By Topic

Systems, Man and Cybernetics, IEEE Transactions on

Issue 4 • Date Jul/Aug 1989

Filter Results

Displaying Results 1 - 25 of 25
  • Partial simultaneous updating in Hopfield memories

    Page(s): 887 - 888
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (176 KB)  

    A simple generalization of the Hopfield memory is presented. The model proposed updates simultaneously groups of a fixed number of neurons that are disjoint in the sense that each neuron belongs to one and only one group. An analysis is presented of the case in which one of the groups is chosen at random with equal probability and then is updated according to a rule equivalent to the one given by J.J. Hopfield (1982). It is shown that the rule minimizes an energy function in the same way as the original Hopfield model. Sufficient conditions on the corresponding connection matrix as to ensure stability are given View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • New graphics as computerized displays for human information processing

    Page(s): 893 - 898
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (656 KB)  

    A comparative study of various graphic and tabular representations of financial and accounting statistics in an interactive decision setting is presented. Controls are placed on demographic variables, cognitive style, abilities, and math and computer anxiety. Bar graphics are found to be a faster but more accurate form of man-machine communication that tabular presentation of information in credit rating and industry classification decisions. Star graphics take more time on the part of the user but improve the ability to make decisions which involve ranking alternatives. Persons whose cognitive style is more directed toward thinking than feeling have significantly better success in utilizing new graphic forms. It is argues that all new graphics should be tested for speed and efficacy for different types of information display and for people with different cognitive styles and computer backgrounds before they are incorporated into outputs for computerised decision-support systems View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Exploration and dynamic shape estimation by a robotic probe

    Page(s): 840 - 846
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (620 KB)  

    A strategy for motion of a planar manipulator on an unknown surface is presented. To estimate a parameter vector for the surface, least-squares estimators are formulated that use both the kinematic and dynamic data available online. The authors begin with the presentation of a control strategy that uses local sensory data to guide the end effector incrementally over the surface. Force feedback is given, which is later shown to be successful in the uninterrupted maintenance of contact. Motion over the unknown shape is justified by demonstrating that a simple shape estimation algorithm can converge to give a parametric description of the surface. Geometric and differential models of the surface are presented and the estimation procedure is specified. Also presented are the results of a number of computer simulations for a three-link planar manipulator moving over an ellipse whose parameters are unknown to the controller. It is found that, in the presence of noise, dynamic data degrade the estimates View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Adaptive self-calibration of vision-based robot systems

    Page(s): 811 - 824
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1236 KB)  

    An adaptive self-learning process to dynamically and continuously learn the transformation between the camera space and the robot space is discussed. The process is referred to as the adaptive self-calibration of hand-eye systems in which a visual-feedback-based self-learning process is used for dynamically and continuously learning the hand-eye transformation through repetitive operation trials. The hand-eye system calibration is used in situ and in real time while the system is operating. Recursive real-time implementation using adaptive and square-root Kalman filtering techniques is described and recent related research is reviewed. An experimental stereo-vision-based hand-eye system is described. Both simulation and experimental results are presented View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Model-based object recognition using a large-field passive tactile sensor

    Page(s): 846 - 853
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (896 KB)  

    The results of a model-driven touch sensor recognition experiment are reported. The touch sensor used is a large-field tactile array. Object features appropriate for touch sensor recognition are extracted from a geometric model of an object, and a dual spherical image is formed. Both geometric and dynamic features are used to identify objects and their position and orientation on the touch sensor. Experiments show that geometric features extracted from the model are effective but that dynamic features must be determined empirically. Correct object identification rates, even for very similar objects, exceed 90%, a success rate much higher than would have been expected from only two-dimensional contact patterns. The position and orientation of objects, once identified, are very reliable. The authors conclude that large-field tactile sensors could prove useful in the automatic palletizing problem when object models (from a computer-aided design system, for example) can be utilized View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Issues in low-dimensional sensing and feedback [in robot grippers]

    Page(s): 832 - 839
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (796 KB)  

    A discussion is presented of problems of multisensory integration and feedback in a robot gripper. Various contact and noncontact sensors are described and it is shown how a number of such `low-dimensional' sensors are integrable in an advanced robot gripper. The resulting gripper uses only a few data and power supply connections out of the wrist. Feedback structures are outlined with the main emphasis on different alternatives in force-torque feedback; the various approaches proposed in the literature are considered in more detail. The problem of sensor data fusion, including the redundancy problem, is briefly explained View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Some discussion of static gripping and its stability

    Page(s): 783 - 796
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1296 KB)  

