工业机器人的目标策略

Yi Zhang, Hang Zhang, Xiaodong Xu, Jianchun Dai
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引用次数: 0

摘要

为了解决工业机器人爬行时定位目标效率低的问题,提出了一种结合MeanShift算法和SURF算法的分层目标定位策略,实现了目标的快速准确定位。首先,根据双目视觉系统采集到的目标物体图像信息,采用MeanShift算法对目标图像信息进行裁剪进行初始处理;然后,利用SURF算法对特征点进行匹配,该算法具有良好的计算优势和可重复性、唯一性和鲁棒性。最后,将匹配的特征点与三角测量原理相结合,精确定位目标的三维坐标。实验证明,本文方法提高了机器人爬行识别的速度和精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Target Strategy for Industrial Robots
In order to solve the problem of low efficiency in the process of locating objects when the industrial robot performs a crawling operation, a hierarchical object localization strategy combining MeanShift algorithm and SURF algorithm is proposed to locate the objects quickly and accurately. Firstly, the MeanShift algorithm is used for cutting out the target image information for initial processing, according to the target object image information collected by the binocular vision system. Then, the feature points are matched by the SURF algorithm with good computational superiority and repeatability, uniqueness and robustness. Finally, the matching feature points are combined with the triangular measurement principle to accurately locate the three-dimensional coordinates of the object. The experiment proves that the method of this paper has improved the speed and precision of the recognition of the robot crawling.
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