognition and teamwork are the two major areas where improvement in supervisory performance seems to be most needed. The initial report card results will serve as a baseline against which future performance ratings will be compared. Once supervisors have been presented with their data and given an opportunity to analyze and discus the results, they will be assisted in developing an action plan for improving their performance and work processes. They will be provided with ongoing support from management in following through with the action plan.
DI is short for Distributed Intelligence for Ground/Space Systems and the DI Study is one in a series of ESA projects concerned with the development of new concepts and architectures for future autonomous spacecraft systems. The kick-off of DI was in January 1994 and the planned duration is three years. The background of DI is the desire to design future ground/space systems with a higher degree of autonomy than seen in today's missions. The aim of introducing autonomy in spacecraft systems is to: (1) lift the role of the spacecraft operators from routine work and basic troubleshooting to supervision; (2) ease access to and increase availability of spacecraft resources; (3) carry out basic mission planning for users; (4) enable missions which have not yet been feasible due to eg. propagation delays, insufficient ground station coverage etc.; and (5) possibly reduce mission cost. The study serves to identify the feasibility of using state-of-the-art technologies in the area of planning, scheduling, fault detection using model-based diagnosis and knowledge processing to obtain a higher level of autonomy in ground/space systems.
We address the problem of classifying time series according to their morphological features in the time domain. In a supervised machine-learning framework, we induce a classification procedure from a set of preclassified examples. For each class, we infer a model that captures its morphological features using Bayesian model induction and the minimum message length approach to assign priors. In the performance task, we classify a time series in one of the learned classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. We report results from experiments in a monitoring domain of interest to NASA.