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IEEE International Conference on Mechatronics and Automation

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

In this paper we discuss a learning approach to distributed object pushing. In the proposed approach, first the required individual skills for single-robot object pushing are learned using a fuzzy reinforcement learning method. Then, the robots learn how to coordinate their actions to push the object to the desired configuration cooperatively in a distributed manner. The proposed team-level learning benefits from the knowledge, which is in the form of a Q-table, that the agent has gained in its individual learning phase by a special design of reward signal and state-action representation. Each robot learns a threshold on its Q-value using a single state reinforcement learning method and pushes the object when the Q-value of its best action in the current state is above this threshold. The reward signal is designed based on the robots' Q-tables and no external critic is needed for learning cooperation. Simulation results show that the robots learn their individual skills and a cooperation protocol to push the object cooperatively

关键词： Robot kinematics Learning Protocols Robot control Robotics and automation Intelligent robots Signal design Mechatronics Process control Intelligent control

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Learning Distributed Object Pushing: Individual Learning and Distributed Cooperation Protocol

Learning Distributed Object Pushing: Individual Learning and...

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2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Hossein Aminaiee Majid Nili Ahmadabadi Control and Intelligent Processing Center of Excellence Robotics and AI Lab Department of Electrical and Computer Engineering University of Tehran Iran

In this paper we study learning in cooperative object pushing systems. The proposed approach is based on the idea of learning individual skills and then mapping the required cooperative behaviors on the learned skills. The control point for each individual robot is chosen so as to simplify the design of the reinforcement signal and reduce the role of delayed reward on individual learning in addition to make cooperative protocol simpler. A fuzzy Q-learning system for learning individual object pushing is proposed, together with a method for coordination among the robots to push the object cooperatively. The coordination method takes into account the dynamics of the object and the learned individual skills. The idea of the coordination protocol is based on the notion of ability and active regions defined in this paper. In effect, the cooperation protocol is mapped to a Q-value based policy. Simulation results supportively show that the robots learn individual and cooperative object pushing efficiently

关键词： Protocols Robot kinematics Intelligent robots Fuzzy systems Learning Friction Control systems Artificial intelligence Robot control Fuzzy control

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The Formal Economic Model of software engineering

The Formal Economic Model of Software Engineering

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Canadian Conference on Electrical and computer engineering (CCECE)

作者： Yingxu Wang Yuyu Yuan Theoretical and Empirical Software Engineering Research Center Department of Electrical and Computer Engineering University of Calgary Calgary AB Canada University of Calgary Calgary AB Canada

This paper presents a coherent theory on the nature of collaborative work and their mathematical models in software engineering. The formal economic model of software engineering costs (FEMSEC) is created based on the collaborative work theory. The FEMSEC model provides a theoretical foundation for software engineering decision optimizations on the optimal labor allocation, the shortest duration determination, and the lowest workload/effort and costs estimation. Based on the FEMSEC model, a wide range of fundamental problems in software project organization and cost estimation can be solved rigorously

关键词： software engineering Cost function Mathematical model Collaborative work Drives Productivity computer industry Collaborative software Tin Remuneration

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Routing for the Pennsylvania Maglev system by a genetic algorithm (vol 220, pg 55, 2006)

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART F-JOURNAL OF RAIL AND RAPID TRANSIT 2006年第4期220卷 475-475页

作者： Cao, Y-Y Lin, Z. Giras, T. C. Disk, D. R. Center of Rail Safety-Critical Excellence Charlottesville Virginia USA Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville Virginia USA Director of Engineering Maglev Inc. Pittsburgh Pennsylvania USA

The scheduling of vehicle movement activities is an important component in high-speed railway transit operations planning process. This paper presents a mathematical programming approach to vehicle routing for the Pennsylvania Transrapid Maglev Train System. A mathematical model of the routing procedure is first derived. Based on this model, the vehicle routing problem is formulated into a constrained optimization problem, in which the train miles travelled are maximized subject to various operational and safety requirements. This large scale non-linear optimization problem is then solved by a genetic algorithm. [PUBLICATION ABSTRACT]

