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2008 IEEE/RSJ International Conference on intelligent Robots and systems, Pages 526-1042

作者： Masoud Asadpour Alexander Sproewitz Aude Billard Pierre Dillenbourg Auke Jan Ijspeert ECE Dept. University of Tehran Control and Intelligent Processing Center of Excellence Iran Bio-Inspired Robotics Group (BIRG) Switzerland Learning Algorithms and Systems Laboratory (LASA) Switzerland Centre de Recherche et d Appui pour la Formation Switzerland Centre de Recherche et d'Appui pour la Formation (CRAFT) Ecole Polytechnique Fédérale de Lausanne (EPFL) Switzerland Bio-Inspired Robotics Group (BIRG)

ISBN: (纸本)9781424420575

This project incorporates modular robots as building blocks for furniture that moves and self-reconfigures. The reconfiguration is done using dynamic connection/disconnection of modules and rotations of the degrees of freedom. This paper introduces a new approach to self-reconfiguration planning for modular robots based on the graph signature and the graph edit-distance. The method has been tested in simulation on two type of modules: YaMoR and M-TRAN. The simulation results shows interesting features of the approach, namely rapidly finding a near-optimal solution.

关键词： Modular self-reconfigurable robots Adaptive furniture Graph isomorphism Graph signature Graph edit distance Modular robots graph editing Line graph Reconfiguration Furnishings signatures Building blocks Degree of freedom crop rotation

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Towards an inclusive computational model of visual cortex

Towards an inclusive computational model of visual cortex

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： M. Gheiratmand H. Soltanian-Zadeh H. Khaloozadeh Electrical Engineering Department K.N. Toosi University of Technology Tehran Iran Radiology Department Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA School of Cognitive Sciences Institute for Studies Theoretical Physics and Mathematics (IPM) Tehran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran

Understanding the primatespsila visual system has been one of the challenging problems of different groups of scientists for years. Though many studies, from physiology and neuroscience to computer vision, are done on different aspects of visual processing in the cortex, a comprehensive computational model of visual cortex is still missing. We have implemented a computational model of object recognition in ventral visual pathway in our previous work. This hierarchical model covers visual areas V1/V2, V4/PIT, and AIT sending inputs to the Prefrontal Cortex (PFC) for categorization. To extend our model, in this work, we have added a simple model of motion detection in neurons of areas V1 and MT of the dorsal stream to our previous model. This has enabled the model to perform another principal function of the visual cortex, i.e., motion perception.

关键词： Brain modeling Computational modeling Neurons Biological system modeling Object recognition Motion analysis Solid modeling Visual system Computer vision Motion detection

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Challenges in implementation of human-automation interaction models

Challenges in implementation of human-automation interaction...

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2007 Mediterranean Conference on control and Automation, MED

作者： Fereidunian, Alireza Lucas, Caro Lesani, Hamid Lehtonen, Matti Nordman, Mikael Center of Excellence for Control and Intelligent Processing School of ECE University of Tehran Iran IPM Iran Power Systems and High Voltage Engineering Lab. Helsinki University of Technology Finland

ISBN: (纸本)142441282X

This paper presents the practical experience gained in the process of implementing the human-centered automation design methodology to an electric power utility management automation function, along with the analytical discussions on the implementation challenges. This report of implementation challenges and the discussions made on the methods devised to conquer those challenges lead to an alternative approach to the original approach to the well-known human-centered automation design model in the literature. ©2007 IEEE.

关键词： Human computer interaction

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Learning Cooperative Object Pushing with Variable Contact Point

Learning Cooperative Object Pushing with Variable Contact Po...

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2007 IEEE/ASME International Conference on advanced intelligent Mechatronics, Pages 805-1210

作者： Abdol Hossein Aminaiee Majid Nili Ahmadabadi Robotics and AI Laboratory Control and Intelligent Processing Center of Excellence Department of Electerical and Computer Engineering University of Tehran

ISBN: (纸本)9781424412631;1424412633

Learning in multi-agent environments where each agent's action directly affects other agents would be an important matter and a complicated task. To reduce the learning time and simplifying the learning process, it is suitable to learn individual skills and then provide cooperation and coordination utilizing the learned individual skills. In the approach proposed in this paper, agents benefit from their individual knowledge obtained in the individual learning phase to cooperate with other agents. Cooperative object pushing system is used as a testbed to our proposed method where cooperation and coordination between agents are needed in these systems. Agents independently learn to push the object to the target by using the proposed fuzzy reinforcement learning method. Agents attain their cooperative behaviors properly making use of the coded knowledge in the Q-table. Simulation and experimental results show that by interpreting the knowledge in the Q-table, agents can achieve high level behaviors with a high degree of cooperation.

关键词： Agents Learning Point contacts pushing variable contact

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An Agent Matching Architecture for Bilateral Contacts in Multi Agent Markets

An Agent Matching Architecture for Bilateral Contacts in Mul...

