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Neural-fuzzy force control using a TAI-lorable parallel computer concept

IFAC Proceedings Volumes 1994年第14期27卷 151-156页

作者： S. Fatikow B. Magnussen T. Doersam University of Karlsruhe Faculty for Informatics Institute for Real-Time Computer Systems and Robotics Kaiserstr. 12 76128 Karlsruhe Germany

In this paper a new control system for the intelligent force control of multifingered robot grips is presented. The multi-level system architecture combines both fuzzy-based and a neural-based control algorithms. After defining the fine manipulation problem fuzzy and neural controller are developed. The demands of flexibility and real-time control of the implementation of the control system are suited by a tailorable parallel computer concept. The basic ideas of the concept are to set up each processing element and the communication individually for its application

关键词： Force control fuzzy control neural nets real time computer systems parallel processing

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Intelligent robot hand control system using a tailorable parallel computer concept

Intelligent robot hand control system using a tailorable par...

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IEEE International Workshop on Intelligent Robots and systems (IROS)

作者： S. Fatikow B. Magnussen Th. Dorsam Institute for Real Time Computer Systems and Robotics Faculty for Informatics University of Karlsruhe Karlsruhe Germany

Presents a control system for the intelligent force control of multifingered robot grips. The multilevel system architecture combines both a fuzzy-based adaptation level and a neural-based one with a conventional PID-controller that allows autonomous performance of fine manipulations of an object. Two kinds of fuzzy controllers are presented. They use a decision making logic which expresses the a priori knowledge about the grasp force behaviour inside the friction cones and the necessary reactions regarding the criterion for grip stability. A neural controller, based on a Hooke-Jeeves optimisation approach, has been developed as well. The neural control algorithm is implemented by a three-layered backpropagation neural network. The neural and fuzzy controllers can be used separately or in parallel. In the last case the neural controller can be on-line trained using the input-output information from the fuzzy one. A computer based simulation system for the peg-in-hole insertion task is developed to analyse and to compare the capabilities of both control algorithms. The demands of flexibility and real-time control of the implementation of the control system are suited by a tailorable parallel computer concept. The two basic ideas of the concept are to set up each processing element individually for its application and connect these elements with different communicational methods according to the applicational demands. As this happens before runtime the concept is called static flexibility and is implemented using a new mechanical computer structure.< >

关键词： Intelligent robots Robot control Control systems Fuzzy control Communication system control Force control Intelligent systems Intelligent control Multilevel systems Decision making

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A multi-agent approach to distributed control for task-level programs for cooperating manipulators

A multi-agent approach to distributed control for task-level...

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IEEE International Workshop on Intelligent Robots and systems (IROS)

作者： P. Bohner Institute for Real-Time Computer Systems and Robotics Faculty for InfonnaticS University of Karlsruhe Karlsruhe Germany

The use of two or more robots in a common workspace is essential to expand the field of potential applications. This paper presents a distributed approach for executing task-level programs for cooperating manipulators or one arm systems with many degrees of freedom. At task level, only the movement of the objects to be manipulated is specified. The corresponding manipulator motions are then calculated by assigning the local intelligence to each joint. The local intelligence enables the joint agents to calculate in parallel their appropriate movements to make the end effector reach the desired position. During execution, each joint evaluates the sensor data to compensate for execution errors, to react on unexpected obstacles and to provide the manipulator coordination. Therefore, a distributed fuzzy rule base has been developed. As this local evaluation may lead to non-optimal overall behavior of the manipulator, the joint agents communications provide global suboptimality.< >

关键词： Distributed control Manipulators Mobile robots Robot kinematics Intelligent sensors Intelligent agent Control systems Error correction real time systems Distributed computing

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Requirements for a real-time image processing language

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Annual Review in Automatic Programming 1994年第C期18卷 175-180页

作者： Laplante, P Marlowe, T Stoyenko, A Department of Mathematics and Computer Science Fairleigh Dickinson University Madison NJ 07940 United States also research faculty of the Real-Time Computing Laboratory (CIS NJIT) United States Department of Mathematics and Computer Science Seton Hall University South Orange NJ 07079 United States also research faculty of the Real-Time Computing Laboratory (CIS NJIT) United States Real-Time Computing Laboratory Department of Computer and Information Science New Jersey Institute of Technology Newark NJ 07102 United States

In this paper we discuss issues in real-time image processing, including applications, approaches and hardware. In particular, we discuss the failure of existing programming languages to support these considerations a... 详细信息

关键词： image processing multimedia programming languages real-time virtual reality

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The Karlsruhe dextrous hand: grasp planning, programming and real-time control

The Karlsruhe dextrous hand: grasp planning, programming and...

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IEEE International Workshop on Intelligent Robots and systems (IROS)

作者： G. Wohlke Institute for Real-Time Computer Control Systems and Robotics Faculty for Informatics University of Karlsruhe Karlsruhe Germany

In this paper the framework of an intelligent control system of a multi-finger robot hand is described, that is especially tailored for sensor-based object handling and assembly. The research has concerned with the Karlsruhe dextrous hand, a modular three-finger hand with 9 degrees of freedom, independent finger modules and integrated sensors. The total system structure consists of three embedded subsystems, with a planning and supervisory system on the top, which has a blackboard-like architecture to exchange information with a distributed real-time control system that provides force/position control strategies for dextrous grasping and manipulating of arbitrary objects. A programming and simulation system supports the object/task-based description of all robot and gripper actions required to perform a specific operation.< >

