Feature point recognition for the direct teaching data in industrial robot

Taeyong Choi, Chanhun Park, J. Kyung
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引用次数: 4

Abstract

Direct teaching in the industrial robot are the novel technique to teach manipulator with easy usage. However, teaching data by human hand cannot help having large noise error ranged low and high frequency. To use teaching data, post processing to correct teaching trajectory are required. Here, the intuitive feature point recognition method to rebuild teaching data with curvature information is proposed.
工业机器人直接教学数据的特征点识别
在工业机器人中直接教学是一种易于使用的机械手教学新技术。然而,人工教学数据难免存在较大的低频和高频噪声误差。为了利用教学数据,需要对教学数据进行后处理以纠正教学轨迹。本文提出了一种基于曲率信息的直观特征点识别方法来重建教学数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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