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Affecting the accuracy of an active vision head 2nd

2nd Hellenic Conference on Artificial Intelligence, SETN 2002

作者： Gasteratos, Antonios Sandini, Giulio Laboratory of Electronics Section of Electronics and Information Systems Technology Department of Electrical and Computer Engineering Democritus University of Thrace XanthiGR-671 00 Greece Laboratory for Integrated Advanced Robotics Department of Communication Computer and System Sciences University of Genoa Viale Causa 13 GenoaI-16145 Italy

ISBN: (纸本)3540434720

In any measuring system the categorization of the error generation factors leads to simplification of complex error problems and to higher suppression of the error. In this paper we categorize, quantify and analyze the errors that affect a binocular active vision head. Simulations have been made and experimental results on a high resolution pan-tilt-vergence mechanism are also proposed. As a conclusion it can be said that the system performs optimal when it is initialized so that the two cameras are perfectly aligned and perpendicular to the baseline. Small variations in the vergence angle or small horizontal deviations of the principal point alters the measurement dramatically. On the other hand, variations in pan and tilt and vertical deviations of the principal point, affect the measurement insignificantly. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Errors

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MODELING AND control OF KEYHOLE ARC WELDING PROCESS

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IFAC Proceedings Volumes 2002年第1期35卷 151-156页

作者： Y.M. Zhang Y.C. Liu Welding Research Laboratory Center for Robotics and Manufacturing Systems and Department of Electrical and Computer Engineering College of Engineering University of Kentucky Lexington KY 40506 USA

This paper addresses the development of an adaptive control system for keyhole arc welding process. The system developed adjusts the amperage of the peak current to achieve the desired peak current period under varying manufacturing conditions. A nominal model is selected from models identified using experimental data and is used as the a prior model of the controlled process. A predictive control algorithm has been designed for the nominal model structure. Closed-loop control experiments have been conducted to verify the effectiveness of the developed system under varying set-point and varying travel speed.

关键词： Adaptive control manufacturing processes identification predictive control

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Triangle mesh-based edge detection and its application to surface segmentation and adaptive surface smoothing

Triangle mesh-based edge detection and its application to su...

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IEEE International Conference on Image Processing

作者： Y. Sun D.L. Page J.K. Paik A. Koschan M.A. Abidi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville USA

Triangle meshes are widely used in representing surfaces in computer vision and computer graphics. Although 2D image processing-based edge detection techniques have been popular in many application areas, they are not well developed for surfaces represented by triangle meshes. This paper proposes a robust edge detection algorithm for triangle meshes and its applications to surface segmentation and adaptive surface smoothing. The proposed edge detection technique is based on eigen analysis of the surface normal vector field in a geodesic window. To compute the edge strength of a certain vertex, the neighboring vertices in a specified geodesic distance are involved. Edge information are used further to segment the surfaces with the watershed algorithm and to achieve edge-preserved, adaptive surface smoothing. The proposed algorithm is novel in robustly detecting edges on triangle meshes against noise. The 3D watershed algorithm is an extension from previous work. Experimental results on surfaces reconstructed from multi-view real range images are presented.

关键词： Image edge detection Smoothing methods Application software Image segmentation Surface reconstruction computer vision computer graphics Geophysics computing Noise robustness Image reconstruction

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Permanent magnet stepper motor control via position-only feedback

Permanent magnet stepper motor control via position-only fee...

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American control Conference (ACC)

作者： P. Krishnamurthy F. Khorrami Control/Robotics Research Laboratory(CRRL) Department of Electrical and Computer Engineering Polytechnic University Brooklyn NY USA

In this paper, a robust nonlinear dynamic controller is designed to achieve global practical stabilization for position tracking error of a voltage-fed permanent-magnet stepper motor. The control design is an output-feedback design that utilizes only rotor position measurement. Rotor velocity and stator phase currents are not available for feedback. Furthermore, only upper and lower bounds are required for the electromechanical parameters of the motor. The proposed controller is robust to load torques, friction, cogging forces, and other disturbances satisfying certain bounds. These results can also be extended to other classes of motors.

关键词： Motor drives Feedback Robust control Rotors Voltage control Error correction Permanent magnet motors control design Position measurement Stators

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Generalized adaptive output-feedback form with unknown parameters multiplying high output relative-degree states

Generalized adaptive output-feedback form with unknown param...

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IEEE Conference on Decision and control

作者： P. Krishnamurthy F. Khorrami Control/Robotics Research Laboratory Department of Electrical and Computer Engineering Six Metrotech Center Polytechnic University Brooklyn NY USA

We propose a global high-gain scaling based observer/controller for systems in the uncertain generalized output-feedback canonical form. Time-varying nonlinear parametric uncertainty is allowed to occur coupled with unmeasured states in the system dynamics. This represents a significant generalization from existing results which allow unknown parameters only in output-dependent terms. This restriction in previous results is mainly owing to the fact that no general solution is known for systems involving bilinear terms in unmeasured states. The design utilizes the dual architecture of a high-gain observer and controller with the underlying state scaling being dynamically output-dependent. The proposed observer/controller structure provides a globally asymptotically stabilizing output-feedback solution for the benchmark open problem proposed in our earlier work with the provision that a magnitude bound on the unknown parameter be given.

关键词： Riccati equations control systems Linear matrix inequalities Differential equations Robot control Laboratories Ear Uncertainty Lyapunov method Linear systems

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Entire region filling in indoor environments using neural networks

Entire region filling in indoor environments using neural ne...

