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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： Heping Chen Ning Xi Yifan Chen Electrical and Computer Engineering Department Michigan State University East Lansing MI USA Scientific Research Laboratory Ford Motor Company Limited Dearborn MI USA

ISBN: (纸本)0780378601

Automatic CAD-guided optimal tool planning has many application in surface manufacturing, such as spray painting, spray forming, rapid tooling, cleaning and polishing. A general framework for CAD-guided optimal tool planning is developed to automatically generate optimal trajectories for these tasks. A material distribution model is developed. A multi-objective constraint optimization problem is formulated. An optimal tool trajectory with an optimal time and material quantity deviation is generated. Simulations are performed to verify the generated trajectory. The results show that the developed optimal tool planning algorithm can be applied to generate optimal tool trajectories. This framework can also be extended to other applications.

关键词： Robots Path planning Spraying Painting Constraint optimization robotics and automation computer aided manufacturing Cleaning Trajectory Manufacturing processes

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Activation hebbian learning rule for Fuzzy Cognitive Maps 15th

Activation hebbian learning rule for Fuzzy Cognitive Maps

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15th World Congress of the International Federation of Automatic Control, 2002

作者： Papageorgiou, Elpiniki Stylios, Chrysostomos D. Groumpos, Peter P. Laboratory for Automation and Robotics Department of Electrical and Computer Engineering University of Patras Rion26500 Greece

ISBN: (纸本)9783902661746

Fuzzy Cognitive Maps (FCM) is a soft computing, modeling methodology for complex systems, which is originated from the combination of fuzzy logic and neural networks. Many different learning algorithms have been suggested for the training of neural networks. Only some initial thoughts on learning rules have described for FCMs. A learning law is a mathematical algorithm, which can train the FCM by selecting the appropriate weights and it is very important for a system to have learning and adaptive capabilities. In this paper a new learning algorithm, the Activation Hebbian Learning (AHL) has been proposed for FCMs. The learning rule for a FCM is a procedure where FCM weight matrix is modified in order the FCM to model the behavior of a system. Simulation results proving the strength of the learning rule are provided. Copyright © 2002 IFAC.

关键词： Learning algorithms

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Modeling and control of keyhole ARC welding process 15th

Modeling and control of keyhole ARC welding process

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15th World Congress of the International Federation of Automatic Control, 2002

作者： Zhang, Y.M. Liu, Y.C. Welding Research Laboratory Center for Robotics and Manufacturing Systems Department of Electrical and Computer Engineering College of Engineering University of Kentucky LexingtonKY40506 United States

ISBN: (纸本)9783902661746

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. Copyright © 2002 IFAC.

关键词： Adaptive control systems

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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

关键词： Adaptive control manufacturing processes identification predictive control

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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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Distributed heterogeneous outdoor multi-robot localization

Distributed heterogeneous outdoor multi-robot localization

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IEEE International Conference on robotics and Automation (ICRA)

作者： R. Madhavan K. Fregene L.E. Parker Center for Engineering Science Advanced Research Computer Science and Mathematics Division Oak Ridge National Laboratory Oak Ridge TN USA Department of Electrical and Computer Engineering University of Waterloo Canada

An extended Kalman filter (EKF)-based algorithm for the localization of a team of robots is described in this paper. The distributed EKF localization scheme is straightforward in that the individual robots maintain a pose estimate using EKFs that are local to every robot. We then show how these results can be extended to perform heterogeneous cooperative localization in the absence or degradation of absolute sensors aboard the team members. The proposed algorithms are implemented using field data obtained from a team of ATRV-mini robots traversing on uneven outdoor terrain.

关键词： Robot sensing systems Global Positioning System Centralized control Kalman filters Mobile robots computer science Mathematics Laboratories Electronic mail Degradation

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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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Using Motives and Artificial Emotions for Prolonged Activity of a Group of Autonomous Robots

Using Motives and Artificial Emotions for Prolonged Activity...

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2001 AAAI Fall Symposium

作者： Michaud, François Robichaud, Etienne Audet, Jonathan LABORIUS - Research Laboratory on Mobile Robotics and Intelligent Systems Department of Electrical and Computer Engineering Université de Sherbrooke SherbrookeQCJ1K 2R1 Canada

To operate over a long period of time in the real world, autonomous mobile robots must have the capability of recharging themselves whenever necessary. In addition to be able to find and dock into a charging station, robots must be able to decide when and for how long to recharge. This decision is influenced by the energetic capacity of their batteries and the contingencies of the environment. To deal with this temporality issue and using research evidences from the field of psychology, this study investigates the use of motives and artificial emotions to regulate the recharging need of autonomous robots. © 2001 AI Access Foundation. All rights reserved.

关键词： Robots

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Articulated body posture estimation from multi-camera voxel data

Articulated body posture estimation from multi-camera voxel ...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： I. Mikic M. Trivedi E. Hunter P. Cosman Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of California La Jolla CA USA

ISBN: (纸本)0769512720

We present a framework for articulated body model acquisition and tracking from voxel data. A 3D voxel reconstruction of the person's body is computed from silhouettes extracted from four cameras. The model acquisition process is fully automated. In the first frame, body parts are located sequentially. The head is located first, since its shape and size are unique and stable. Other parts are found by sequential template growing and fitting. This initial estimate of body part locations, sizes and orientations is then used as a measurement for the extended Kalman filter which ensures a valid articulated body model. The same filter, with a slightly modified state and state transition matrix, is then used for tracking. The performance of the system has been evaluated on several video sequences with promising results.

关键词： Cameras Image reconstruction Biological system modeling Data mining computer vision Robot vision systems Head Shape Filters Image segmentation

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