    An overview is presented of research done in the area of dextrous manipulation. The main issue has been how to control mechanical hands so that they can perform manipulation task with the same dexterity and sensitivity as the human hands. To achieve sophisticated algorithms for grasping, compliance control, and manipulation, the nature of the contact wrenches, twists, and compliance of the fingers have to be well understood. Here emphasis is on the area of dextrous manipulation encompassed by static grasping. The two main approaches to the problems of grasping reviewed are those motivated by a study of human hands and those motivated by the physical and mechanical properties of grasps such as contact types, number of fingers required to achieve grasp, equilibrium, stability and compliance View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • The likelihood ratio test for goodness of fit with fuzzy experimental observations

    Page(s): 771 - 779
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (804 KB)  

    Experiments are considered in which the person responsible for observation cannot crisply perceive the outcomes, but where each observable event can be identified with a fuzzy subset of the sample space. It is explained that in such a situation, the likelihood ratio test can immediately be derived for goodness of fit to a completely specified hypothetical distribution regarding the `exact experiment' on the basis of fuzzy information. On the other hand, if the hypothetical distribution involves unknown parameters the extension of the likelihood ratio test usually becomes unmanageable, because of the unoperativeness of the trivial generalization of the maximum likelihood principle to fuzzy observations. This last generalization is suitably approximated by means of the minimum inaccuracy principle of point estimation (introduced in previous papers as an operative extension of the maximum likelihood one, on the basis of the inaccuracy measure defined by D.F. Kerridge in 1961) whose use for the likelihood-ratio test for goodness of fit with fuzzy data provides a manageable procedure View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Alternative implementations of Prolog: the microarchitecture perspective

    Page(s): 693 - 698
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (572 KB)  

    An area that should provide opportunities for obtaining improvements in the performance of Prolog programming is explored: the microarchitecture of the uniprocessor engine. Alternative execution models are examined for a uniprocessor microengine, and their performance is measured on 14 separate benchmark programs; the resulting data is presented and analyzed. The author also examines the program size explosion that results from compiling directly to a low-level instrument assembly. The characteristics of an optimal microarchitecture are identified and opportunities for further improvement at the microengine level are discussed View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Classification quality assessment for a generalized model-based object identification system

    Page(s): 861 - 866
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (660 KB)  

    An object recognition system based on global features and nearest neighbor matching is extended and enhanced using classification quality assessment methodology. For quality assessment, a classification decision is processed at two levels. The first is to reject options that are not contained in the model database. The second is to identify the likelihood of error for classifications of known objects. Both stages are based on empirically determined thresholds of measures that are generated solely from the system's a priori knowledge, exploiting the known characteristics of both physical object space and feature space. Results are presented for a standardized object identification task, with a set of six similar known objects, and four unknown objects. It is shown that objects outside the model database are effectively rejected and that the accuracy of known object identifications is increased by rejecting views of low classification quality View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A model-based aid for monitoring and controlling a large-scale system

    Page(s): 888 - 892
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (576 KB)  

    Approaches to aiding human performance in monitoring and controlling a large-scale system are considered. One particular approach that is based on a model of human performance is described in detail. The model includes a rule-based representation of procedural knowledge, a frame-based representation of declarative knowledge, and a fuzzy prioritization mechanism to handle rule of conflicts. The online aiding approach is implemented in a simulated large-scale system that requires human monitoring and control. Results from an experimental evaluation of the aid are inconclusive in that they do not demonstrate the benefit of a direct advice-giving system; however, the aiding approach was found helpful in some tasks View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A dynamic approach to high-precision parts mating

    Page(s): 797 - 810
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1328 KB)  

    A method for the mating of tightly fitting parts in the presence of significant sensing, model, and control uncertainties is presented. Using this method randomly placed parts that were located using a three-dimensional laser range scanning system can be mated even when the clearance between them is only 0.001 in. The various sources of error introduced in the fine forced-guided motions used to execute assemblies are examined. Among these sources are noisy force/torque readings, mechanical vibrations, the presence of sliding and sticking frictions, and the possibility of eccentric oblique impacts. It is pointed out how most of these errors might be reduced or eliminated. Straight-line motion goals (SLMGs) are then processed by the basic building blocks of a dynamic planning strategy. By dynamically building an assembly plan out of SLMGs, it is possible to carry out robotic assemblies in the presence of sensing and model uncertainties while recognizing and recovering from errors introduced by control uncertainties. A specific instance of this approach is outlined View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Reasoning with imprecise knowledge to enhance intelligent decision support

    Page(s): 756 - 770
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1552 KB)  

