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Fuzzy classification of plasma reflection for keyhole sensing and control

Fuzzy classification of plasma reflection for keyhole sensin...

引用

IEEE Conference on Control Technology and Applications (CCTA)

作者： B.E. Losch YuMing Zhang Department of Electrical and Computer Engineering and Center for Robotics and Manufacturing Systems University of Kentucky Lexington KY USA

Keyhole arc welding (KAW) can achieve deeper, narrower penetration than other arc welding processes. If KAW can be controlled in such a way as to minimize the heat input and the size of the weld pool while insuring full penetration, KAW could be an effective and affordable technology to improve the welding of thick materials. The key to developing such a controlled process is the development of a sensor that can detect the development of the keyhole. Preliminary studies have indicated that monitoring the plasma reflection could lead to a practical and accurate sensor for monitoring the keyhole development. Fuzzy logic provides a method for analysing this dynamic process in real time.

关键词： Fuzzy control Reflection Plasma welding Monitoring Size control Temperature control Thickness control Process control Plasma materials processing Fuzzy logic

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Data fusion for compliant motion tasks based on human skills

Data fusion for compliant motion tasks based on human skills

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： R. Cortesao R. Koeppe U. Nunes G. Hirzinger Electrical and Computer Engineering Department Institute of Systems and Robotics (ISR) University of Coimbra Coimbra Portugal Institute of Robotics and Mechatronics German Aerospace Center Germany

The paper discusses new developments of the data fusion paradigm due to Cortesao and Koeppe (1999, 2000). A bank of Kalman filters is analyzed in the fusion process. Experiments for a robotic compliant motion task (peg-in-hole) emerged from human skills are reported. Stereo vision and pose sense are fused to execute the task. Feedforward artificial neural networks (ANNs) are trained to transfer human skills to robotic manipulators.

关键词： Humans Sensor phenomena and characterization Stochastic resonance Robot sensing systems State estimation Information filtering Information filters Aerospace engineering Mechatronics Stereo vision

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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...

引用

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

引用

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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A new approach to credit assignment in a team of cooperative Q-learning agents

A new approach to credit assignment in a team of cooperative...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： A. Harati 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

Q-learning is widely used in many multi agent systems. In most cases, a separate critic is considered for qualifying each individual agent behavior or it is assumed that the critic is completely aware of effects of all agents' actions on the team qualification. But, in many cases, the role of each team member in the group performance is not known. In order to distribute a common credit among the agents, a suitable criterion must be provided to estimate the role of each agent in the team performance and to judge if an agent has done a wrong action. In this paper two such criteria, named certainty and expertness, for a team of agents with parallel tasks are introduced. In addition, two methods for reinforcing the agents based on the proposed measures are provided. Some simulation results are also reported to show the effectiveness of the proposed measures and methods.

关键词： Intelligent agent Learning systems Multiagent systems Intelligent sensors Artificial intelligence Laboratories Intelligent systems Intelligent robots Physics Mathematics

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A decision-making based approach for fault-handling in multi-agent systems

A decision-making based approach for fault-handling in multi...

引用

International Conference on Neural Information Processing

作者： M.S. Mirian M.N. Ahmadabadi Z. Navabi Robotics and AI Laboratory Department of Elect. and Comp. Eng Faculty of Engineering University of Tehran Iran Robotics and AI Lab Control & Intelligent Processing Center of Excellence Dept. of Elect. and Comp. Eng. University of Tehran Iran

This paper focuses on distributed fault recovery in agent-based systems by providing help for faulty members. In the presented method, if one faulty agent requests for help or agents are informed of fault in one of their teammates, they first decide if they are able to help or not. In the case that they are able to help and several help requests exist, helper agents specify a sequence of help actions through another distributed decision-making phase. The introduced fault clearing method is totally distributed in the sense that each helper agent makes its decisions by itself and no central or special agent exists in the system. In fact, the decision making process and the required information are designed such that the agents cooperate implicitly to prevent the system performance loss. The developed ideas are implemented in a simulated distributed control system. As it is shown, the proposed distributed fault-clearing method through reconfiguring the agents' roles is very effective.

关键词： Decision making Multiagent systems Robustness Condition monitoring Process control Robots Artificial intelligence Hardware Distributed decision making System performance

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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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Particle filter with analytical inference for human body tracking

Particle filter with analytical inference for human body tra...

引用

Workshop on Motion and Video Computing, MOTION 2002

作者： Lee, Mun Wai Cohen, I. Jung, Soon Ki Institute for Robotics and Intelligent Systems Integrated Media Systems Center University of Southern California Los AngelesCA90089-0273 United States Department of Computer Engineering Kyungpook National University 1370 Sankyuk-dong Buk-gu Daegu702-701 Korea Republic of

ISBN: (纸本)0769518605

The paper introduces a framework that integrates analytical inference into the particle filtering scheme for human body tracking. The analytical inference is provided by body parts detection, and is used to update subsets of state parameters representing the human pose. This reduces the degree of randomness and decreases the required number of particles. This new technique is a significant improvement over the standard particle filtering, with the advantages of performing automatic track initialization, recovering from tracking failures, and reducing the computational load. © 2002 IEEE.

关键词： Monte Carlo methods

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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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System architecture for versatile autonomous and teleoperated control of multiple miniature robots

System architecture for versatile autonomous and teleoperate...

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IEEE International Conference on robotics and Automation (ICRA)

作者： P.E. Rybski I. Burt T. Dahlin M. Gini D.F. Hougen D.G. Krantz F. Nageotte N. Papanikolopoulos S.A. Stoeter Center for Distributed Robotics Department of Computer Science and Engineering University of Minnesota Minneapolis USA Center for Distributed Robotics Department of Computer Science and Engineering University of Minnesota Minneapolis MN USA

ISBN: (纸本)0780365763

Using robots for surveillance and reconnaissance applications requires a versatile connection between the human operator and robotic hardware. Some application domains require a fully teleoperated system while others may benefit by giving robots more autonomy. This paper describes a robotic control architecture which merges both paradigms. The whole scheme is implemented using the miniature Scout robot and involves a suite of user interfaces that can be tailored to specific surveillance and reconnaissance missions. Hardware capabilities are presented and a visual servoing strategy, important for semi-autonomous Scout operation, is discussed.

关键词： Control systems Robot kinematics Mobile robots Robot sensing systems Humans Robot control Surveillance Hardware Reconnaissance Communication system control

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