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World Congress on Intelligent control and Automation (WCICA)

作者： Chaomin Luo S.X. Yang M. Meng Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph Canada Department of Electrical and Computer Engineering University of Alberta Edmonton Canada

Entire region filling is a special type of robot path planning strategy that requires the mobile robot to cover every part of the whole workspace, which has many applications such as cleaning robots, vacuum cleaners, painter robots, land mine detectors, lawn mowers, and window cleaners. In this paper, a novel biologically inspired neural network approach is proposed for entire region filling with obstacle avoidance of a mobile cleaning robot in a nonstationary environment. The dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation or an additive equation derived from Hodgkin and Huxley's (1952) membrane equation. There are only local lateral connections among neurons. Thus the computational complexity linearly depends on the neural network size. The robot path is autonomously generated from the dynamic activity landscape of the neural network and the previous robot location. The proposed model algorithm is computationally efficient. It can deal with an unstructured environment with irregular obstacles. The effectiveness of the proposed model is demonstrated by simulation results.

关键词： Filling Indoor environments Neural networks Mobile robots Equations Cleaning Landmine detection Neurons Computational modeling Path planning

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An extension of weighted strategy sharing in cooperative Q-learning for specialized agents

An extension of weighted strategy sharing in cooperative Q-l...

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International Conference on Neural Information Processing

作者： S.M. Eshgh M.N. Ahmadabadi School of Intelligent Systems Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence and Robotics Laboratory Department of Electrical and Computer Engineering University of Tehran Tehran Iran

Using other agents' experiences and knowledge, a learning agent may learn faster, make fewer mistakes, and create some rides for unseen situations. These benefits will be gained if the learning agents know the area of expertise and the expertness values of each other. In this paper, some Q-learning agents with different skills and expertness levels cooperate in learning. The agents use some criteria to judge others information and knowledge. Four expertness criterion, certainty and entropy measures are used to assign degrees of importance to others' Q-Tables. Effects of measuring these values based on their whole Q-Table, a portion of Q-Tables that reflects their proficiencies, and the states in Q-Tables on the learning quality are studied. Simple strategy sharing and two different weighted strategy-sharing methods are used to combine the acquired knowledge from different agents.

关键词： Intelligent robots Intelligent agent Process control control systems Intelligent control Laboratories Intelligent systems Physics Mathematics Entropy

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ROBUST CONGESTION control IN HIGH SPEED COMMUNICATION NETWORKS: A MODEL PREDICTIVE control APPROACH

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IFAC Proceedings Volumes 2002年第1期35卷 103-108页

作者： Hua O. Wang Yongru Gu Huajing Fang Laboratory for Intelligent and Nonlinear Control (LINC) Department of Electrical and Computer Engineering Duke University Durham NC 27708-0291 USA Center for Nonlinear and Complex Systems Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

In this paper, the design of explicit rate-based congestion control in high speed communication networks is considered. At a bottleneck node, there are multiple best-effort sources competing with other high priority cross traffic sources. The goal of congestion control is to achieve high link utilization, low packet loss, low delay, and fairness among the best-effort sources. In this paper, the high priority traffic is described by an autoregressive integrated moving average (ARIMA) process. To deal with the propagation delays associated with the best-effort sources, model predictive control, particularly, generalized predictive control, techniques are proposed to solve the congestion problem here. It is demonstrated that the proposed controller performs well and is robust to delay uncertainties. In addition, in a multiple-nodes configuration, the controller provides max-min fairness.

关键词： Communication control applications Model-based control Predictive control Communication networks Time delay Robustness

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Certainty and expertness-based credit assignment for cooperative Q-Learning agents with an AND-type task

Certainty and expertness-based credit assignment for coopera...

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International Conference on Neural Information Processing

作者： A. Harati M.N. Ahmadabadi School of Intelligent Systems Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence & AI and Robotics Laboratory Department of Electrical and Computer Engineering University of Tehran Tehran Iran

In multiagent reinforcement learning, inter-agent credit assignment is a fundamental problem, since a single scalar reinforcement signal is the only reliable feedback that teams of learning agents receive. This problem is more critical in groups of independent learners with a joint task. In this research, it is assumed that a critic agent receives the environment feedback and assigns a proper credit to each agent using some measures. Three of such measures for a team of cooperative agents with a parallel and AND-type task are introduced. These measures somehow compare the agents' knowledge. One of these criteria, called normal expertness, is a non-relative measure while two other ones (certainty and relative normal expertness) are relative measure. It is experimentally shown that relative measures work better as they contain more information for the critic agent.

关键词： Feedback Intelligent agent Intelligent robots Process control control systems Intelligent control Artificial intelligence Robot kinematics Physics computing Reliability engineering

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Cooperative Q-learning with heterogeneity in actions

Cooperative Q-learning with heterogeneity in actions

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IEEE International Conference on systems, Man and Cybernetics

作者： S.M. Reza MirFattah M.N. Ahmadabadi Institute for Studies on Theoretical Physics and Mathematics School of Intelligent Systems Tehran Iran Robotics and AI Laboratory Department of Electrical and Computer Engineering University of Tehran Tehran Iran

Cooperation in learning improves the speed of convergence and the quality of learning. Special care is needed when heterogeneous agents cooperate in learning. It is discussed that, cooperation in learning may cause the learning process to diverge if heterogeneity is not handled properly. In this paper, it is assumed that two heterogeneous Q-learning agents cooperate to learn. The heterogeneity is assumed in their action order (and not in their action set). A Q-learning-based method is introduced for the agents to learn the mapping among their actions. It is shown that, the agents are able to learn this mapping while cooperating in learning. Some simulation results are reported to show the effectiveness of the proposed method.

关键词： Intelligent agent Intelligent robots Humans Telecommunication control Artificial intelligence Laboratories Intelligent systems Physics Mathematics Convergence

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