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IEEE International Conference on robotics and Automation (ICRA)

作者： S.I. Roumeliotis G.S. Sukhatme G.A. Bekey Department of Electrical Engineering University of Southern California Los Angeles CA USA Department of Computer Science Institute for Robotics and Intelligent Systems University of Southern California Los Angeles CA USA

The mobile robot localization problem is decomposed into two stages; attitude estimation followed by position estimation. The innovation of our method is the use of a smoother, in the attitude estimation loop that outperforms other Kalman filter based techniques in estimate accuracy. The smoother exploits the special nature of the data fused; high frequency inertial sensor (gyroscope) data and low frequency absolute orientation data (from a compass or sun sensor). Two Kalman filters form the smoother. During each time interval one of them propagates the attitude estimate forward in time until it is updated by an absolute orientation sensor. At this time, the second filter propagates the recently renewed estimate back in time. The smoother optimally exploits the limited observability of the system by combining the outcome of the two filters. The system model uses gyro modeling which relies on integrating the kinematic equations to propagate the attitude estimates and obviates the need for complex dynamic modeling. The indirect (error state) form of the Kalman filter is developed for both parts of the smoother. The proposed approach is independent of the robot structure and the morphology of the ground. It can easily be transferred to another robot which has an equivalent set of sensors. Quaternions are used for the 3D attitude representation mainly for practical reasons discussed in the paper. Proposed innovative algorithm is tested in simulation and the overall improvement in position estimation is demonstrated.

关键词： Mobile robots Frequency Sensor fusion Filters Robot sensing systems Technological innovation Gyroscopes Sun Observability Kinematics

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Fusion of soft computing and hard computing techniques: a review of applications

Fusion of soft computing and hard computing techniques: a re...

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IEEE International Conference on systems, Man and Cybernetics

作者： S.J. Ovaska Y. Dote T. Furuhashi A. Kamiya H.F. VanLandingham Institute of Intelligent Power Electronics Helsinki University of Technology Finland Department of Computer Science and Systems Engineering Muroran Institute of Technology Muroran Japan Department of Information Electronics University of Nagoya Nagoya Japan Power and Industrial Systems Research and Development Center Power Systems and Services Company Toshiba Corporation Fuchu Tokyo Japan The Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Blacksburg VA USA

Soft computing (SC) is an emerging collection of methodologies, which aim to exploit tolerance for imprecision, uncertainty, and partial truth to achieve robustness, tractability, and low total cost. It differs from conventional hard computing (HC) in the sense that, unlike hard computing, it uses intuition or subjectivity. Therefore, soft computing provides an attractive opportunity to represent ambiguity in human thinking with the real life uncertainty. Fuzzy logic (FL), neural networks (NN), and genetic algorithms (GA) are the core methodologies of soft computing. However, FL, NN, and GA should not be viewed as competing with each other but synergistic and complementary instead, as emphasized by Dr. Zadeh . Considering the available literature, it is easy to conclude that the fusion of individual soft computing methodologies has been advantageous in numerous applications. In this paper, we give a review of applications where the fusion of soft computing and hard computing has provided innovative solutions for demanding real-world problems. A representative list of references is provided with evaluative discussions and conclusions.

关键词： Neural networks Uncertainty Fuzzy logic Application software Research and development Robustness Costs Power electronics computer science Power engineering and energy

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Robust and efficient cluster analysis using a shared near neighbours approach

Robust and efficient cluster analysis using a shared near ne...

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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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Multi-loop control approach to designing iterative learning controllers

Multi-loop control approach to designing iterative learning ...

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IEEE Conference on Decision and Control

作者： K.L. Moore Center for Self-organizing and Intelligent systems Department of Electrical and Computer Engineering Utah State University Logan UT USA

In this paper we consider convergence of iterative learning control (ILC) algorithms. We use a multiloop control interpretation of the signal flow in ILC to derive a necessary and sufficient condition for convergence of discrete-time, linear, time-invariant systems. We then use our multiloop approach to develop an iterative learning control algorithm that can converge in as few as four trials. The scheme uses an adaptive (in trial number) gain adjustment that does not have to be "tuned". This is combined with the use of feedforward correction terms (in time) to produce the complete algorithm. A simulation illustrates the effectiveness of the strategy. The paper concludes with comments on how the multiloop approach can be used to address (i) higher-order ILC schemes for dealing with noise in the process and with initial state uncertainty (using a Kalman filter in trial number); (ii) ILC convergence for nonlinear and time-varying systems; and (iii) the adaptive gain adjustment rule.

