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

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

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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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Optimal genetic representation of complete strictly-layered feedforward neural networks

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6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001

作者： Raptis, Spyros Tzafestas, Spyros Karagianni, Hermione Intelligent Robotics and Automation Laboratory Division of Signals Control and Robotics Department of Electrical and Electronic Engineering National Technical University of Athens Zographou Campus Athens15773 Greece

ISBN: (纸本)9783540422372

The automatic evolution of neural networks is both an attractive and a rewarding task. The connectivity matrix is the most common way of directly encoding a neural network for the purpose of genetic optimization. However, this representation presents several disadvantages mostly stemming from its inherent redundancy and its lack of robustness. We propose a novel representation scheme for encoding complete strictly-layered feedforward neural networks and prove that it is optimal in the sense that it utilizes the minimum possible number of bits. We argue that this scheme has a number of important advantages over the direct encoding of the connectivity matrix. It does not suffer from the curse of dimensionality, it allows only legal networks to be represented which relieves the genetic algorithm from a number of checking and rejections, and the mapping from the genotypes to phenotypes is one-to-one. Additionally, the resulting networks have a simpler structure assuring an easier learning phase. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Genetic algorithms

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Robust synchronizing motion control of twin-servo systems based on network modeling

Robust synchronizing motion control of twin-servo systems ba...

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IEEE Conference on Decision and control

作者： Bong Keun Kim Wan Kyun Chung Il Hong Suh Robotics & Bio-Mechatronics Laboratory Pohang University of Science and Technology South Korea Intelligent Control & Robotics Laboratory Hanyang University South Korea

ISBN: (纸本)0780366387

In this paper, a robust control method for synchronizing motions of a twin-servo system is proposed. Using the correspondence between the mathematical modeling and the circuit representation, a network representation of twin-servo system is proposed. And a stabilizing control input is designed based on robust internal-loop compensator for the separate system in the presence of uncertainty and disturbance. Skew motion compensating control input is also designed to maintain the synchronizing motion during high speed motion. The stability of the whole closed-loop system is proved based on passivity theory. Through experiments using a semiconductor chip mounting device, the performance of the proposed method is evaluated.

关键词： Robust control Motion control Adaptive control control systems Uncertainty intelligent robots Stability analysis Damping Biomechatronics intelligent control

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A novel visual servoing with stereo cameras using QR decomposition and disturbance observer

A novel visual servoing with stereo cameras using QR decompo...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Joon-Soo Lee Il Hong Suh Bum-Jae You Sang-Rok Oh Intelligent Control and Robotics Laboratory Hanyang University Ansan Gyeonggi South Korea Intelligent System Control Research Center Korea Institute of Science and Technology Seoul South Korea

This paper proposes a visual serving method based on QR decomposition and disturbance observer. The QR decomposition factorizes the image feature Jacobian into a unitary matrix and an upper triangular matrix. It is shown that several performance indices such as measurement sensitivity of visual features, sensitivity of the control to noise and controllability can be improved for any general image feature Jacobian by OR decomposition and disturbance observer. To show the validities of the proposed approach, visual servoing with stereo cameras is experimented on Samsung FARAMAN 6-axis industrial manipulator.

关键词： Visual servoing Cameras Jacobian matrices Matrix decomposition controllability Manipulators intelligent control intelligent robots Robot vision systems Robot sensing systems

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Factorization method for multiple perspective views via iterative depth estimation

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Systems and Computers in Japan 2000年第13期31卷 87-95页

作者： Ueshiba, Toshio Tomita, Fumiaki Electrotechnical Laboratory Tsukuba 305-8568 Japan Department of Electrical Engineering University of Tokyo Electrotechnical Laboratory Min. of Intl. Trade and Industry Intelligent Systems Division Canada Nat. Inf. Eng. Lab. Information Processing Society Robotics Society of Japan Soc. of Instrum. Control Engineers Department of Control Engineering Osaka University CMU Department of Computer Science Information Processing Society Robotics Society of Japan

This paper proposes a factorization method that reconstructs camera motion and scene shape based on the matching of multiple images under the condition that the camera captures a perspective view. Starting from the affine projection camera model, the projection depth is iteratively estimated until the measurement matrix has rank 4. Then, the obtained measurement matrix is factorized to restore the three-dimensional information of the scene in the projection space. This approach eliminates noise sensitive processes, such as the calculation of the fundamental matrix, that are required in the factorization for the conventional perspective projection image, and a stable reconstruction is realized. Furthermore, the metric constraint in the conventional affine model is extended, and the metric constraint in the perspective projection condition is derived. It is shown that the reconstruction in Euclidean space is realized if the internal parameters of the camera are given.

