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An automatic shoe-groove feature extraction method based on robot and structural laser scanning:

机译:基于机器人和结构激光扫描的自动鞋纹特征提取方法:

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摘要

In order to improve the operational efficiency of robot-based shoe manufacturing, a method of shoe-groove tracking based on industrial robot is presented in the article. First, side surface of a shoe upper with a sole is scanned with a laser scanning device. The presented approach mainly consists of two steps: reconstruction of three-dimensional point cloud and feature curve extraction. It is difficult to extract the closed groove curve on shoe surface. We propose an innovative method to simplify the feature extraction through projecting geometric information from three dimension to two dimension, which is convenient to identify longest groove feature line in two-dimensional space. After detecting the two-dimensional groove line, we back project it to three-dimensional space to identify the three-dimensional thick groove point set. Finally, we thin and fit the groove curve into a trackable sequential curve. The experimental results show that the proposed system can effectively detect the shoe groove and generate trackable sequential curve. We also simulate the robot tracking process in a virtual environment to demonstrate the effectiveness of the presented method.
机译:为了提高机器人制鞋的生产效率,本文提出了一种基于工业机器人的鞋槽跟踪方法。首先,用激光扫描装置扫描具有鞋底的鞋帮的侧面。提出的方法主要包括两个步骤:三维点云的重构和特征曲线的提取。很难提取鞋表面的闭合凹槽曲线。我们提出了一种创新的方法,通过将几何信息从三维投影到二维,简化了特征提取,这便于识别二维空间中最长的凹槽特征线。在检测到二维凹槽线之后,我们将其反向投影到三维空间以识别三维厚凹槽点集。最后,我们将凹槽曲线细化并拟合为可跟踪的连续曲线。实验结果表明,所提出的系统可以有效地检测出鞋槽并产生可追踪的顺序曲线。我们还模拟了虚拟环境中的机器人跟踪过程,以证明所提出方法的有效性。

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