大型构件机器人原位加工中的测量方案概述

doi:10.3901/JME.2022.14.001

机械工程学报 ›› 2022, Vol. 58 ›› Issue (14): 1-14.doi: 10.3901/JME.2022.14.001

• 特邀专栏：大型构件视觉测量与机器人加工 • 上一篇下一篇

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大型构件机器人原位加工中的测量方案概述

何雨镐¹, 谢福贵^1,2, 刘辛军^1,2, 张旭³

1. 清华大学机械工程系北京 100084;
2. 清华大学精密超精密制造装备及控制北京市重点实验室北京 100084;
3. 上海大学机电工程与自动化学院上海 200444

收稿日期:2021-05-30 修回日期:2022-03-10 出版日期:2022-07-20 发布日期:2022-09-07
通讯作者: 谢福贵(通信作者)，男，1982年出生，博士，副教授，博士研究生导师，国家优秀青年科学基金获得者。主要研究方向为机器人与机构学、先进制造技术及装备。E-mail：xiefg@mail.tsinghua.edu.cn
作者简介:何雨镐，男，2000年出生。主要研究方向为并混联加工机器人。E-mail：he-yh18@mails.tsinghua.edu.cn;刘辛军，男，1971年出生，博士，教授，博士研究生导师，国家杰出青年科学基金获得者。主要研究方向为机器人与机构学、先进制造装备。E-mail：xinjunliu@mail.tsinghua.edu.cn;张旭，男，1982年出生，博士，教授，博士研究生导师。主要研究方向为机器人视觉、光学三维测量。E-mail：xuzhang@shu.edu.cn
基金资助:
国家自然科学基金资助项目(51922057,91948301)。

Review on Measurement Schemes for Robotic Machining of Large Components In-situ

HE Yuhao¹, XIE Fugui^1,2, LIU Xinjun^1,2, ZHANG Xu³

1. Department of Mechanical Engineering(DME), Tsinghua University, Beijing 100084;
2. Beijing Key Lab of Precision/Ultra-precision Manufacturing Equipments and Control, Tsinghua University, Beijing 100084;
3. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444

Received:2021-05-30 Revised:2022-03-10 Online:2022-07-20 Published:2022-09-07

摘要/Abstract

摘要： 面向大型构件的加工方案中，以加工机床为代表的“包容式”加工模式和传统的“分体加工”模式已无法满足高柔性、高效率以及加工质量稳定性和一致性的要求。移动机器人具有轻量化、模块化、灵活性高等优点，为大型复杂构件的高效高精原位加工提供了一种有效的解决方案。移动机器人原位加工过程通常包含自主寻位、精确定位加工与加工质量原位检测三个阶段，将机器人通过自主寻位引导至待加工位置，并精确定位加工，在加工完成后进行原位检测以缩短生产周期。围绕上述过程，对大型构件机器人原位加工中基于视觉和基于激光的测量方案进行综述。在移动机器人的定位导航中，基于视觉和基于激光的测量系统分别因其成本低和数据密度大而得以应用；精确确定刀具与工件的相对位置中，双目视觉相关理论与应用都较成熟，激光跟踪仪也表现出应用潜力；零件表面质量的原位检测中，基于激光技术的检测系统检测效率、精度高，是该过程的理想选择。但现有测量方案仍面临诸多挑战，且单一测量方法难以满足多变的测量需求，随着人工智能理论的发展，多测量手段集成是大型构件机器人原位加工中测量方法的发展趋势。

关键词: 移动机器人, 原位加工, 自主寻位, 精确定位, 表面质量检测

Abstract: Among the machining schemes for large-scale components, the inclusive mode represented by processing machine tools and the traditional mode of split processing can no longer meet the requirements of high flexibility, high efficiency, and stability and consistency of machining quality. With the advantages of light weight, modularity and flexibility, mobile robots provide an effective solution for efficient and high precision in-situ machining of large and complex components. The in-situ machining process of mobile robots usually consists of three stages:autonomous navigation, precise positioning and in-situ detection of machining quality. The robot is guided to the position to be machined by autonomous navigation system, and the machining is performed after precise positioning, and in-situ detection is performed after the machining is completed to shorten the production cycle time. Around the above process, vision-based and laser-based measurement schemes for in-situ machining of large component robots are reviewed. In the positioning and navigation of mobile robots, vision-based and laser-based measurement systems are widely applied due to their low cost and high data density, respectively. In the precise determination of the relative position of the tool and the workpiece, binocular vision-related theories and applications are well established, and the laser tracker also show its application potential. In the in-situ detection of the surface quality of parts, laser technology-based detection systems are efficient and high accuracy, which makes it the ideal choice for this process. However, there still exists many challenges in the present measurement schemes. And it is difficult for a single measurement method to meet the changing measurement needs, and with the development of artificial intelligence theory, the integration of multiple measurement means is the development trend of measurement methods in the machining of large component robots in-situ.

Key words: mobile robot, in-situ machining, autonomous navigation, precise positioning, surface quality detection

中图分类号:

TG156

何雨镐, 谢福贵, 刘辛军, 张旭. 大型构件机器人原位加工中的测量方案概述[J]. 机械工程学报, 2022, 58(14): 1-14.

HE Yuhao, XIE Fugui, LIU Xinjun, ZHANG Xu. Review on Measurement Schemes for Robotic Machining of Large Components In-situ[J]. Journal of Mechanical Engineering, 2022, 58(14): 1-14.

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大型构件机器人原位加工中的测量方案概述

Review on Measurement Schemes for Robotic Machining of Large Components In-situ

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