It is known that the solution of the inverse kinematics problem for robot arms is mathematically very elaborate. A technique is proposed for automatically generating the closed-form inverse kinematics solution for mos...
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It is known that the solution of the inverse kinematics problem for robot arms is mathematically very elaborate. A technique is proposed for automatically generating the closed-form inverse kinematics solution for most industrial robots very efficiently. This is achieved by a careful structural analysis of equations resulting from systems like A/sub i-1//sup -1/ A/sub i-2//sup -1/. . . A/sub 1//sup -1R/T/sub H/=A/sub i/A/sub i+1/. . . A/sub n/ with (i=1, . . ., n), where A/sub i/ and /sup R/T/sub H/ denote the homogeneous transformation matrices between the adjacent robot links and the homogeneous robot hand-base transformation, respectively. Features derived from these equations are described, and it is shown how they can be used advantageously to solve the inverse kinematics problem symbolically. The system is implemented in Prolog and needs a few seconds on a PC for a complete inversion.< >
A three fingered, multijointed robot gripper for experimental use is presented. The mechanics as well as the control architecture is designed for this special purpose. The gripper system provides the basic means in te...
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A three fingered, multijointed robot gripper for experimental use is presented. The mechanics as well as the control architecture is designed for this special purpose. The gripper system provides the basic means in terms of position and force control to perform experiments about grasping and object motion in a useful way. The gripper can be used to develop and evaluate different approaches of stable grasping and object manipulation. Results of the control of the gripper on joint level, the Cartesian behaviour of the fingers and some experiences with the grasping and manipulation experiments using the presented system are reported.< >
The paper is concerned with the problems of rough sets theory and rough classification of objects. It is a new approach to problems from the field of decision-making, data analysis, knowledge representation, expert sy...
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The paper is concerned with the problems of rough sets theory and rough classification of objects. It is a new approach to problems from the field of decision-making, data analysis, knowledge representation, expert systems etc. Several applications (particularly in medical diagnosis and engineering control) confirm the usefulness of the rough sets idea. Rough classification concerns objects described by multiple attributes in a so-called information system. Traditionally, the information system is assumed to be complete, i.e. the descriptors are not missing and are supposed to be precise. In this paper we investigate the case of incomplete information systems, and present a generalization of the rough sets approach which deals with missing and imprecise descriptors.
A concept for the intelligent control of subsystems of a flexible assembly cell is presented. Unknown or uncertain data about the real world may lead towards failure during an assembly task. Therefore, a fault toleran...
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This paper describes a hierarchical robot action planning system for automatic assembly. Input to the system is a geometrical model of the parts to be assembled. The system provides a graphical editor to model the geo...
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Machine learning has been studied for more than 20 years. Most of the recent research contributions are basic and come from the areas of Cognitive Science and Artificial Intelligence. The classical domain of machine l...
Machine learning has been studied for more than 20 years. Most of the recent research contributions are basic and come from the areas of Cognitive Science and Artificial Intelligence. The classical domain of machine learning is related to vision and image analysis and image description. Since about five years there has been encreased activity to apply and to extend these general learning methods to really complex systems such as autonomous robots. The purpose of applied machine learning methods is to facilitate and to aid automatic construction and generation of knowledge based systems and to increase the system performance with time. Autonomous robot systems will operate in an unknown real environment and are based on the interaction of the basic system components such as action planner, plan executive and action monitor which need knowledge about the real world and knowledge about how to behave to reach a given goal. A robot system can learn if it is able to make changes and extensions in its behavioural control structure that enables it to better perform a given task. This includes acquisition of declarative procedural knowledge, the developement of manipulative and cognitive skills through instruction and practice as well as the organisation of knowledge into efficient representations. The purpose of automatic self-configurating or self-modifying representations is to make experience based knowledge available for possible future use in the context of increasing robot system performance. This paper reviews some general methods of machine learning application and some first results achieved to date.
It is shown how structural information from Hough space representations of 2-D images from 3-D scenes can be derived and used to match polyhedra-like objects topologically to 3-D wire-frame models. The matching is per...
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It is shown how structural information from Hough space representations of 2-D images from 3-D scenes can be derived and used to match polyhedra-like objects topologically to 3-D wire-frame models. The matching is performed by an attributed subgraph isomorphism detection algorithm. A subsequent algorithm match can be used to verify the topological match, yielding simultaneously pose information. Simulation results show the method to be a practicable approach for 3-D object recognition.< >
The Karlsruhe Hand is a non-anthropomorphic three finger dextrous gripper with 9 degrees of freedom, which is being developed at the institute for Real-Time computercontrol Systems and robotics of the University of K...
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The Karlsruhe Hand is a non-anthropomorphic three finger dextrous gripper with 9 degrees of freedom, which is being developed at the institute for Real-Time computercontrol Systems and robotics of the University of Karlsruhe.
This paper describes a method to simulate vision for use in robot applications. Our approach shows the physical modeling of the camera, the light sources and the objects within the scene based on a geometric model. Ma...
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This paper describes a method to simulate vision for use in robot applications. Our approach shows the physical modeling of the camera, the light sources and the objects within the scene based on a geometric model. Many parameters of the physical model may be adjusted to obtain simulation results close to reality. For processing of the picture data the SPIDER program is added to the simulation of the camera. Though a complete vision system is created. An example shows the simulation of a CCD-camera and a scene with workpieces taken from the ‘European Benchmark’ [COL85].
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