关键词： Genetic algorithms Routing Vehicles Magnetic levitation systems

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WL-VC SRAM: a low leakage memory circuit for deep sub-micron design

WL-VC SRAM: a low leakage memory circuit for deep sub-micron...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： G. Razavipour A. Motamedi A. Afzali-Kusha Department of Electrical Engineering Amirkabir University of Technology슠 Tehran Iran Nanoelectronics Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

In this paper, a static random access memory (SRAM) cell that reduces the gate leakage power with low access latency is proposed. The technique reduces the gate leakage current both in the zero and in the one states. The efficiency of the design is evaluated by simulating the circuit in a 45-nm CMOS technology. Compared to the conventional SRAM cell, the proposed design reduces the total gate leakage current around 58% for an oxide thickness of 1.4nm. The increase in the area of the proposed cell is minimal compared to the conventional SRAM. The read access time of this SRAM is only 5.6% slower than that of the conventional SRAM

关键词： Random access memory Circuits Leakage current Voltage Gate leakage CMOS technology MOSFETs Tunneling Power dissipation Power engineering computing

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Piecewise Linear Model Tree: A modified combination of two learning algorithms for neuro-fuzzy models

Piecewise Linear Model Tree: A modified combination of two l...

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IEEE International Conference on computer-Aided Design

作者： Atiye Sarabi Jamab Babak N. Araabi Electrical Engineering Department Malek Ashtar University of Technology Tehran Iran Control & Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran

Locally Linear Model Tree (LOLIMOT) and Piecewise Linear Network (PLN) learning algorithms are two approaches in local linear modeling use different algorithm in each part of training phase. PLN learning is more depended on training data than LOIMOT and needs rich training data set. In PLN learning no division test is needed and it causes this algorithm to be much faster than LOLIMOT, but it may create adjacent neurons that would lead to singularity in regression matrix. In LOLIMOT, because of regular splitting of input space, this problem does not occur and always it leads to acceptable output error, but needs large number of neuron. Therefore, PILIMOT learning algorithm is introduced as modified combination of these two main Locally Linear approaches. This new method takes suitable error and neuron number from both of algorithms and leads to efficient network which is applicable to identify all functions. Simulation results show the advantage and behavior of new method.

关键词： Piecewise linear techniques Function approximation Neurons Partitioning algorithms Neural networks Approximation algorithms Piecewise linear approximation Radial basis function networks Training data Artificial neural networks

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A New Clustering Method for Improving Plasticity and Stability in Handwritten Character Recognition Systems

A New Clustering Method for Improving Plasticity and Stabili...

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International Conference on Pattern Recognition

作者： J. Sadri C.Y. Suen T.D. Bui CENPARMI Center for Pattern Recognition and Machine Intelligence Computer Science and Software Engineering Department Concordia University Montreal QUE Canada

This paper presents a new online clustering algorithm in order to improve plasticity and stability in handwritten character recognition systems. Our clustering algorithm is able to automatically determine the optimal number of clusters in the input data. An incremental learning technique similar to adaptive resonance theory (ART) is used to determine the best cluster for new data. Our technique also allows the previously learned clusters to be merged whenever the newly arrived data points push their centers close together. We also developed new features and similarity measures in order to describe and compare the shapes of handwritten digits to be used in our clustering algorithm. Results of our algorithm on clustering the shapes of the handwritten numerals from the CENPARMI isolated digit database are shown. Our method can incrementally learn new handwriting styles of digits, without forgetting the previous ones, therefore it can improve plasticity and stability

关键词： Clustering methods Stability Character recognition Shape measurement Clustering algorithms Prototypes Machine learning Pattern recognition Subspace constraints Neural networks

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UML-based service robot software development: A case study

UML-based service robot software development: A case study

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28th International Conference on software engineering 2006, ICSE '06

作者： Kim, Minseong Kim, Suntae Park, Sooyong Choi, Mun-Taek Kim, Munsang Gomaa, Hassan Department of Computer Science Sogang University Seoul Korea Republic of Center for Intelligent Robotics Frontier 21 Program Korea Institute of Science and Technology Seoul Korea Republic of Dept. of Information and Software Engineering George Mason University Fairfax VA 22030 United States

