基于双目视觉和先验加工数据的大型筒件原位位姿感知方法

doi:10.3901/JME.2023.11.129

机械工程学报 ›› 2023, Vol. 59 ›› Issue (11): 129-146.doi: 10.3901/JME.2023.11.129

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基于双目视觉和先验加工数据的大型筒件原位位姿感知方法

郑联语^1,2,3, 付强^1,4, 樊伟^1,2,3, 张学鑫¹, 刘新玉¹, 曹彦生¹

1. 北京航空航天大学机械工程及自动化学院北京 100191;
2. 航空高端装备智能制造技术工业和信息化部重点实验室北京 100191;
3. 数字化设计与制造技术北京市重点实验室北京 100191;
4. 北京电子工程总体研究所北京 100854

收稿日期:2022-11-29 修回日期:2023-02-15 出版日期:2023-06-05 发布日期:2023-07-19
通讯作者: 樊伟(通信作者),男,1989年出生,博士后。主要研究方向为大型复杂构件数字化测量技术、大型构件多机协同自适应加工技术、可重构柔性智能工装技术、智能制造系统数字孪生技术。E-mail:fanwei@buaa.edu.cn
作者简介:郑联语,男,1967年出生,博士,教授,博士研究生导师。主要研究方向为数字化与智能制造技术、可重构柔性制造、制造系统建模与仿真、下一代工业辅助技术及系统。E-mail:lyzheng@buaa.edu.cn;付强,男,1997年出生,硕士。主要研究方向为大部件数字化测量技术。E-mail:qiang_fox@buaa.edu.cn
基金资助:
国防基础科研计划资助项目(JCKY2021204B045)。

In-situ Pose Measurement Method for Large Cylinders Based on Binocular Vision and Prior Processing Data

ZHENG Lianyu^1,2,3, FU Qiang^1,4, FAN Wei^1,2,3, ZHANG Xuexin¹, LIU Xinyu¹, CAO Yansheng¹

1. School of Mechanical Engineering and Automation, Beihang University, Beijing 100191;
2. MIIT Key Laboratory of Intelligent Manufacturing Technology for Aeronautics Advanced Equipments, Ministry of Industry and Information Technology, Beijing 100191;
3. Beijing Key Laboratory of Digital Design and Manufacturing Technology, Beijing 100191;
4. Beijing Institute of Electronic System Engineering, Beijing 100854

Received:2022-11-29 Revised:2023-02-15 Online:2023-06-05 Published:2023-07-19

摘要/Abstract

摘要： 为保证航空航天领域大型筒件最终装配的协调性和互换性，一般在总装前对其安装面进行精加工处理。其中对大型筒件位姿精确感知是保证安装面机器人加工准确性的根本前提，但目前多采用人工划线找正方式对大型筒件进行定位，使得大型筒件定位精度的一致性与其效率无法得到保证。为解决该问题，提出了一种基于双目视觉和先验数据的大型筒件原位位姿感知方法。在该方法中，首先采用深度学习与边缘检测视觉算法可实现对大型筒件关键特征的识别与定位，将关键特征的中心位置定位至一个像素点。基于此，根据双目视觉三维重构方法可实现大型筒件关键特征中心位置的空间坐标求解。同时引入大型筒件的先验数据并结合其关键特征三维重构结果可最终求解出大型筒件的原位位姿(即轴线位姿和轴向偏转角)，并基于上述方法开发了大型筒件原位位姿测量系统。最后以某型号大型筒件为验证对象对所提方法的有效性和可行性进行了实验验证。实验结果表明所提方法及所设计系统能够实现大型筒件原位位姿的有效感知，从而满足大型筒件机器人原位加工的需求。

关键词: 双目视觉, 激光跟踪测量, 先验加工数据, 大型筒件, 位姿测量

Abstract: To ensure the final assembly of large aerospace cylindrical components is coordinated and interchangeable, the reserved machining allowance of the assembly interface of the large component is usually fettled before final assembly. Note that accurate positioning of the large component is critical to ensure the machining accuracy of the assembly interface. However, in the traditional method, the large component is manually marked and aligned, which has a negative impact on the machining quality and efficiency of the assembly surface. To cope with these problems, an in-situ pose measurement method for large cylinders based on binocular vision and prior data is proposed. In this method, the deep learning and edge detection vision algorithms are applied to identify and locate key features of the large cylinder, and the central position of the key feature can be located to a pixel in the original image of the large cylinder. Based on this, the spatial coordinates of the center position of the key feature can be solved using binocular vision 3D reconstruction method. Meanwhile, the actual pose of the large component is finally solved by combining the prior processing data of the large component and the 3D reconstruction results of the key features, which can improve the pose calculation accuracy. Finally, the in-situ pose measurement control system for the large cylinder is developed and validated using the proposed method, and the experimental results illustrate that the developed measurement control system is capable of efficiently realizing high-precision pose perception of the large cylinder in order to meet the production demand of in-situ finish machining of the assembly interface.

Key words: binocular vision, laser tracking measurement, prior processing data, large cylindrical component, pose measurement

中图分类号:

TH164
TH166

郑联语, 付强, 樊伟, 张学鑫, 刘新玉, 曹彦生. 基于双目视觉和先验加工数据的大型筒件原位位姿感知方法[J]. 机械工程学报, 2023, 59(11): 129-146.

ZHENG Lianyu, FU Qiang, FAN Wei, ZHANG Xuexin, LIU Xinyu, CAO Yansheng. In-situ Pose Measurement Method for Large Cylinders Based on Binocular Vision and Prior Processing Data[J]. Journal of Mechanical Engineering, 2023, 59(11): 129-146.

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基于双目视觉和先验加工数据的大型筒件原位位姿感知方法

In-situ Pose Measurement Method for Large Cylinders Based on Binocular Vision and Prior Processing Data

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