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Optimal Positioning for Mobile Platform/Manipulator systems using Genetic Algorithms

IFAC Proceedings Volumes 1997年第3期30卷 197-202页

作者： M.W. Chen A.M.S. Zalzala Robotics Research Group Dept. of Automatic Control and Systems Engineering University of Sheffield Sheffield SI 3JD UK

This paper presents a genetic-based approach to multi-criteria position and configuration optimisation of mobile manipulator systems. Optimisation criteria include obstacle avoidance, least joint torque norm, manipulability and joint torque distribution. Due to the competition among various criteria, the multi-criteria optimisation problem typically exhibits many local minima. The emphasis of the paper is put on using genetic algorithms to search for global optimum and solve the minilnax problem for torque distribution. Various simulations for a system including a three-link lnanipulator mounted on a mobile platform show that the proposed genetic algorithm approach performs better than conventional methods.

关键词： robotics genetic algorithems mobile manipulators motion planning parallel algorithms

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FasBack: matching-error based learning for automatic generation of fuzzy logic systems

FasBack: matching-error based learning for automatic generat...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： J.M.C. Izquierdo Y.A. Dimitriadis J.L. Coronado Group of Vision and Robotics. Department of Automatic Electronic and Industrial Electricity School of Industrial Engineering. University of Murcia Murcia Spain Department of Signal Theory Telecommunications and Telematics Enginnering School of Telecommunications Engineering. University of Valladolid Spain Department of Systems Engineering and Control School of Industrial Engineering. University of Valladolid Spain

Many research works have been reported with respect to the relation between neural and fuzzy systems. Looking for a synergistic relation of these technologies, an important property of neural network-based systems is their learning capacity, that permits to embed self-organization in fuzzy logic systems. In this paper, a new neuro-fuzzy system, called FasBack, is proposed, that combines learning based on prediction error minimization and pattern matching. FasBack adds error-based learning to a previously proposed model, called FasArt, which extended and formalized neural networks models of the ART family, as fuzzy logic systems. Experimental results are presented in nonlinear systems identification problems, typically used in the literature.

关键词： Fuzzy logic control systems Fuzzy systems Hardware Industrial engineering Neural networks Subspace constraints System performance Service robots Robot vision systems

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Transputer based GA motion control for PUMA robot

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MECHATRONICS 1996年第3期6卷 349-365页

作者： Wang, Q Zalzala, AMS Robotics Research Group Department of Automatic Control and Systems Engineering University of Sheffield Mappin Street Sheffield S1 3JD U.K.

A new control system is described for the PUMA 560 industrial robotic manipulator based on transputer networks, where both the hardware and software designs are detailed. A Transputer Interface Board (TIE) establishing a transputer link to the 6503 microprocessors of the PUMA arm joints has been designed, built and tested successfully. In addition to hardware implementation, software testing for this new system had been accomplished. The new system can communicate with the PUMA lower level controller at a much shorter period (i.e. 1.75 ms) than the default 28 ms. Genetic Algorithms are used to plan the PUMA robot minimum-time motion trajectory, which is not possible by the traditional exhaustive search method. Real-time experiments have been carried out based on the new PUMA control platform, and show a very good match with simulations. controlled by the new system, PUMA perfoms better when it is interfaced with the shorter time period. Copyright (C) 1996 Elsevier Science Ltd.

关键词： Robotics

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Embedding objects into Matlab/Simulink for process supervision

Embedding objects into Matlab/Simulink for process supervisi...

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IEEE International Symposium on Computer Aided control System Design (CACSD)

作者： J. Melendez J. Colomer J.L. de la Rosa J. Aguilar-Martin J. Vehi Systems Engineering and Automatic Control Group EIA department University of Girona Catalonia Spain

This paper introduces how artificial intelligence technologies can be integrated into a known computer aided control system design (CACSD) framework, Matlab/Simulink, using an object oriented approach. The aim is to build a framework to aid supervisory systems analysis, design and implementation. The idea is to take advantage of an existing CACSD framework, Matlab/Simulink, so that engineers can proceed: first to design a control system, and then to design a straightforward supervisory system of the control system in the same framework. Thus, expert systems and qualitative reasoning tools are incorporated into this popular CACSD framework to develop a computer aided supervisory system design (CASSD) framework. Object-variables an introduced into Matlab/Simulink for sharing information between tools.

关键词： MATLAB control systems Object oriented modeling Expert systems Mathematical model automatic control systems engineering and theory Libraries Artificial intelligence Design engineering

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Model-Based Neural Network Compensation for Uncertainties of Robotic Arms

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IFAC Proceedings Volumes 1996年第1期29卷 157-162页

作者： S.M. Ziauddin A.M.S. Zalzala Robotics Research Group Department of Automatic Control and Systems Engineering University of Sheffield Mappin Street Sheffield SI 3JD UK.

This paper proposes a decentralised compensation scheme for unstructured uncertainties and modelling errors of robotic manipulators. The scheme employs a central decoupler and independent joint neural network compensators. Recursive Newton Euler formulas are used to decouple robot dynamics to obtain a set of equations in terms of input and output of each joint. Each joint sub-system is then controlled separately by neural network controllers which suppress the effects of uncertainties associated with the model. Multi-layered perceptrons using back-propagation learning algorithm are employed as the adaptive elements in the control scheme. The effectiveness of the proposed scheme is demonstrated by a simulation experiment on PUMA 560. Simulation results show that this control scheme achieves fast and precise robot motion control under substantial model inaccuracies. Properties of the neural compensation technique are compared with those of a globally stable adaptive controller.