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IEEE International Conference on intelligent Computer Communication and processing (ICCP)

作者： Hamed Kebriaei Vahid Johari Majd Ashkan Rahimi-Kian Intelligent Control Systems Lab. Electrical Engineering Dept. Tarbiat Modares University Tehran Iran Intelligent Control Systems Laboratory Electrical Engineering Department Tarbiat Moalem University Tehran Iran Control and Intelligent Process Center of Excellence Electrical Engineering Department University of Tehran Tehran Tehran Iran

In this paper, an agent matching architecture for bilateral contracts of a multi agent market is proposed. The bilateral market contains a number of sellers and buyers who face opponents for negotiation and signing bilateral contracts. Each agent has a hierarchical representation of trading commodity attributes, where based on that it will create a tree structure of attributes. Using this structure, we apply a modified version of fuzzy similarity algorithm to compute similarity between each pair of buyer and seller agents' trees. Then, we use game theory and the concept of Stackelberg equilibrium to assess the matchmaking among the seller and buyer agents. Agents who lose contract or want to sign a new contract have a chance to restart the procedure. Through a case study for bilateral contracts in energy market, the applicability of our agent matching architecture is illustrated.

关键词： Contracts Game theory Tree data structures Decision making Contacts intelligent control intelligent agent control systems Supply and demand Fuzzy sets

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Evaluation of BOLD Sensitivity Using a Realistic MRI Simulator

Evaluation of BOLD Sensitivity Using a Realistic MRI Simulat...

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Joint Meeting of the International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the International Conference on Functional Biomedical Imaging (NFSI-ICFBI)

作者： Ali-Reza Mohammadi-Nejad G.-Ali Hossein-Zadeh Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of ECE University of Tehran Tehran Iran Henry Ford Health System Medical Image Analysis Laboratory Detroit MI USA

MRl simulation is a suitable method to evaluate and acquire understanding of the complex blood oxygenation level dependent (BOLD) effect. To study the observability of BOLD signal, we extended a MRI simulator. This simulator is capable of complete modeling of object (tissue) and main field inhomogeneities. We made a digital phantom in which the magnitude of fractional oxygenation (Y), hematocrit (Hct) values in red blood cells, the diameter of vessels, and also the position of blood vessel within the voxel can be changed. Then we created echo planar imaging (EPI) images of the phantom under resting and activated states using the simulator. Resulting images were analyzed using cross-correlation and t-test analysis for activation detection. Then the effect of various parameters on the detection of BOLD is investigated. These parameters include fractional oxygenation, spatial extent of BOLD effect and the location of vessel inside voxel. This simulation study provides a basis for planning experiments aimed at BOLD contrast detection with EPI pulse sequence.

关键词： Magnetic resonance imaging Red blood cells Medical simulation Biomedical imaging Image analysis Magnetic susceptibility Analytical models Imaging phantoms Blood vessels Magnetic properties

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Adaptive autonomy: Smart cooperative cybernetic systems for more humane automation solutions

Adaptive autonomy: Smart cooperative cybernetic systems for ...

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IEEE International Conference on systems, Man and Cybernetics

作者： Alireza Fereidunian Matti Lehtonen Hamid Lesani Caro Lucas Mikael Nordman Eslamshahr Barnch Islamic Azad University Iran Helsinki University of Technology Finland Imperial College London UK Center of Excellence for Control and Intelligent Processing University of Tehran Iran Power Systems and High Voltage Engineering Laboratory Helsinki University of Technology Finland

Smart cooperation of human and computer agents should be harmonized by adapting the automation level of the cybernetic systems to the changing environmental and peripheral situations. This paper presents an adaptive autonomy methodology that is based on an extension of a well-known human-automation interaction model, as well as the expert judgment technique and the performance shaping factors concept. The method is implemented to a power distribution automation system, and the results are discussed through a scenario-based approach. Then, the performance of the proposed methodology and the effectiveness of adaptive autonomy are shown by the wide span of the changes in the resulting automation levels. The trends of the automation levels are investigated versus the criticality of the situations and the automation stages. The application-oriented matters are also discussed to stress on the context-based nature of the human-centered automation models.

关键词： Cybernetics Scholarships Process control intelligent control Human computer interaction Power systems Voltage Power engineering and energy Design automation Computer peripherals

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Challenges in implementation of human-automation interaction models

Challenges in implementation of human-automation interaction...