关键词： Image reconstruction

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Application of a genetic algorithm in triangulation of a 3-D object surface

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International Journal of Computers and Applications 2000年第2期22卷 73-77页

作者： Zhenyu, Chen Mbede, J.B. Yan, Zhou Dehua, Li Hanping, Hu State Commn. Res. Open Lab. Image P. Inst. Pattern Recog. Artif. Intell. Huazhong Univ. of Sci. and Technol. 430074 Wuhan China Intelligent Contr. and Robotics Lab. Dept. of Contr. Sci. and Engineering Huazhong Univ. of Sci. and Technol. 430074 Wuhan China Second Artillery Institute Huazhong Univ. of Sci. and Technol. Inst. Pattern Recog. Artif. Intell. Huazhong Univ. of Sci. and Technol. Second Artillery Institute China Wuhan University China Artificial Intelligence Department University of Edinburgh Inst. of AI and Pattern Recognition Huazhong Univ. of Sci. and Technol. China Cogn. Sci. Natl. Key Found. Res. P. Douala University Cameroon Tübingen University Germany Automatic Control Laboratory Darmstadt University Department of Service Cameroon Min. of National Education Robotics Laboratory Huazhong Univ. of Sci. and Technol. Wuhan China Assoc. Connectionnistes These-ACTH Rennes France IEEE Soc. of Robotics and Automation IEEE Society of Control Systems IASTED Assoc. Jeunes Chercheurs Robotique France Navy University of Engineering China Huazhong Univ. of Sci. and Technol. China Department of Computer Science Airforce Radar Acad. of Engineering China Inst. of P.R and AI Huazhong Univ. of Sci. and Technol.

This paper proposes a genetic-based algorithm for surface reconstruction of three-dimension (3-D) objects from a group of contours representing its section plane lines. The algorithm can optimize the triangulation of the surface of 3-D objects with a multi-objective optimization function to meet the needs of a wide range of applications. Further, a new crossover operator for triangulation and a new 3-D quadrilateral mutation operator are also introduced.

关键词： Object recognition

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intelligent compliance control for robot manipulators using adaptive stiffness characteristics

Intelligent compliance control for robot manipulators using ...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Byoung-Ho Kim Nak Young Chong Sang-Rok Oh Il Hong Suh Young-Jo Cho Intelligent System Control Research Center KIST Seoul South Korea Biorobotics Division Robotics Department MEL Limited Japan Intelligent Control and Robotics Laboratory Hanyang University Seoul South Korea

A compliance control strategy for robot manipulators is proposed by employing a self-adjusting stiffness function. To be specific, each entry of the diagonal stiffness matrix corresponding to task coordinate in Cartesian space is adaptively adjusted during contact along the corresponding axis based on the contact force with its environment. It can also be used for both unconstrained and constrained motions without any switching mechanism which often causes undesirable instability and/or vibrational motion of the end-effector. The experimental results show the effectiveness of the proposed method by employing a two-link direct drive manipulator interacting with an unknown environment.

关键词： intelligent robots intelligent control Robot control Manipulators Programmable control Adaptive control Robot kinematics Force control Orbital robotics Servomechanisms

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A novel visual servoing approach involving disturbance observer

A novel visual servoing approach involving disturbance obser...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Joon-Soo Lee Il Hong Suh Bum-Jae You Sang-Rok Oh Intelligent System Control Research Center Korea Institute of Science and Technology Seoul South Korea Intelligent Control and Robotics Laboratory Hanyang University Ansan Gyeonggi South Korea

To improve the visual servoing performance, several strategies have been proposed by using redundant feature points, by using a point with different height, and by a weighted selection of image features. The performance of these visual servoing methods depends on the configuration between the camera and objects. And redundant feature points require much computational efforts. The paper proposes a visual servoing method based on a disturbance observer which compensates the effect of the off-diagonal component of the image feature Jacobian to be null. The performance indices such as measurement sensitivity of visual features, sensitivity of the control to noise, and controllability are improved when an image feature Jacobian is given as a block diagonal matrix. The proposed approach is applied to the PUMA560 and Samsung FARAMAN 6-axis industrial robot manipulators successfully.

关键词： Visual servoing Jacobian matrices Robot sensing systems Manipulators Service robots Image sensors intelligent control intelligent robots Cameras controllability

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