关键词： Iterative methods Convergence Control systems Iterative algorithms Uncertainty Algorithm design and analysis intelligent systems Sufficient conditions Time varying systems Error correction

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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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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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Design of fuzzy querying in object-oriented spatial data and geographic information systems

Design of fuzzy querying in object-oriented spatial data and...

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： A. Morris F.E. Petry Center for Intelligent and Knowledge Based Systems Department of Electrical Engineering and Computer Science Tulane University New Orleans LA USA

Fuzzy set approaches are particularly suitable for issues of modeling uncertainty in spatial data. The authors survey where and how uncertainty may appear in spatial data. They consider the issues involved in developing the modeling of uncertain spatial data in the framework of object-oriented databases. Finally they outline the issues in an approach for implementing fuzzy spatial queries in a commercially available object-oriented database.

关键词： Fuzzy systems Geographic Information systems Spatial databases Uncertainty Object oriented databases Educational institutions Fuzzy sets Object oriented modeling Fires Information systems

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Kinematic manipulability of general constrained rigid multibody systems

Kinematic manipulability of general constrained rigid multib...

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IEEE International Conference on robotics and Automation (ICRA)

作者： J.T. Wen L.S. Wilfinger Center for Advanced Technology in Automation Robotics & Manufacturing Department of Electrical Computer & Systems Engineering Rensselaer Polytechnic Institute RPI Troy NY USA

Extends the kinematic manipulability concept commonly used for serial manipulators to general constrained rigid multibody systems. Examples of such systems include multiple cooperating manipulators, multiple fingers holding a payload, multi-leg walking robots, and variable geometry trusses. Explicit formulas for velocity and force manipulability ellipsoids are derived and their duality explained. The concept of unstable grasp and manipulable grasp are also extended and illustrated with examples.

关键词： Kinematics Torque Ellipsoids Manufacturing automation robotics and automation computer aided manufacturing Manipulators Fingers Legged locomotion Robots

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Autonomous mobile robot global self-localization using Kohonen and region-feature neural networks

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Journal of Field robotics 1998年第4期14卷

作者： Jason A. Janét Ricardo Gutierrez Troy A. Chase Mark W. White John C. Sutton III Center for Robotics and Intelligent Machines Department of Electrical and Computer Engineering North Carolina State University Raleigh NC 27695-7911

This article presents and compares two neural network-based approaches to global self-localization (GSL) for autonomous mobile robots using: (1) a Kohonen neural network, and (2) a region-feature neural network (RFNN). Both approaches categorize discrete regions of space (topographical nodes) in a manner similar to optical character recognition (OCR). That is, the mapped sonar data assumes the form of a character unique to that region. Hence, it is believed that an autonomous vehicle can determine which room it is in from sensory data gathered from exploration. With a robust exploration routine, the GSL solution can be time-, translation-, and rotation-invariant. The GSL solution can also become independent of the mobile robot used to collect the sensor data. This suggests that a single robot can transfer its knowledge of various learned regions to other mobile robots. The classification rate of both approaches are comparable and, thus, worthy of presentation. The observed pros and cons of both approaches are also discussed. © 1997 John Wiley & Sons, Inc.

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Autonomous mobile robot global motion planning and geometric beacon collection using traversability vectors

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IEEE TRANSACTIONS ON robotics AND AUTOMATION 1997年第1期13卷 132-140页

作者： Janet, JA Luo, RC Kay, MG Center for Robotics and Intelligent Machines Department of Electrical and Computer Engineering North Carolina State University Raleigh NC USA

Approaches in global motion planning (GMP) and geometric beacon collection (for self-localization) using traversability vectors have been developed and implemented in both computer simulation and actual experiments on mobile robots. Both approaches are based on the same simple, modular, and multifunctional traversability vector (t-vector). Through implementation it has been found that t-vectors reduce the computational requirements to detect path obstructions, Euclidean optimal via points, and geometric beacons, as well as to identify which features are visible to sensors. Environments can be static or dynamic and polygons are permitted to overlap (i.e., intersect or be nested). While the t-vector model does require that polygons be convex, it is a much simpler matter to decompose concave polygons into convex polygon sets than it is to require that polygons not overlap, which is required for many other GMP models. T-vectors also reduce the data size and complexity of standard V-graphs and variations thereof, This paper presents the t-vector model so that the reader can apply it to mobile robot GMP and self-localization.

关键词： computational geometry collision detection geometric beacon detection/collection mobile robot motion planning range sensor prediction self-localization

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