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Mediterranean Conference on control and Automation (MED)

作者： Afreza Fereidunian Caro Lucas Hamid Lesani Matti Lehtonen Mikael Nordman Helsinki University of Technology Finland Imperial College London UK Center of Excellence for Control and Intelligent Processing School of ECE University of Tehran Iran Power Systems and High Voltage Engineering Laboratory Helsinki University of Technology Finland Researcher with the Power Systems and High Voltage Engineering Laboratory Helsinki University of Technology Finland

关键词： Design automation Human computer interaction Scholarships intelligent agent Power system modeling Process control intelligent control Design methodology Energy management Collaboration

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LANDING AN UNMANNED AIR VEHICLE: VISION BASED MOTION ESTIMATION AND NONLINEAR control

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Asian Journal of control 2008年第3期1卷

作者： Omid Shakernia Yi Ma T. John Koo Shankar Sastry Dept. of Electrical Engineering & Computer Science University of California at Berkeley Berkeley CA94720-1774 U.S.A. Tak-Kuen John Koo received the B.Eng. degree in 1992 in Electronic Engineering and the M.Phil. in 1994 in Information Engineering both from the Chinese University of Hong Kong. From 1994 to 1995 he was a graduate student in Signal and Image Processing Institute at the University of Southern California. He is currently a Ph.D. Candidate in Electrical Engineering and Computer Sciences at the University of California at Berkeley. His research interests include nonlinear control theory hybrid systems inertial navigation systems with applications to unmanned aerial vehicles. He received the Distinguished M.Phil. Thesis Award of the Faculty of Engineering The Chinese University of Hong Kong in 1994. He was a consultant of SRI International in 1998. Currently he is the team leader of the Berkeley AeRobot Team and a delegate of The Graduate Assembly University of California at Berkeley. He is a student member of IEEE and SIAM. S. Shankar Sastry received his Ph.D. degree in 1981 from the University of California Berkeley. He was on the faculty of MIT from 1980-82 and Harvard University as a Gordon McKay professor in 1994. He is currently a Professor of Electrical Engineering and Computer Sciences and Bioengineering and Director of the Electronics Research Laboratory at Berkeley. He has held visiting appointments at the Australian National University Canberra the University of Rome Scuola Normale and University of Pisa the CNRS laboratory LAAS in Toulouse (poste rouge) and as a Vinton Hayes Visiting fellow at the Center for Intelligent Control Systems at MIT. His areas of research are nonlinear and adaptive control robotic telesurgery control of hybrid systems and biological motor control. He is a coauthor (with M. Bodson) of “Adaptive Control: Stability Convergence and Robustness Prentice Hall 1989.” and (with R. Murray and Z. Li) of “A Mathematical Introduction to Robotic Manipulati

In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-motion estimation problem since all feature points lie on a planar surface (the landing pad). We study together the discrete and differential versions of the ego-motion estimation, in order to obtain both position and velocity of the UAV relative to the landing pad. After briefly reviewing existing algorithm for the discrete case, we present, in a unified geometric framework, a new estimation scheme for solving the differential case. We further show how the obtained algorithms enable the vision sensor to be placed in the feedback loop as a state observer for landing control. These algorithms are linear, numerically robust, and computationally inexpensive hence suitable for real-time implementation. We present a thorough performance evaluation of the motion estimation algorithms under varying levels of image measurement noise, altitudes of the camera above the landing pad, and different camera motions relative to the landing pad. A landing controller is then designed for a full dynamic model of the UAV. Using geometric nonlinear control theory, the dynamics of the UAV are decoupled into an inner system and outer system. The proposed control scheme is then based on the differential flatness of the outer system. For the overall closed-loop system, conditions are provided under which exponential stability can be guaranteed. In the closed-loop system, the controller is tightly coupled with the vision based state estimation and the only auxiliary sensor are accelerometers for measuring acceleration of the UAV. Finally, we show through simulation results that the designed vision-in-the-loop controller generates stable landing maneuvers even for large levels of image measurement noise. Experiments on a real UAV will be presented in future work.

关键词： Motion estimation computer vision based control unmanned air vehicle differential flatness

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A Hierarchical Clustering Based on Mutual Information Maximization

A Hierarchical Clustering Based on Mutual Information Maximi...

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IEEE International Conference on Image processing

作者： M. Aghagolzadeh H. Soltanian-Zadeh B. Araabi A. Aghagolzadeh Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran

Mutual information has been used in many clustering algorithms for measuring general dependencies between random data variables, but its difficulties in computing for small size datasets has limited its efficiency for clustering in many applications. A novel clustering method is proposed which estimates mutual information based on information potential computed pair-wise between data points and without any prior assumptions about cluster density function. The proposed algorithm increases the mutual information in each step in an agglomerative hierarchy scheme. We have shown experimentally that maximizing mutual information between data points and their class labels will lead to an efficient clustering. Experiments done on a variety of artificial and real datasets show the superiority of this algorithm, besides its low computational complexity, in comparison to other information based clustering methods and also some ordinary clustering algorithms.

关键词： Mutual information Clustering algorithms Clustering methods Data mining Data structures Density functional theory Computational complexity Entropy Higher order statistics Probability density function

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