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IEEE International Conference on Systems, Man and Cybernetics

作者： Xianyi Yang M. Meng ART Advanced Robotics & Teleoperation Laboratory Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

In this paper, a neural network approach is proposed for real-time path planning of robots with safety consideration. The neural network is topologically organised, which is based on a previous biologically inspired model for dynamical trajectory generation of a mobile robot in a nonstationary environment. The state space of the neural network can be the joint space of multilink robot manipulators or the Cartesian workspace. This model is capable of dealing with multiple target problems as well. The target globally attracts the robot, while the obstacles push the robot away locally to avoid collisions. By taking into account of the clearance from obstacles, the planned "comfortable" path does not suffer either the "too close" or the "too far" problems. Each neuron has only local lateral connections. The optimal path is generated in real-time through the dynamics of the neural activity landscape without explicitly optimising any cost function. Therefore, it is computationally efficient. The stability of the network is guaranteed by the existence of a Lyapunov function. The effectiveness and efficiency are demonstrated through simulation studies.

关键词： Neural networks Path planning Safety Orbital robotics Biological system modeling Mobile robots State-space methods Manipulator dynamics Neurons Cost function

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A neural network approach to real-time trajectory generation [mobile robots]

A neural network approach to real-time trajectory generation...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Max Meng Xianyi Yang ART Advanced Robotics & Teleoperation Laboratory Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

ISBN: (纸本)078034300X

A neural network approach is proposed for real-time collision free trajectory generation in an environment with varying obstacles and moving target. This biologically inspired neural network is topologically organised. The dynamics of each neuron is characterised by a shunting equation or an additive equation. Each neuron has only local connections, and the optimal trajectories are generated without any explicitly optimising cost functions and without learning. Therefore the model is computationally efficient. The stability of the network is analytically proved using a Lyapunov function candidate. As examples, the proposed neural network is applied to trajectory formation for a mobile robot in solving maze-type problems, dynamically tracking moving target, and avoiding varying obstacles. The efficiency of the proposed approach is demonstrated through simulation and comparison studies.

关键词： Neural networks Trajectory Neurons Equations Cost function Biological system modeling Computational modeling Biology computing Stability analysis Lyapunov method

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3-D motion and depth estimation from sea-floor images for mosaic-based station-keeping and navigation of ROVs/AUVs and high-resolution sea-floor mapping

3-D motion and depth estimation from sea-floor images for mo...

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Symposium on Autonomous Underwater Vehicle Technology (AUV)

作者： S. Negahdaripour X. Xu A. Khamene Z. Awan Underwater Vision and Imaging Laboratory Electrical and Computer Engineering Department University of Miami Coral Gables FL USA

A vision system has been developed in order to support the autonomous operation or operated-assisted missions of AUV and ROV near the ocean bottom. The sea-floor images, acquired by a down-look camera installed on the vehicle, are processed by the vision system in order to detect and estimate its motion in real time. This information is utilized to realize a number of capabilities, including automatic station keeping, navigation and trajectory following, and the construction of a composite (mosaic) image of the sea floor. We describe the system and provide sample results from various experiments for evaluating performance. We also provide examples from ongoing work, planned for implementation on the real-time vision system.

关键词： Motion estimation Machine vision Remotely operated vehicles Real time systems Oceans Cameras Motion detection Vehicle detection Navigation Sea floor

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Topological dimensionality determination and dimensionality reduction based on minimum spanning trees

Topological dimensionality determination and dimensionality ...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： R. Oten R.J.P. de Figueiredo Laboratory for Machine Intelligence Vision and Neural Computing Department of Electrical and Computer Engineering University of California Irvine USA

In the design of multidimensional systems for the analysis of complex data, an intelligent reduction of the data dimensionality is needed to enable its efficient and accurate processing without much loss of information. The underlying data transformation process can be implemented by nonlinearly mapping the high-dimensional data space onto a low-dimensional feature space where the mapping preserves the topological structure of the transformed data in the feature space as much as possible. This method is often referred to as Multidimensional Scaling (MDS). This paper describes a new MDS approach for feature extraction purposes. It consists of a fast hierachical Minimal-Spanning-Tree-based method which minimizes the Sammon's criteria with a genetic algorithm. Results presented show that this new approach is promising for several applications.