ISBN: (纸本)1595933751

The research field of Intelligent Service Robots, which has become more and more popular over the last years, covers a wide range of applications from climbing machines for cleaning large storefronts to robotic assistance for disabled or elderly people. When developing service robot software, it is a challenging problem to design the robot architecture by carefully considering user needs and requirements, implement robot application components based on the architecture, and integrate these components in a systematic and comprehensive way for maintainability and reusability. Furthermore, it becomes more difficult to communicate among development teams and with others when many engineers from different teams participate in developing the service robot. To solve these problems, we applied the COMET design method, which uses the industry-standard UML notation, to developing the software of an intelligent service robot for the elderly, called T-Rot, under development at center for Intelligent Robotics (CIR). In this paper, we discuss our experiences with the project in which we successfully addressed these problems and developed the autonomous navigation system of the robot with the COMET/UML method. Copyright 2006 ACM.

关键词： Intelligent robots

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Optimal evolutionary computational parameters for habitat structures optimization

Optimal evolutionary computational parameters for habitat st...

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Earth and Space 2006 - 10th Biennial International Conference on engineering, Construction, and Operations in Challenging Environments

作者： Hull, Patrick V. Sansoucie, Michael Dozier, Gerry Tinker, Mike NASA Marshall Space Flight Center Spacecraft and Vehicle Systems Dept./EV11 Huntsville AL 35812 United States Applied Computational Intelligence Lab. Department of Computer Science Amd Software Engineering Auburn University Auburn AL 36849-5347

ISBN: (纸本)0784408300

Long-duration surface missions to the Moon and Mars will require bases to accommodate habitats for the astronauts, as well as indoor laboratory facilities, in-situ resource plants, power plants, and scientific/surface mobility equipment. Transporting the materials and equipment required to build the necessary habitats would be costly and difficult. However, the use of planetary resources to produce construction materials, or even as naturally found (such as lunar regolith utilized as an outer layer for radiation shielding, or regolith in bags as wall structure), could drastically reduce the upmass for habitats. The materials chosen for the habitat walls play a direct role in protection against each of the mentioned hazards. Choosing the best materials, their configuration, and the amount required is extremely difficult due to the immense size of the design region. For example a 3-layer habitat wall created from 20 possible materials all with varying thicknesses would have #number of layers(possible material types)∧(possible thicknesses) = 320∧inf possible solutions. Clearly, an optimization method is warranted for habitat wall design. Standard optimization techniques are not suitable for problems with such large search spaces. To overcome the large search regions, a habitat wall design tool using genetic algorithms has been developed. GAs use a "survival of the fittest" philosophy, where the most fit individuals are more likely to survive and reproduce, therefore transmitting their genes to the next generation. This paper focuses on finding optimal GA parameters for the habitat optimization tool. This tool is a multiobjective formulation of structural analysis, heat loss, radiation, and meteoroid protection. Some of the constraint calculations (i.e. safety factor, deflection, and heat loss) require long computation times. Even though each material has a designated thickness range, the number of different values within that range is near infinite;therefore, the searc

关键词： Lunar missions

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Design and simulation of an adaptive load shedding algorithm using a real network

Design and simulation of an adaptive load shedding algorithm...

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IEEE Power India Conference

作者： H. Seyedi M. Sanaye-Pasand M.R. Dadashzadeh School of Electrical and Computer Engineering University of Tehran Iran Control and Intelligent Processing Center of Excellence University of Tehran Iran Department of Electrical Engineering University of Western Ontario Canada

ISBN: (纸本)0780395255

In this paper a new adaptive under frequency load shedding algorithm is designed. The purpose of this method is to enhance the adaptability of under frequency relays and increase the security of power system during large disturbances. A suitable method to design the proposed adaptive under frequency load shedding scheme is described in detail. After completing the design, it is tested on a real power system by modeling the network in a power system studies software. Simulation results indicate that the proposed method has an improved performance for large disturbances while its response is similar to the conventional scheme for small disturbances

关键词： Algorithm design and analysis Power system simulation Power system relaying Power system security Power system modeling Frequency Design methodology software testing System testing software systems

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