关键词： Neural networks Adaptive control Model-based control Robotics

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Investigations into Robotic Multi-Joint Motion Considering Multi-Criteria Optimisation Using Genetic Algorithms

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IFAC Proceedings Volumes 1996年第1期29卷 301-306页

作者： Q. Wang A.M.S. Zalzala Robotics Research Group Department of Automatic Control and Systems Engineering The University of Sheffield Mappin Street Sheffield SI 3JD U.K.

The search for minimum-time motion of an articulated mechanical arm by tessellating the joint space involves heavy computational burden. In this work, Genetic Algorithms (GAs) are used to tackle this problem while considering different optimisation criteria, namely, minimum motion time, constraints on torque commands and constraints on end-point velocities. In addition, the search algorithm considers all constraints imposed on the manipulator design, including bounds on motor torque values. Several case studies are simulated for a two joint planner arm as well as for the PUMA 560 industrial manipulator, with results showing much better performance than those reported in the literature.

关键词： Time-optimal Motion Genetic Algorithms Heuristic Search Dynamic Scaling Robot Arms

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A comparison of fuzzy and qualitative control techniques

A comparison of fuzzy and qualitative control techniques

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IEEE International Symposium on Intelligent control (ISIC)

作者： J.L. de la Rosa A. Oiler J. Melendez J. Colomer S. Esteva J.A. Ramon C. Pous J. Vehi Systems Engineering and Automatic Control Group Department d' Electrònica Informàtica i Automàtica University of Girona Girona Spain

This paper attempts to explain an example of applying fuzzy vs. qualitative techniques to a tracking control problem. In the first instance, the qualitative technique is considered as fuzzy controllers with less knowledge. This facility can make qualitative control more feasible for certain problems when little precision is necessary. It is possible to build up models of systems with shallow knowledge about the systems' inner structure just by following their behaviour. The common utility of both techniques is to design simple-to-understand controllers on difficult-to-control systems, based on qualitative and fuzzy reasoning. One interesting side-feature of this study is the intersection of qualitative reasoning, fuzzy control and mobile tracking. The goal is to use the minimum information to control an auto-guided vehicle that, by qualitative-fuzzy reasoning, is able to track another mobile object and to keep a constant distance.

关键词： Fuzzy control automatic control control systems Vehicles Robot vision systems Cameras systems engineering and theory Fuzzy systems Knowledge engineering Process control

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AN IMPLEMENTATION OF FAST GLOBALLY-STABLE ADAPTIVE ROBOT control ON A MULTIPROCESSOR NETWORK

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control engineering PRACTICE 1995年第11期3卷 1553-1562页

作者： ZIAUDDIN, SM ZALZALA, AMS Department of Automatic Control and Systems Engineering Robotics Research Group University of Sheffield Mappin Street Sheffield Sl 4DU UK

This paper is concerned with efficient and fast computations of adaptive control algorithms for robot manipulators. Adaptive controllers employing the highly coupled and non-linear dynamics of manipulators are computationally complex, which presents a major obstacle in their real-time implementation for industrial applications. A solution to this problem is suggested by utilising a parallel-processing approach. The controller algorithm is implemented for a robot manipulator with six degrees of freedom, utilising a transputer network, for which programming is performed in C. The execution times achieved by the distributed algorithm are well within the limit acceptable for real-time control.

关键词： ADAPTIVE control ROBOTIC MANIPULATORS GLOBAL STABILITY PARALLEL PROCESSING MULTIPROCESSORS

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Transputer control System with a GAs Motion Planner for the PUMA560 Industrial Robotic Manipulator

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IFAC Proceedings Volumes 1995年第22期28卷 77-82页

作者： Q. Wang A.M.S. Zalzala Robotics Research Group Department of Automatic Control & Systems Engineering University of Sheffield Mappin Street Sheffield SI 3JD UK

This paper describes a new control system for the PUMA 560 industrial robotic manipulator based on transputer networks, where both the hardware and software designs are detailed. A Transputer Interface Board (ТIB) establishing a transputer link to the 6503 microprocessors of the PUMA arm joints has been designed, built and tested. In addition to hardware implementation, software testing for this new system has been successfully accomplished. A great deal of flexibility can be achieved with this new system, yet without many difficulties, where it can be used as a platform to implement advanced control algorithms and develop sensor-based intelligent robotic structures which need much more computational power. Genetic Algorithms are used to plan the PUMA robot motion trajectory based on the new PUMA control platform, and the motion planner runs concurrently with the controller. Real-time experiments show that PUMA moves much more smoothly along the optimum planned trajectory.

关键词： Robot control Motion Planning Genetic Algorithms (GAs) Distributed control Interfaces

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A virtual environment for real-time interaction with robotic systems

A virtual environment for real-time interaction with robotic...

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IEE Colloquium on Innovations in Manufacturing control Through Mechatronics

作者： A.P. Shepperson A.M.S. Zalzala University of Sheffield UK Robotics Research Group Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

A virtual environment was created which mimicked the real-world operation of the LongArm robotic system. In addition to considering an exact model of the physical system, online two-way data exchange between the actual robot and its virtual counterpart makes actual real-time interaction possible. The designed interface allows the operator to experiment in the virtual mode with any commands later executed on the real system. There is an option to view a second set of graphics showing the kinematic relationships between the joints of the robot. This prototype is intended as an initial investigation into the design of virtual environments for the real-time control of dynamic systems.

关键词： Virtual reality Telerobotics Interactive systems Real time systems Robot programming Manipulator kinematics

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