智能制造测量机器人关键技术研究综述

doi:10.3901/JME.2024.16.001

机械工程学报 ›› 2024, Vol. 60 ›› Issue (16): 1-18.doi: 10.3901/JME.2024.16.001

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智能制造测量机器人关键技术研究综述

王耀南¹, 谢核¹, 邓晶丹¹, 毛建旭¹, 李文龙², 张辉¹

1. 湖南大学机器人学院长沙 410082;
2. 华中科技大学智能制造装备与技术全国重点实验室武汉 430074

收稿日期:2023-12-21 修回日期:2024-05-25 出版日期:2024-08-20 发布日期:2024-10-21
作者简介:王耀南,男,1957年出生,教授,中国工程院院士。主要研究方向为机器人感知与控制。E-mail:yaonan@hnu.edu.cn
谢核(通信作者),男,1990年出生,博士,副教授。主要研究方向为机器人测量。E-mail:xiehe@hnu.edu.cn
邓晶丹,女,2001年出生。主要研究方向为三维检测。E-mail:dengjingdan@hnu.edu.cn
毛建旭,男,1974年出生,博士,教授。主要研究方向为机器人视觉检测。E-mail:maojianxu@hnu.edu.cn
李文龙,男,1980年出生,博士,教授。主要研究方向为机器人三维测量。E-mail:wlli@hust.edu.cn
张辉,男,1983年出生,博士,教授。主要研究方向为机器人视觉检测。E-mail:zhanghui1983@hnu.edu.cn
基金资助:
国家重点研发计划(2023YFB4704800)、国家自然科学基金(62203160，62293512，62293515)、湘江实验室重大(22xj01006)和中央引导地方科技发展基金(2023ZYT003-1)资助项目。

Overview of Key Technologies for Measurement Robots in Intelligent Manufacturing

WANG Yaonan¹, XIE He¹, DENG Jingdan¹, MAO Jianxu¹, LI Wenlong², ZHANG Hui¹

1. School of Robotics, Hunan University, Changsha 410082;
2. State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074

Received:2023-12-21 Revised:2024-05-25 Online:2024-08-20 Published:2024-10-21

摘要/Abstract

摘要： 复杂曲面构件是航空航天、海洋舰船等领域高端装备的核心组成部分，其测量精度对保障高端装备制造品质具有不可替代的基础支撑作用。为克服传统手工、专机等制造方式的局限性，三维视觉引导的机器人系统为复杂曲面构件的高端化智能化加工提供新思路，并逐渐成为机器人化智能制造领域的研究热点。综述围绕机器人三维测量方法，首先根据传感器类型和应用场景，对不同制造场景的测量方案特点进行全面归纳，以帮助研究人员快速全面地认识和理解该领域。然后按照测量流程，将关键核心技术归纳为系统标定、测量规划、点云融合、特征识别等，综述各类别近十年的主要研究成果，分析现有研究存在的不足。最后总结机器人测量面临的技术挑战，并从应用场景、测量需求、测量手段等方面对未来的发展趋势进行了展望。

关键词: 智能制造, 机器人测量, 系统标定, 扫描规划, 特征识别

Abstract: Complex curved components are the core elements of high-end equipment in fields such as aerospace and marine vessels, and their measurement accuracy plays an irreplaceable role in ensuring the quality of high-end equipment manufacturing. To overcome the limitations of traditional manual and specialized manufacturing methods, vision-guided robotic systems provide a new approach for the high-end and intelligent processing of complex curved components, gradually becoming a research hot spot in the field of robotic intelligent manufacturing. Focusing on the 3D measurement methods of robots, this review first summarizes the characteristics of measurement schemes in different manufacturing scenarios according to sensor types and application scenarios, so as to help researchers quickly and comprehensively understand this field. Then, according to the measurement process, key core technologies are categorized as system calibration, measurement planning, point cloud fusion, feature recognition, etc. The major research achievements in various categories over the past decade are reviewed, and the existing research limitations are analyzed. Finally, the technical challenges faced by robotic measurement are summarized, and future development trends are discussed from the perspectives of application scenarios, measurement requirements, measurement methods, etc.

Key words: intelligent manufacturing, robotic measurement, system calibration, scanning planning, feature recognition

中图分类号:

TP242

王耀南, 谢核, 邓晶丹, 毛建旭, 李文龙, 张辉. 智能制造测量机器人关键技术研究综述[J]. 机械工程学报, 2024, 60(16): 1-18.

WANG Yaonan, XIE He, DENG Jingdan, MAO Jianxu, LI Wenlong, ZHANG Hui. Overview of Key Technologies for Measurement Robots in Intelligent Manufacturing[J]. Journal of Mechanical Engineering, 2024, 60(16): 1-18.

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智能制造测量机器人关键技术研究综述

Overview of Key Technologies for Measurement Robots in Intelligent Manufacturing

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