The use of multisensor integration and fusion enables a multisensor-based mobile robot to operate in uncertain or unknown dynamic environments. After first distinguishing between multisensor integration and the more r...
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A flexible robotic system with intelligent sensory capability which can be used in an industrial environment to autonomously perform sophisticated manufacturing tasks that are typically done by manual labor is present...
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Issues concerning the effective integration of multiple sensors into the operation of intelligentsystems are presented, and a description of some of the general paradigms and methodologies that address this problem i...
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In this paper, the usefulness of applying the complex as well as ordinary moment features for similar object recognition using a tactile array sensor has been explored. Some complex moment invariants have been derived...
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Current Artificial Intelligence can be used to good effect in engineeringsystems for emulating some high-level mental functions of humans but is not suitable for coping with many other difficult tasks, especially tho...
A robotic system that can visually track and intercept an arbitrary object which is traveling at an unknown velocity on a conveyor has been presented. A fiber-optic eye-in-hand vision system developed at NCSU is used ...
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A robotic system that can visually track and intercept an arbitrary object which is traveling at an unknown velocity on a conveyor has been presented. A fiber-optic eye-in-hand vision system developed at NCSU is used as an integral part of the entire tracking system. The eye-in-hand system is used to characterize the object trajectory in real time, using a modified optical flow approach. A control strategy has been developed which utilizes the kinematic data that are extracted by the tracking algorithm to intercept the moving object. An overall system configuration and its basic principles are described. The demonstration of the initial results is presented.< >
A system is presented which automatically constructs an assembly partial-order graph from an object-oriented model describing parts and their connections. The construction is based on the principle of assembly by disa...
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A system is presented which automatically constructs an assembly partial-order graph from an object-oriented model describing parts and their connections. The construction is based on the principle of assembly by disassembly and on assembly heuristics representing criteria for preferred subassemblies. The system first identifies disassemblable parts and subassemblies by reasoning geometric and physical constraints as well as resource requirements, and then assigns preference to the identified disassembly options based on assembly heuristics. The recursive application of this process to the selected disassemblies results in a hierarchical partial-order graph (HPOG). The HPOG not only specifies the required precedence in part assembly but also provides parallelism for implementing multiple-robot distributed and cooperative assembly. The software is organized under the cooperative-problem-solving paradigm.< >
The authors present a learning expert system which enables a robot to acquire fine motion skills automatically. The system follows the paradigm of Expert Assisted Robot Skill Acquisition (EARSA) proposed by the author...
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The authors present a learning expert system which enables a robot to acquire fine motion skills automatically. The system follows the paradigm of Expert Assisted Robot Skill Acquisition (EARSA) proposed by the authors (1987). EARSA is mainly concerned with the self-discovery of skills by a robot in conjunction with the transfer of human skills to a robot and emphasizes the distinctive difference in perceptual and physical capabilities between a human and a robot. The authors review the theory and mechanism of EARSA, describe the robot fine motion skill learning algorithm formulated on the basis of EARSA, and present the details of simulation on the robot learning of two-dimensional peg-hole insertion skills. The results of simulation indicate the dramatic improvement of performance as a result of skill learning.< >
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