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International Conference on Pattern Recognition

作者： I. Hofman R. Jarvis Intelligent Robotics Research Centre Department of Electrical and Computer Systems Engineering Monash University Clayton VIC Australia

A nonparametric method for clustering multidimensional data in O(nlogn) time is described. It is based on the shared near neighbours algorithm. It uses adaptive k-d trees combined with various other sophisticated data structures to significantly decrease the computational complexity of the original algorithm which was O(n/sup 2/). The algorithm is suitable for a wide range of data and capable of delineating clusters of varying shape, density, and homogeneity. A comprehensive set of results is presented.

关键词： Robustness Clustering algorithms Partitioning algorithms intelligent robots electrical capacitance tomography systems engineering and theory Data structures Computational complexity Shape Clustering methods

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Dynamic fuzzy control and system stability for the Acrobot

Dynamic fuzzy control and system stability for the Acrobot

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： M.H. Smith T. Zhang W.A. Gruver Department of Electrical Engineering and Computer Science University of California Berkeley CA USA Intelligent Robotics and Manufacturing Systems Laboratory Manufacturing Systems Laboratory Simon Fraser University Burnaby Canada

This paper discusses the swing-up control of a two link robot mechanism known as the Acrobot. Previously, a technique using meta-rules was proposed to compensate for external disturbances when using a dynamic fuzzy controller. In this paper, stability of the meta-rule system is analyzed from a global asymptotic stability viewpoint based on fuzzy characteristic matrices. These matrices are generated from the first phase of a three phase learning process involving the combination of genetic algorithms, dynamic switching fuzzy systems, and meta-rule techniques with the purpose of developing a better performing fuzzy controller.

关键词： Fuzzy control Stability Fuzzy systems Automatic control Fuzzy reasoning Robot kinematics Control systems Leg PD control Genetic algorithms

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Simple adaptive control by fuzzy boxes methodology

Simple adaptive control by fuzzy boxes methodology

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Mediterranean Electrotechnical Conference (MELECON)

作者： D. Stipanicev Z. Torba LaRIS-Laboratory for Robotics and Intelligent Systems Faculty of Electrical Engineering Machine Engineering and Naval Architecture University of Split Split Croatia

"Simplicity is an advantage", particularly in solving real-life problems. Control engineering is not the exception. Simple control algorithms capable of controlling complex systems are dreams of all control engineers. 30 years ago Michie and Chambers (1968) had introduced the control methodology with such properties. They called it the boxes methodology. On the other hand, these days we are witnessing the commercial success of another simple and effective control procedure: fuzzy control. This paper shows the common points of both control procedures and looks at the boxes methodology as a special case of the fuzzy control principle. Theoretical, simulation and experimental results are given as well.

关键词： Adaptive control Fuzzy control Control systems Mathematical model Quantization intelligent systems Error correction Input variables intelligent robots Control system synthesis

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An Efficient PC-Based Environment for Power System Studies - Application to the Restoration Problem

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IFAC Proceedings Volumes 1998年第20期31卷 659-664页

作者： N.A. Fountas N.D. Hatziargyriou K.P. Valavanis Electric Energy Systems Laboratory Department of Electrical and Computer Engineering National Technical University of Athens Greece Robotics and Automation Laboratory The Center for ACS The University of Southwestern Louisiana Lafayette

Advanced powerful tools are sought for in order to conduct power system studies, especially for large scale systems. In this paper, an efficient PC-based environment for power system studies is presented. It is based on both analytical and artificial intelligence techniques. To demonstrate its effectiveness, this environment has been used for restoration studies following a recent blackout in the Hellenic power system, with very promising results.

关键词： computer environment analytic approximations Timed Petri-nets Power system

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Allocating goals and planning responsibility in dynamic sensible agent organizations

Allocating goals and planning responsibility in dynamic sens...

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IEEE International Conference on systems, Man and Cybernetics

作者： K.S. Barber R.M. McKay The Laboratory for Intelligent Process and Systems Electrical and Computer Engineering University of Texas Austin Austin TX USA

A multi-agent system (MAS) can be viewed as a group of entities interacting to achieve individual or collective goals. Communication is a central issue in this interaction between agents. This paper uses the COOL language to define an extended version of the contract net protocol to address issues in one particular MAS-sensible agents. The proposed implementation of our protocol and its use in the sensible agent testbed is also discussed.

关键词： Protocols Contracts Testing Character generation Laboratories intelligent systems Autonomous agents

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Multi-Agent Planning under Dynamic Adaptive Autonomy

Multi-Agent Planning under Dynamic Adaptive Autonomy

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IEEE International Conference on systems, Man and Cybernetics

作者： K.S. Barber D.C. Han The Laboratory for Intelligent Process and Systems Electrical and Computer Engineering University of Texas Austin Austin TX USA

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Algorithmic navigation to train deictic mobile robot operators

Algorithmic navigation to train deictic mobile robot operato...