    Decisionmakers often have to deal with knowledge that is both unstructured and imprecise in nature. Lack of structure forces the use of heuristic programming and artificial intelligence methods in automated decision support systems for such problems. At the same time, the knowledge representation and manipulation methods used should be able to include imprecise knowledge, where imprecision may be caused by uncertainty and/or fuzziness. The authors use their previously developed methodology (see Decision Support Syst. vol.2, no.3, 1986 and vol.2, no.4, 1986) for using imprecise reasoning in decision support systems to describe a prototype system based on this methodology. The system's behavior is examined using a set of sample problems. The knowledge representation mechanisms used are shown to have significant expressive power and facilitate the knowledge of engineering process through greater flexibility in the representation and use of imprecise knowledge. The system is able to provide additional information to the user that cannot readily be provided in systems limited to precise reasoning View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • RIPS: a platform for experimental real-time sensory-based robot control

    Page(s): 853 - 860
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (816 KB)  

    The design and performance benchmarking of the prototype robotic instruction processing systems (RIPS) at the Center for Robotic Systems in Microelectronics at the University of California-Santa Barbara, is discussed. The architecture of RIPS is specifically geared for robot control, yet the system is general and fully programmable and does not assume any manipulator characteristics. RIPS provides sufficient computing capacity to attack important real-time sensory-based robot control problems. Compliant control, multiple manipulator coordination, and manufacturing cell-level integration are presently under study. Experimental testing in these areas is possible because of RIPS' high computational performance for robot control problems: a Stanford manipulator using the computed torque method can be controlled with an update time of 255 μs. This time includes inverse kinematics, dynamic compensation, and proportional derivative servoing for the six-degrees-of-freedom manipulator View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A survey on the design of multiprocessing systems for artificial intelligence applications

    Page(s): 667 - 692
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3024 KB)  

    Some issues in designing computers for artificial intelligence (AI) processing are discussed. These issues are divided into three levels: the representation level, the control level, and the processor level. The representation level deals with the knowledge and methods used to solve the problem and the means to represent it. The control level is concerned with the detection of dependencies and parallelism in the algorithmic and program representations of the problem, and with the synchronization and scheduling of concurrent tasks. The processor level addresses the hardware and architectural components needed to evaluate the algorithmic and program representations. Solutions for the problems of each level are illustrated by a number of representative systems. Design decisions in existing projects on AI computers are classed into top-down, bottom-up, and middle-out approaches View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Real-time application of neural networks for sensor-based control of robots with vision

    Page(s): 825 - 831
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (916 KB)  

    A practical neural network-based learning control system is described that is applicable to complex robotic systems involving multiple feedback sensors and multiple command variables. In the controller, one network is used to learn to reproduce the nonlinear relationship between the sensor outputs and the system command variables over particular regions of the system state space. The learned information is used to predict the command signals required to produce desired changes in the sensor outputs. A second network is used to learn to reproduce the nonlinear relationship between the system command variables and the changes in the video sensor outputs. The learned information from this network is then used to predict the next set of video parameters, effectively compensating for the image processing delays. The results of learning experiments using a General Electric P-5 manipulator are presented. These experiments involved control of the position and orientation of an object in the field of view of a video camera mounted on the end of the robot arm, using moving objects with arbitrary orientation relative to the robot. No a priori knowledge of the robot kinematics or of the object speed of orientation relative to the robot was assumed. Image parameter uncertainty and control system tracking error in the video image were found to converge to low values within a few trials View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A gray-level threshold selection method based on maximum entropy principle

    Page(s): 866 - 871
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (536 KB)  

    A description is given of a gray-level threshold selection method for image segmentation that is based on the maximum entropy principle. The optimal threshold value is determined by maximizing the a posteriori entropy subject to certain inequality constraints which are derived by means of spectral measures characterizing uniformity and the shape of the regions in the image. For this purpose, the authors use both the gray-level distribution and the spatial information of an image. The effectiveness of the method is demonstrated by its performance on some real-world images. An extension of this method to chromatic images is provided View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A description of the dynamic behavior of fuzzy systems

    Page(s): 745 - 755
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (920 KB)  

    An approach is presented for analyzing the global behavior of a fuzzy dynamical system that applies the concept and method of cell-to-cell mapping to obtain the evolving trend of the states of a fuzzy dynamical system. The behavior of the fuzzy system is characterized by equilibria, periodic motions, and their domain of attractions. Min-max operation accumulates the fuzziness of a fuzzy system in every step of iterations and makes the state evolution obscure. The proposed method transforms a given fuzzy mapping to at Z-to-Z mapping and does not accumulate fuzziness. Both the real and fuzzy initial state response analyses are discussed. An inverted pendulum controlled by a fuzzy controller is analyzed to illustrate the validity of the method View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • The Connection Machine model CM-1 architecture

    Page(s): 707 - 713
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (612 KB)  

