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KNOWLEDGE-BASED ROBOT VISION SYSTEM FOR AUTOMATED PART HANDLING

机译:基于知识的自动化零件处理机器人视觉系统

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摘要

This paper discusses an algorithm incorporating a knowledge-based vision system into an industrial robot system for handling parts intelligently. A continuous fuzzy controller was employed to extract boundary information in a computationally efficient way. The developed algorithm for on-line part recognition using fuzzy logic is shown to be an effective solution to extract the geometric features of objects. The proposed edge vector representation method provides enough geometric information and facilitates the object geometric reconstruction for gripping planning. Furthermore, a part-handling model was created by extracting the grasp features from the geometric features. [PUBLICATION ABSTRACT]
机译:本文讨论了一种将基于知识的视觉系统集成到工业机器人系统中以智能处理零件的算法。采用连续模糊控制器以计算有效的方式提取边界信息。所开发的模糊逻辑在线零件识别算法被证明是提取物体几何特征的有效解决方案。提出的边缘矢量表示方法提供了足够的几何信息,并有助于对象几何结构的重构以进行抓取规划。此外,通过从几何特征中提取抓取特征来创建零件处理模型。 [出版物摘要]

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  • 来源
    《South African Journal of Industrial Engineering》 |2008年第1期|p.119-130|共12页
  • 作者单位

    J. Wang 1 ,T.I. van Niekerk2, D.G. Hattingh3 and T. Hua42,3,4 Faculty of Engineering, the Built Environment and Information TechnologyNelson Mandela Metropolitan University, South Africatheo.vanniekerk@nmmu.ac.za1School of Mechanical and Automotive EngineeringHefei University of Technology, Chinayangwang@mail.hf.ah.cn;

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