Peng Chi , Zhenmin Wang , Haipeng Liao , Ting Li , Xiangmiao Wu , Jianwen Wu , Qin Zhang
{"title":"一种人形焊接机器人集成标定与三维重建方法","authors":"Peng Chi , Zhenmin Wang , Haipeng Liao , Ting Li , Xiangmiao Wu , Jianwen Wu , Qin Zhang","doi":"10.1016/j.measurement.2025.117748","DOIUrl":null,"url":null,"abstract":"<div><div>Welding, a key process in traditional manufacturing and repair, is evolving towards intelligent automation, with humanoid welding robots (HWR) playing a central role in the next generation of welding technologies. This paper addresses the challenge of rapid coordinate system unification and area identification for HWR by proposing an integrated calibration and three-dimensional (3D) reconstruction method. A multi-camera, multi-IMU, dual robotic arm calibration system is first introduced to precisely define the robot’s coordinate system and enhance calibration accuracy. A novel multi-parameter error optimization method is then proposed, significantly improving calibration precision. This represents the first application of this method to multi-camera-IMU and hand-eye calibration scenarios in the context of welding. Furthermore, the integration of multi-view 3D reconstruction technology, driven by the fusion of the head binocular camera and the RGB-D camera on the left robotic arm, substantially enhances the accuracy of welding area reconstruction. Experimental validation demonstrates the feasibility and effectiveness of the method, achieving an absolute 3D model error of 1.09 ± 0.23 mm, with a 0.99% error rate. Future work will focus on integrating these methods with dual-arm collaborative welding path planning to further advance intelligent welding manufacturing using HWR.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117748"},"PeriodicalIF":5.2000,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An integrated calibration and 3D reconstruction method for humanoid welding robots\",\"authors\":\"Peng Chi , Zhenmin Wang , Haipeng Liao , Ting Li , Xiangmiao Wu , Jianwen Wu , Qin Zhang\",\"doi\":\"10.1016/j.measurement.2025.117748\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Welding, a key process in traditional manufacturing and repair, is evolving towards intelligent automation, with humanoid welding robots (HWR) playing a central role in the next generation of welding technologies. This paper addresses the challenge of rapid coordinate system unification and area identification for HWR by proposing an integrated calibration and three-dimensional (3D) reconstruction method. A multi-camera, multi-IMU, dual robotic arm calibration system is first introduced to precisely define the robot’s coordinate system and enhance calibration accuracy. A novel multi-parameter error optimization method is then proposed, significantly improving calibration precision. This represents the first application of this method to multi-camera-IMU and hand-eye calibration scenarios in the context of welding. Furthermore, the integration of multi-view 3D reconstruction technology, driven by the fusion of the head binocular camera and the RGB-D camera on the left robotic arm, substantially enhances the accuracy of welding area reconstruction. Experimental validation demonstrates the feasibility and effectiveness of the method, achieving an absolute 3D model error of 1.09 ± 0.23 mm, with a 0.99% error rate. Future work will focus on integrating these methods with dual-arm collaborative welding path planning to further advance intelligent welding manufacturing using HWR.</div></div>\",\"PeriodicalId\":18349,\"journal\":{\"name\":\"Measurement\",\"volume\":\"253 \",\"pages\":\"Article 117748\"},\"PeriodicalIF\":5.2000,\"publicationDate\":\"2025-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Measurement\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0263224125011078\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Measurement","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0263224125011078","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
An integrated calibration and 3D reconstruction method for humanoid welding robots
Welding, a key process in traditional manufacturing and repair, is evolving towards intelligent automation, with humanoid welding robots (HWR) playing a central role in the next generation of welding technologies. This paper addresses the challenge of rapid coordinate system unification and area identification for HWR by proposing an integrated calibration and three-dimensional (3D) reconstruction method. A multi-camera, multi-IMU, dual robotic arm calibration system is first introduced to precisely define the robot’s coordinate system and enhance calibration accuracy. A novel multi-parameter error optimization method is then proposed, significantly improving calibration precision. This represents the first application of this method to multi-camera-IMU and hand-eye calibration scenarios in the context of welding. Furthermore, the integration of multi-view 3D reconstruction technology, driven by the fusion of the head binocular camera and the RGB-D camera on the left robotic arm, substantially enhances the accuracy of welding area reconstruction. Experimental validation demonstrates the feasibility and effectiveness of the method, achieving an absolute 3D model error of 1.09 ± 0.23 mm, with a 0.99% error rate. Future work will focus on integrating these methods with dual-arm collaborative welding path planning to further advance intelligent welding manufacturing using HWR.
期刊介绍:
Contributions are invited on novel achievements in all fields of measurement and instrumentation science and technology. Authors are encouraged to submit novel material, whose ultimate goal is an advancement in the state of the art of: measurement and metrology fundamentals, sensors, measurement instruments, measurement and estimation techniques, measurement data processing and fusion algorithms, evaluation procedures and methodologies for plants and industrial processes, performance analysis of systems, processes and algorithms, mathematical models for measurement-oriented purposes, distributed measurement systems in a connected world.