关键词： Multidimensional systems Machine intelligence Extraterrestrial measurements Laboratories computer vision Data engineering Design engineering Poles and towers Buildings Data analysis

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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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An Overview and Critical Issues for Research and Education of Intelligent Manufacturing Systems

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IFAC Proceedings Volumes 1998年第15期31卷 679-687页

作者： Peter P. Groumpos Laboratory for Automation and Robotics Department of Electrical and Computer Engineering University of Patras Rion 26500 GREECE Tel. +3061 997295 Fax. +3061 997309

Intelligent Manufacturing Systems is the major challenge that must be met by scientific community in order to develop the next generation sophisticated manufacturing systems. This paper presents an overview of new promising domains, such as fuzzy logic, neural networks and hybrid intelligent control systems, that could be utilised to achieve human intention for more advanced manufacturing systems. The modelling of the supervisor of manufacturing systems using fuzzy cognitive map is proposed and system functionalization architecture is presented. Finally, conclusions of an international symposium on issues and challenges of Manufacturing and Control Education for the 21 st Century are presented.

关键词： Modelling Supervisory Control Fuzzy Neural Systems Intelligent Manufacturing Systems

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Analysis of nonlinear neural network impedance force control for robot manipulators

Analysis of nonlinear neural network impedance force control...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Seul Jung T.C. Hsia Robotics and Computational Intelligence Laboratory Department of Mechatronics Engineering Chungnam National University Taejon South Korea Robotics Research Laboratory Department of Electrical and Computer Engineering University of California슠Davis Davis CA USA

A force tracking nonlinear impedance control scheme using a neural network is introduced. Due to the nonlinear characteristics of the proposed control law, stability has been analyzed. The numerical bound of environment position uncertainty for ensuring robot contact with the environment and to perform desired force tracking has been found. Intensive simulation studies with a three link rotary robot manipulator tracking the surface with a desired force are carried out to confirm the boundary solutions of the proposed scheme under no knowledge of environment surface position and environment stiffness.

关键词： Neural networks Impedance Force control Robots Manipulators Iron Orbital robotics Nonlinear equations Uncertainty Nonlinear control systems

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Application of Fuzzy Cognitive Maps in Large Manufacturing Systems

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IFAC Proceedings Volumes 1998年第20期31卷 521-526页

作者： Chrysostomos D. Stylios Peter P. Groumpos Laboratory for Automation and Robotics Department of Electrical and Computer Engineering University of Patras Rion 26500 GREECE Tel. +30 61 997293 Fax. +30 61 997309

In this paper the application of Fuzzy Cognitive Map (FCM) in controlling a process problem and its use in modelling Supervisory Manufacturing Systems is presented. The description, construction and the mathematical model of Fuzzy Cognitive Map are examined. Then, a chemical process is modelled with FCM and its behaviour is simulated and the application of Fuzzy Cognitive Maps in the mode ling of the Supervisor of Manufacturing Systems is discussed.

关键词： Cognitive Systems Supervision Manufacturing Systems

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Robust feature tracking in underwater video sequences

Robust feature tracking in underwater video sequences

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OCEANS

作者： T. Tommasini A. Fusiello V. Roberto E. Trucco Machine Vision Laboratory Dipartimento di Matematica e Informatica Università di Udine IT Italy Computer Vision Group and Ocean Systems Laboratory Department of Computing and Electrical Engineering Heriot-Watt University UK

The paper proposes a robust feature tracker based on an efficient outlier rejection scheme, suitable for feature tracking in subsea video sequences. We extend the Shi-Tomasi-Kanade scheme (C. Tomasi and T. Kanade, 1991; J. Shi and C. Tomasi, 1994) by introducing a technique for rejecting spurious features. We employ a simple and efficient outlier rejection rule, called X84, and prove that its theoretical assumptions are satisfied in the feature tracking scenario. Experiments with synthetic and real subsea sequence confirm that our algorithm locates and discards unreliable features accurately and consistently, and tracks good features reliably over many frames. We also illustrate quantitatively the benefits introduced by the algorithm with the example of fundamental matrix estimation.

关键词： Robustness Underwater tracking Video sequences computer vision Image sequences Laboratories Stereo vision Optical filters Machine vision Oceans

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A new fuzzy geometric representation for online isolated character recognition

A new fuzzy geometric representation for online isolated cha...

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International Conference on Pattern Recognition

作者： J.-F. Hebert M. Parizeau N. Ghazzali Computer Vision and Systems Laboratory Department of Electrical and Computer Engineering Laval University Sainte-Foy QUE Canada Department of Mathematics and Statistics Laval University Sainte-Foy QUE Canada

Introduces a fuzzy representation for isolated character description. This representation maps a character from its original sequence of 2D coordinates into a fuzzy vector space that can thereafter serve as input to any artificial neural network classifier. Recognition experiments on isolated digits extracted from the UNIPEN database are their conducted to evaluate the performances of the proposed representation using a hybrid Kohonen-perceptron (KP) neural network.

关键词： Character recognition Fuzzy sets Read only memory Handwriting recognition computer vision Laboratories Mathematics Statistics Artificial neural networks Neural networks

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