CLC number: TP391.4
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2014-07-16
Cited: 2
Clicked: 10021
Wei-dong Zhu, Biao Mei, Guo-rui Yan, Ying-lin Ke. Development of a monocular vision system for robotic drilling[J]. Journal of Zhejiang University Science C,in press.Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/jzus.C1300379 @article{title="Development of a monocular vision system for robotic drilling", %0 Journal Article TY - JOUR
用于机器人制孔的单目视觉系统开发研究目的:在航空结构件机器人制孔中,通常通过误差测量和补偿保证制孔位置精度。本文旨在开发一种低成本、高精度的视觉系统,通过集成鲁棒的椭圆特征提取算法、实用的视觉系统标定方法,实现对刀具和工件之间相对误差的精确测量。创新要点:视觉测量相关研究中缺乏对视觉系统工作原理的深入阐释;视觉系统误差测量原理的精确阐述,为视觉系统的开发和测量精度的提高提供了理论基础。机器人制孔环境中存在大量噪声和环境干扰因素,视觉系统中集成的特征提取算法应具有较高的鲁棒性;基于显著性的椭圆轮廓提取算法可实现鲁棒、精确的基准孔检测。工业应用通常要求视觉系统的标定方法兼具实用性和精确性;本文方法提供了一种实用、精确、可同时实现相机和手眼关系标定的标定方法。 方法提亮:精确阐释了视觉系统的工作原理,为后续相机刀具中心点和视觉系统标定方法的确定提供了理论依据。通过集成显著性计算、投票方法和Snake模型,开发了一种鲁棒、精确的椭圆轮廓特征提取算法(图8)。提出了一种基于专用标定板的、可同时实现相机内参数和手眼关系标定的视觉系统标定方法,该方法可避免测量过程引入Abbe误差(图12)。 重要结论:本文研究了视觉测量系统的工作原理,并结合提出的椭圆轮廓提取算法、视觉系统标定方法,开发了一种低成本、满足机器人制孔精度要求的单目视觉测量系统。在机器人制孔系统平台上的实验证实,本文提出的视觉系统满足航空工业对制孔精度的要求,特征提取算法和标定方法鲁棒、有效。 视觉系统;机器人制孔;误差测量;椭圆轮廓提取;手眼关系标定 Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article
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