关键词： Robot programming Robotic assembly Force control Intelligent control Robot sensing systems Intelligent robots Assembly systems Fingers Intelligent sensors Strategic planning

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Fuzzy-based grasp-force-adaptation for multifingered robot hands

Fuzzy-based grasp-force-adaptation for multifingered robot h...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： T. Dorsam S. Fatikow I. Streit Institute for Real-Time Computer Systems awl Robotics Faculty for Informatics University of Karlsruhe Karlsruhe Germany

A fuzzy logic approach for the online grasp-force-adaptation, which can be used for the control of fine manipulating with a multifingered robot hand, will be presented in this paper. The kernel of this approach consists of decision making logic which expresses the a-priory knowledge about the force behaviour inside the friction cones and the necessary reactions, regarding the criterion for grip stability. For the software realisation of the fuzzy control approach a Fuzzy-C Development System supporting the entire development process was used. Two corresponding fuzzy controllers have been designed: A finger controller and a grasp controller. During fine manipulations of an object the fuzzy controller interacts with an underlying conventional controller that receives, after defuzzyfication, the adapted force values which were applied. A computer based simulation system was developed to analyse the capabilities of the designed fuzzy controllers.< >

关键词： Robots Fuzzy control Force control Fuzzy logic Kernel Decision making Friction Stability criteria Fingers Computational modeling

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Object manipulation with dextrous multi-finger hands: improved computation method

Object manipulation with dextrous multi-finger hands: improv...

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IEEE International Workshop on Intelligent Robots and systems (IROS)

作者： G. Wohlke Institute for Real-Time Computer Control Systems and Robotics Faculty for Informatics University of Karlsruhe Karlsruhe Germany

This paper deals with the two fundamental problems that occur when objects are manipulated with multi-finger robot hands: the determination of the joint motions to perform a manipulation according to a given object trajectory, and the optimization of the joint torques needed to ensure a stable and secure grip. The consideration of the effect of rolling and slipping of the fingertips at the contact points on the object surface leads to a set of linear differential equations for the joint angles and to a partly nonlinear optimization problem for the joint torques solved by the Hooke-Jeeves algorithm. The removal of redundant information reduces the computational effort to about 40% of the operations required for the standard procedure. Especially, the resulting object motions are demonstrated at an example: the rotation of an ellipsoid object with the fingers of the Karlsruhe dextrous hand.< >

关键词： Robots real time systems Equations Motion control Control systems Fingers Grippers Automatic control Flowcharts Torque control

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time-delay neural networks for control

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IFAC Proceedings Volumes 1994年第14期27卷 967-972页

作者： M. Kaiser University of Karlsruhe Department of Computer Science Institute for Real-Time Computer Systems & Robotics Prof. Dr.-Ing. U. Rembold and Prof. Dr.-Ing. R. Dillmann D-76128 Karlsruhe Germany

This paper presents results regarding the Application of time-Delay Neural Networks (TDNNs), up to now mainly used in speech recognition, for control tasks. A set of examples taken from a model-based robot controller is used to validate the suitability of the TDNN and to show its superiority to standard multilayer perceptrons. Afterwards, a new algorithm is presented that shows how the inherent capability of the TDNN to deal with time-variant signals can be employed to directly generate a TDNN from a PID control law. This synthesized neural controller is operational from the very beginning and can be tuned on-line using existing learning techniques. The advantages of this design procedure are shown for a simple control task.

关键词： Neural nets control system design control system synthesis adaptive control knowledge engineering

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Requirements for a real-time Image Processing Language 1

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IFAC Proceedings Volumes 1994年第6期27卷 175-180页

作者： P. Laplante T. Marlowe A. Stoyenko Department of Mathematics and Computer Science Fairleigh Dickinson University Madison NJ 07940 USA research faculty of the Real- Time Computing Laboratory (CIS NJIT) Department of Mathematics and Computer Science Seton Hall University South Orange NJ 07079 USA Real-Time Computing Laboratory Department of Computer and Information Science New Jersey Institute of Technology Newark NJ 07102 USA

In this paper we discuss issues in real-time image processing, including applications, approaches, and hardware. In particular, we discuss the failure of existing programming languages to support these considerations,... 详细信息

关键词： real-time image processing programming languages virtual reality multimedia

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Utilizing spatial relations for natural language access to an autonomous mobile robot 18th

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18th Annual German Conference on Artificial Intelligence, KI 1994

作者： Stopp, Eva Gapp, Klaus-Peter Herzog, Gerd Laengle, Thomas Lueth, Tim C. SFB 314-Project VITRA FB 14 Informatik Universität des Saarlandes SaarbrückenD-66041 Germany Institute for Real-Time Computer Systems and Robotics Prof. Dr.-Ing. U. Rembold and Prof. Dr.-Ing. R. Dillmann Universität Karlsruhe KarlsruheD-76128 Germany

ISBN: (纸本)9783540584674

Natural language, a primary communication medium for humans, facilitates better human-machine interaction and could be an efficient means to use intelligent robots in a more flexible manner. In this paper, we report on our joint efforts at providing natural language access to the autonomous mobile two-arm robot KAMRO. The robot is able to perform complex assembly tasks. To achieve autonomous behaviour, several camera systems are used for the perception of the environment during task execution. Since natural language utterances must be interpreted with respect to the robot’s current environment the processing must be based on a referential semantics that is perceptually anchored. Considering localization expressions, we demonstrate how, on the one hand, verbal descriptions, and on the other hand, knowledge about the physical environment, i.e., visual and geometric information, can be connected to each other. © 1994, Springer Verlag. All rights reserved.

关键词： Intelligent robots

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