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International Conference on computer Integrated Manufacturing

作者： S. Lee Y.G. Shin Department of Electrical Engineering-Systems Institute for Robotics and Intelligent Systems University of Southern California Los Angeles CA USA Computer Science Department University of Southern California Los Angeles CA USA

A system is presented which automatically constructs an assembly partial-order graph from an object-oriented model describing parts and their connections. The construction is based on the principle of assembly by disassembly and on assembly heuristics representing criteria for preferred subassemblies. The system first identifies disassemblable parts and subassemblies by reasoning geometric and physical constraints as well as resource requirements, and then assigns preference to the identified disassembly options based on assembly heuristics. The recursive application of this process to the selected disassemblies results in a hierarchical partial-order graph (HPOG). The HPOG not only specifies the required precedence in part assembly but also provides parallelism for implementing multiple-robot distributed and cooperative assembly. The software is organized under the cooperative-problem-solving paradigm.< >

关键词： Robotic assembly Assembly systems robotics and automation Process planning Job shop scheduling Robot sensing systems intelligent robots Throughput Parallel robots Motion planning

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Learning expert systems for robot fine motion control

Learning expert systems for robot fine motion control

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IEEE International Symposium on intelligent Control (ISIC)

作者： S. Lee M.H. Kim Department of Electrical Engineering-Systems Institute for Robotics and Intelligent Systems University of Southern California Los Angeles CA USA Computer Science Department Sung Kyun Kwan University Seoul South Korea

The authors present a learning expert system which enables a robot to acquire fine motion skills automatically. The system follows the paradigm of Expert Assisted Robot Skill Acquisition (EARSA) proposed by the authors (1987). EARSA is mainly concerned with the self-discovery of skills by a robot in conjunction with the transfer of human skills to a robot and emphasizes the distinctive difference in perceptual and physical capabilities between a human and a robot. The authors review the theory and mechanism of EARSA, describe the robot fine motion skill learning algorithm formulated on the basis of EARSA, and present the details of simulation on the robot learning of two-dimensional peg-hole insertion skills. The results of simulation indicate the dramatic improvement of performance as a result of skill learning.< >

关键词： Expert systems Motion control robotics and automation Robot sensing systems intelligent robots Cognitive robotics Motion planning Robotic assembly Automatic control Humans

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Approaches on multi-sensor fusion under time-evolving conditions

Approaches on multi-sensor fusion under time-evolving condit...

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IEEE International Symposium on intelligent Control (ISIC)

作者： R.C. Luo W.S. Yang M.-H. Lin Robotics and Intelligent Systems Laboratory Electrical and Computer Engineering Department North Carolina State University Raleigh NC USA Dept. of Electr. & Comput. Eng. North Carolina State Univ. Raleigh NC USA

A paradigm for optimum estimation of fused multiple sensor data is developed in order to best use the sensor information in the time evolving environment. Two basic approaches have been developed: dynamic moving quadratic curve fitting and weighted least mean square error. These two approaches are shown to be advantageous in terms of accuracy, speed, and versatility. The theoretical frameworks presented are supported by sets of simulation data.< >

关键词： Sensor fusion Robot sensing systems intelligent robots intelligent sensors Sensor systems Uncertainty Military aircraft Machine intelligence Mobile robots Sensor phenomena and characterization

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Expert self-learning controller for robot manipulator

Expert self-learning controller for robot manipulator

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IEEE Conference on Decision and Control

作者： Z. Geng M. Jamshidi Department of Electrical Engineering and Computer Science George Washington University Washington D.C. DC USA CAD Laboratory of Systems / Robotics Department of ECE University of New Mexico Albuquerque NM USA

Real-time expert system techniques and applications to robot manipulator control systems are discussed. A novel type of intelligent controller structure, the expert learning controller prototype ELEC (expert learning controller), is developed for the trajectory tracking control in repeat operations. ELEC, acting as an intelligent real-time controller in a closed-loop system, can modify the control series in a human-expert-like manner using the experience of previous operations in order to force the system output to converge to the prespecified desired trajectory. ELEC does not require the knowledge of system models, so it can be used in a fairly wide range of control problems. A numerical example for a two-link robot manipulator is given which shows the satisfactory performance of ELEC.< >

关键词： Robot control Manipulators Control systems Real time systems intelligent robots Force control Expert systems intelligent structures Prototypes Trajectory

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Refining edges detected by a LoG operator

Refining edges detected by a LoG operator

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： F. Ulupinar G. Medioni Dept. of Electr. Eng. & Comput. Sci. Univ. of Southern California Los Angeles CA USA Institute for Robotics and Intelligent Systems Department of Electrical Engineering and Computer Science University of Southern California Los Angeles CA USA

The Laplacian of Gaussian (LoG) operator is one of the most popular operators used in edge detection. This operator, however, has some problems: zero-crossings do not always correspond to edges, and edges with an asymmetric profile introduce a symmetric bias between edge and zero-crossing locations. The authors offer solutions to these two problems. First, for one-dimensional signals, such as slices from images, they propose a simple test to detect true edges, and, for the problem of bias, they propose different techniques: the first one combines the results of the convolution of two LoG operators of different deviations, whereas the others sample the convolution with a single LoG filter at two points besides the zero-crossing. In addition to localization, these methods allow them to further characterize the shape of the edge. The authors present an implementation of these techniques for edges in 2-D images.< >

