An analysis of the geometry of light-striping vision systems for feedrate control in robot welding and other industrial processes

IF 2.9 Q2 ROBOTICS

Robotics Pub Date : 1987-06-01 DOI:10.1016/0167-8493(87)90004-0

Lynn R. Ziegler, Richard C. Dorf

引用次数: 0

Abstract

Light-stripping, whereby a laser or other source of a stripe of light in conjunction with a single camera can provide three-dimensional information of a scene, can be used to estimate the volume of a seam gap for welding, filling, or gluing robots, and thus provide automated feedrate control. The geometry of light-striping systems is analyzed to yield an efficient method to map the locations of stripe pixels in the image to three-dimensional coordinates. Methods are discussed to determine fill-points by recognizing the pattern produced by seam walls despite noise. Combined with computation of areas and volumes, the steps simplify to an effective algorithm for microprocessor implementation.

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在机器人焊接和其他工业过程中用于进给速度控制的光条视觉系统的几何分析

光剥离，即激光或其他光源的条纹光与单个摄像机相结合，可以提供一个场景的三维信息，可以用来估计焊接，填充或粘合机器人的接缝间隙的体积，从而提供自动进给速度控制。分析了光条纹系统的几何结构，提出了一种将图像中条纹像素的位置映射到三维坐标的有效方法。讨论了在不受噪声影响的情况下，通过识别煤层壁产生的图样来确定填充点的方法。结合面积和体积的计算，这些步骤简化为一种有效的微处理器实现算法。

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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来源期刊

Robotics Mathematics-Control and Optimization

CiteScore

6.70

自引率

8.10%

发文量

114

审稿时长

11 weeks

期刊介绍： Robotics publishes original papers, technical reports, case studies, review papers and tutorials in all the aspects of robotics. Special Issues devoted to important topics in advanced robotics will be published from time to time. It particularly welcomes those emerging methodologies and techniques which bridge theoretical studies and applications and have significant potential for real-world applications. It provides a forum for information exchange between professionals, academicians and engineers who are working in the area of robotics, helping them to disseminate research findings and to learn from each other’s work. Suitable topics include, but are not limited to: -intelligent robotics, mechatronics, and biomimetics -novel and biologically-inspired robotics -modelling, identification and control of robotic systems -biomedical, rehabilitation and surgical robotics -exoskeletons, prosthetics and artificial organs -AI, neural networks and fuzzy logic in robotics -multimodality human-machine interaction -wireless sensor networks for robot navigation -multi-sensor data fusion and SLAM