作者：
Laengle, ThLueth, T.CUniversity of Karlsruhe
Faculty for Informatics Institute for Real-Time Computer Systems and Robotics 76128 Karlsruhe Prof. Dr.-Ing. U Rembold Prof. Dr.- Ing. R. Dillmann Germany
In a distributed robot system, asynchronous and synchronous communication between the system components is necessary to guarantee problem soliving capability in realtime. On that account, the distributed control archi...
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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. Afte...
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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
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-...
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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.< >
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 Ka...
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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.< >
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 consis...
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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.< >
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 tr...
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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.< >
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...
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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.< >
The development of an advanced planning environment is described, which is especially tailored for the programming and simulating of complex assembly operations with multifinger robot hands. A new geometric-mechanic a...
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The development of an advanced planning environment is described, which is especially tailored for the programming and simulating of complex assembly operations with multifinger robot hands. A new geometric-mechanic approach to the problem of planning grasp parameters for multifinger hands is presented, which considers the constraints of pick-and-place operations in manipulation and insertion tasks. The planning method is subdivided into two successive steps for (1) grasp point planning assertion object reachability and task feasibility, and (2) grasp force planning asserting object stability and grip security. The planning process is connected via a task concept and assembly specific language with the command executer of the planning system which controls both the motion emulation and force simulation.< >
Presents a neuro-fuzzy control approach for intelligent microrobots. Typical tasks of such industrial or medical robots are both exploration and fine manipulation, what demands task planning and motion/force control c...
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Presents a neuro-fuzzy control approach for intelligent microrobots. Typical tasks of such industrial or medical robots are both exploration and fine manipulation, what demands task planning and motion/force control capabilities. For this kind of microsystems the authors investigate the system technical aspects of information processing. The concept for the control system architecture is based on the combination of a neural network approach for the adaptation of process parameters and a fuzzy logic approach for the correction of parameter values given to a conventional controller. A planning component deals with the determination of initial manipulation parameters. Together with a sensor fusion procedure and a supervising and reasoning subsystem this allows reliable operation of a microrobot.< >
A new product model that is particularly useful for model-based assembly planning is presented in this paper. The majority of the models used in this domain are simple approximations of the real workpiece and they are...
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A new product model that is particularly useful for model-based assembly planning is presented in this paper. The majority of the models used in this domain are simple approximations of the real workpiece and they are often dedicated to special algorithms. The model described here provides a more accurate and more flexible representation of workpieces. An increase in accuracy of the shape description was achieved by enhancing a polyhedral model with an analytical representation. The application of the model is demonstrated within the framework of assembly sequence planning.
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