关键词： Image edge detection Laplace equations Detectors intelligent robots Convolution Shape intelligent systems Testing Filters Image segmentation

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Decentralized adaptive control (robot)

Decentralized adaptive control (robot)

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IEEE International Conference on robotics and Automation (ICRA)

作者： B.J. Oh M. Jamshidi H. Seraji CAD Laboratory for Systems/Robotics Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA Dept. of Electr. & Comput. Eng. New Mexico Univ. Albuquerque NM USA Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA

A decentralized adaptive control is proposed to stabilize and track the nonlinear interconnected subsystems with unknown parameters. The adaptation of the controller gain is derived by using model reference adaptive control theory based on Lyapunov's direct method. The adaptive gains consist of sigma , proportional, and integral combination of the measured and reference values of the corresponding subsystem. The proposed control is applied to the joint control of a two-link robot manipulator, and the performance in computer simulation corresponds with what is expected in theoretical development.< >

关键词： Adaptive control Control systems Programmable control Laboratories Manipulators Robot sensing systems Nonlinear control systems Couplings Robust control Propulsion

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Segmented Descriptions of 3-D Surfaces

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IEEE Journal on robotics and Automation 1987年第6期3卷 527-538页

作者： Fan, Ting-Jun Medioni, Gerard Nevatia, Ramakant Institute for Robotics and Intelligent Systems Departments of Electrical Engineering and Computer Science University of Southern California Los Angeles MC0273 CA 90089-0273 United States

A method to segment and describe visible surfaces of three-dimensional (3-D) objects is presented by first segmenting the surfaces into simple surface patches and then using these patches and their boundaries to describe the 3-D surfaces. First, distinguished points are extracted which will comprise the edges of segmented surface patches, using the zero-crossings and extrema of curvature along a given direction. Two different methods are used: if the sensor provides relatively noise-free range images, the principal curvatures are computed at only one resolution, otherwise, a multiple scale approach is used and curvature is computed in four directions 45° apart to facilitate interscale tracking. These points are then grouped into curves and these curves are classified into different classes which correspond to significant physical properties such as jump boundaries, folds, and ridge lines (or smooth extrema). Then jump boundaries and folds are used to segment the surfaces into surface patches, and a simple surface is fitted to each patch to reconstruct the original objects. These descriptions not only make explicit most of the salient properties present in the original input, but are more suited to further processing, such as matching with a given model. The generality and robustness of this approach is illustrated on scene images with different available range sensors. Copyright © 1987 by The Institute of electrical and Electronics Engineers, Inc.

关键词： Object recognition Engine cylinders Surface reconstruction Image sensors intelligent robots Image segmentation Image resolution Image reconstruction Robustness Layout

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Near-Optimum Control of a Robot Manipulator

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IFAC Proceedings Volumes 1987年第5期20卷 271-275页

作者： M. Jamshidi Y.T. Kim M. Shahinpoor CAD Laboratory for Systems/Robotics Electrical & Computer Engineering Department University of New Mexico Aluquerque NM 87131 USA Departmental of Mechanical Engineering University of New Mexico Aluquerque NM 87131 USA

This paper proposes a near-optimum control algorithm for a highly nonlinear robot manipulator model via a parameter sensitivity method. The method uses Pontrvagin's maximum principle and the Riccati formulation of the linear state regulator problem. The effectiveness of the proposed method is verified by simulation results for a two-link planar robot.

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Fixed mode elimination with minimum information exchange among controllers

Fixed mode elimination with minimum information exchange amo...

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IEEE Conference on Decision and Control

作者： M. Tarokh M. Jamshidi CAD Laboratory Systems/Robotics Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

The paper proposes a frequency-domain approach to the problem of fixed mode elimination in decentralized systems. systems having distinct or repeated fixed modes are considered and decentralized controllers requiring ... 详细信息

关键词： Control systems Distributed control Polynomials Laboratories Robots Feedback Displacement control Frequency Equations

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Vertical integration for robot assembly cells

Vertical integration for robot assembly cells

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IEEE International Conference on robotics and Automation (ICRA)

作者： R. Kelley Robotics and Automation Laboratory Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY USA

Vertical integration of transformation of abstract assembly task descriptions into task execution commands is needed to overcome the fundamental factors which limit the widespread application of current robotic systems. These factors are the requirements for precise control of the robot task environment, custom-designed fixtures and end-effectors, and on-site robot control programming. These requirements arise because current robotic systems do not have an understanding of the robot cell environment. Further, these systems are not able to react rationally to non-deterministic events which occur during task execution. A research plan which is aimed at the systematic incorporation of limited amounts of machine intelligence into robot task planning and execution is outlined.

关键词： Robotic assembly Robot kinematics robotics and automation Robot sensing systems Robot programming Machine intelligence Service robots intelligent robots Assembly systems Robot control

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