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IEEE International Conference on robotics and Automation (ICRA)

作者： M.E. Cleary J.D. Crisman College of Computer Science Robotics and Vision Systems Laboratory Boston MA USA Department of Electrical and Computer Engineering Northeastern University Boston MA USA

Presents an algorithm for a simulator to train mobile robot operators in the use of deictic commands. It shows that robots can be deictically controlled in any reasonable environment. Deictic control is a technique which directs the robot by visually servoing on targets pointed out to the robot by its operator. This provides a direct, intuitive control method which any sighted operator can use. Previous work has formally defined canonical targets required for deictic control, and has described a training system for prospective users. This paper extends that work by providing a specific algorithm for the construction of deictically controlled paths. The algorithm is described in detail and results are presented. This algorithm shows that deictic commands and their targets can be simply determined by an agent able to sense the surrounding environment.

关键词： Navigation Mobile robots Robot control Automatic control Control systems Robot vision systems Machine vision Object recognition Humans robotics and automation

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Adaptive stabilization of neural control for robot traj ectory tracking

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Tsinghua Science and Technology 1998年第3期3卷 1149-1154页

作者： Sun Fuchun Lu Wenjuan Dai Min Department of Computer Science and Technology State Key Laboratory of Intelligent Technology and Systems Tsinghua University Beijing 100084 Department of Electrical Engineering Tsinghua University Beijing 100084

A neural network (NN)-based adaptive control law is proposed for the tracking control of an n-link robot manipulator with unknown dynamic nonli nearities. Basis ftnction-like nets are employed to approximate the plant nonli nearilties, and the bound on the NN reconstruction error is assurred to be unknown. The proposed NN-based adaptive control approach integrates an NN approach with an adaptive implementation of discrete variable structure control with a simple estimation law to estimate the upper bound on the NN reconstruction error and an additional control input to be updated as a function of the estimate. Lyapunov stability theory is used to prove the uni form ultimate boundedness of the tracking error.

关键词： Artificial neural networks Manipulator dynamics Vectors Measurement Control systems

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Analysis of the sustained ventricular arrhythmias from SAECG using artificial neural network and fuzzy clustering algorithm

Analysis of the sustained ventricular arrhythmias from SAECG...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： H. Heidari A.V. Shahidi K. Aminian N. Sadati Department of Electrical Engineering Sahand University of Technology Tabriz Iran Department of Electrical and Computer Engineering University of Tehran Tehran Iran Electrical Engineering Department Metrology Laboratory Swiss Federal Lnstitute of Technology Lausanne Switzerland Intelligent Systems Laboratory Sharif University of Technology Tehran Iran

Patients with sustained ventricular tachycardia and ventricular fibrillation have a potential for sudden death. After myocardial infarction the chance to get sustained ventricular tachycardia or ventricular fibrillation increases, thus reduction in number of sudden death requires advanced predictive procedures. In this study, frequency domain feature extraction, clustering and classification models are combined for providing an integrated system for the sustained ventricular arrythmias. The radial basis function network and the fuzzy c-means algorithm for training clustering and classification were investigated. These techniques do not have limitation of the previous classical procedures. The value of sensitivity and specificity, on the data was used here, for the RBFN were found to be 92.3% and 71.4%, respectively, also the value of sensitivity and specificity for the PCM were found to be 84.6% and 71.4%, respectively.

关键词： Artificial neural networks Myocardium Frequency domain analysis Clustering algorithms Fibrillation Feature extraction Filtering Laboratories Sensitivity and specificity Time domain analysis

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Generalizing over aspect and location for rooftop detection

Generalizing over aspect and location for rooftop detection

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IEEE Workshop on Applications of computer Vision (WACV)

作者： M.A. Maloof P. Langley T.O. Binford R. Nevatia Department of Computer Science George town University Washington D.C. DC USA Institute for the Study of Learning and Expertise Palo Alto CA USA Robotics Laboratory Department of Computer Science University of Stanford Stanford CA USA Institute for Robotics and Intelligent Systems School of Engineering University of Southern California Los Angeles CA USA

We present the results of an empirical study in which we evaluated cost-sensitive learning algorithms on a rooftop detection task, which is one level of processing in a building detection system. Specifically, we investigated how well machine learning methods generalized to unseen images that differed in location and in aspect. For the purpose of comparison, we included in our evaluation a handcrafted linear classifier, which is the selection heuristic currently used in the building detection system. ROC analysis showed that, when generalizing to unseen images that differed in location and aspect, a naive Bayesian classifier outperformed nearest neighbor and the handcrafted solution.

关键词： Machine vision Buildings Machine learning computer science intelligent robots Learning systems Image analysis Nearest neighbor searches Robustness Head

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