Evan Rolland , Yasser Krim , Ahmed Joubair , Ilian A. Bonev , Evan Jones , Pengpeng Zhang , Cheng Sun , Nanzhu Zhao
{"title":"Novel calibration method for robotic bottom-up vat polymerization additive manufacturing systems","authors":"Evan Rolland , Yasser Krim , Ahmed Joubair , Ilian A. Bonev , Evan Jones , Pengpeng Zhang , Cheng Sun , Nanzhu Zhao","doi":"10.1016/j.rcim.2025.103059","DOIUrl":null,"url":null,"abstract":"<div><div>This article presents a new affordable calibration method for a 7-axis robotic system used for vat polymerization 3D printing. The method employs three metrology elements: a calibration robot end-effector with three precision balls, a measurement probe composed of three linear gauges, and, notably, a kinematic coupling allowing the precise positioning of the probe onto the resin tank in three locations. The robotic system comprises a Mecademic Meca500 6-axis industrial robot mounted on a Zaber X-LRQ300AP linear guide. The calibration method consists of automatically aligning the centers of each of the three precision balls with the probe origin. This alignment is performed with different robot joint angles and linear guide displacements, and for all three locations of the probe. After calibration, the relative accuracy of the 7-axis robotic system with respect to the resin tank, as validated using a laser tracker, is improved from 1.272 mm to 0.271 mm, which is comparable to what can be achieved with significantly more expensive metrology equipment.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"97 ","pages":"Article 103059"},"PeriodicalIF":9.1000,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotics and Computer-integrated Manufacturing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0736584525001139","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
This article presents a new affordable calibration method for a 7-axis robotic system used for vat polymerization 3D printing. The method employs three metrology elements: a calibration robot end-effector with three precision balls, a measurement probe composed of three linear gauges, and, notably, a kinematic coupling allowing the precise positioning of the probe onto the resin tank in three locations. The robotic system comprises a Mecademic Meca500 6-axis industrial robot mounted on a Zaber X-LRQ300AP linear guide. The calibration method consists of automatically aligning the centers of each of the three precision balls with the probe origin. This alignment is performed with different robot joint angles and linear guide displacements, and for all three locations of the probe. After calibration, the relative accuracy of the 7-axis robotic system with respect to the resin tank, as validated using a laser tracker, is improved from 1.272 mm to 0.271 mm, which is comparable to what can be achieved with significantly more expensive metrology equipment.
期刊介绍:
The journal, Robotics and Computer-Integrated Manufacturing, focuses on sharing research applications that contribute to the development of new or enhanced robotics, manufacturing technologies, and innovative manufacturing strategies that are relevant to industry. Papers that combine theory and experimental validation are preferred, while review papers on current robotics and manufacturing issues are also considered. However, papers on traditional machining processes, modeling and simulation, supply chain management, and resource optimization are generally not within the scope of the journal, as there are more appropriate journals for these topics. Similarly, papers that are overly theoretical or mathematical will be directed to other suitable journals. The journal welcomes original papers in areas such as industrial robotics, human-robot collaboration in manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.