    An examination is presented of the performance of the Connection Machine model CM-1 system, a general-purpose computer capable of adapting to many sizes and types of data sets. An overview of the hardware and software systems is provided and a simple application is presented from which the raw performance of the machine is examined. This illustrates the power of data-level parallelism and indicates how CM-1 performance is enhanced by the use of virtual processors and variable word size. The CM-1 system consists of a 64000 processor array, from one to four front-end computers, and high-speed peripherals such as disks and image devices View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Processing fuzzy temporal knowledge

    Page(s): 729 - 744
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1460 KB)  

    L.A. Zadeh's (1975) possibility theory is used as a general framework for modeling temporal knowledge pervaded with imprecision or uncertainty. Ill-known dates, time intervals with fuzzy boundaries, fuzzy durations, and uncertain precedence relations between events can be dealt with in this approach. An explicit representation (in terms of possibility distributions) of the available information, which may be neither precise nor certain, is maintained. Deductive patterns of reasoning involving fuzzy and/or uncertain temporal knowledge are established, and the combination of fuzzy partial pieces of information is considered. A scheduled example with fuzzy temporal windows is discussed View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A flexible method for nonlinear multicriteria decision-making problems

    Page(s): 883 - 887
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (556 KB)  

    An iterative and interactive approach to formulating and solving multicriteria decision-making problems is proposed in which the modeling and the solution phases are not strictly separated but overlap. At each iteration, the decision-maker is allowed to designate criterion functions as objective functions or as constraints or as something in between. The algorithm guarantees all intermediate solutions to be efficient and the final solution to be a most preferred solution. While the algorithm does not provide information about the marginal rates of substitution among the objective functions at a solution point as given by other methods, the marginal substitution rates are obtained by comparing two objectives at a time. The algorithm can also be used to solve linear multicriteria decision-making problems. However, since the surrogate function is nonlinear, the procedure introduces nonlinearities into the problems and may not be as computationally efficient as some of the other available algorithms. The algorithm is illustrated using a specific problem in water resources management View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • RUBIC: a multiprocessor for rule-based systems

    Page(s): 699 - 706
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (604 KB)  

    It is shown how sequential production systems can be transformed into equivalent parallel forms by performing an analysis of rule interdependence. In the parallel production system model, rules fire simultaneously and the search space is reduced from the original form. A multiprocessor called RUBIC (rule-based inference computer) was designed to implement the parallel processing model. RUBIC has a message-passing architecture. The partitioning and mapping of production systems into the multiprocessor is achieved by optimizing a performance index such that inherent parallelism is maximized and interprocessor communication is minimized View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Joint recognition and tracking for robotic arc welding

    Page(s): 714 - 728
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1272 KB)  

    An automatic joint guidance system was developed as part of a project to develop an expert welding robot. The apparatus consists of a servo-robot laser scanner mounted on a conventional CLOOS model ROMAT 75/76 industrial welding robot. The computer vision system is able to recognize and track the joint to be welded without external information by using range data obtained from scanning the workpiece. An approach and some experiments related to achieving this ultimate goal are discussed. Three different joint types are identified. Tracking of the joint geometry is done by building, online, a three-dimensional model of the joint during the welding process. This approach is attractive because of its complete autonomy for joint recognition and its ability to trace the geometry while at the same time avoiding an elaborate teaching pass prior to the process. The algorithms used have been tested in a simulation using real laser data. The results indicate that it is possible to recognize automatically the joint type and then to track the joint during the process of welding View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Segmentation between overlapping parts: the moving shadows approach

    Page(s): 880 - 883
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (480 KB)  

    A method for segmenting three-dimensional overlapping surfaces is presented that is based on moving a light source in a horizontal plane relative to the surfaces to be segmented. Using a camera that is placed above the surfaces. The shadows cast by the surfaces at each light source angle are recorded and analyzed. The segmentation algorithm is simple and based on Boolean processing of the data. A set of experimental results demonstrates the robustness and usefulness of the method View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • New sensing strategies for monitoring moving polyhedral objects by machine vision

    Page(s): 872 - 880
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1012 KB)  

    A set of sensing strategies is proposed for monitoring three-dimensional moving objects by computer vision. Three-dimensional (3-D) object surface points are selected as the features for monitoring 3-D moving objects because the point features are easy to detects, extract, store, and manipulate. It is proved that the minimum measurable feature point set for monitoring a 3-D moving convex polyhedral object is exactly the set containing all the junction points of the objects. Based on the sampling theorem and several properties of photogrammetry it is proved that the minimum data-acquisition rate of a vision system monitoring 3-D moving objects can be determined with discretely sampled two-dimensional image sequence data alone. Certain properties of orthographic projection useful for determining the minimum number of sensors needed Ns to monitor 3-D moving convex polyhedral objects are investigated, and the bound on Ns are also derived. An algorithm for determining Ns and the corresponding directions of the sensors is proposed. The feasibility of the proposed algorithm is shown by three illustrative examples and an application example View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.