Streamlined robotic hand–eye calibration of multiple 2D-profilers: A rapid, closed-form two-stage method via a single-plane artefact

IF 9.1 1区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Subash Gautam , Hans Lohr , Alejandro Vargas-Uscategui , Peter C King , Alireza Bab-Hadiashar , Ivan Cole , Ehsan Asadi
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引用次数: 0

Abstract

A 2D laser profiler is commonly utilized in high-precision robotic settings to capture detailed surface profiles for 3D scanning. By collecting and combining numerous such measurements from different viewpoints, it is possible to assemble a comprehensive 3D map. However, to effectively merge these individual 2D profiles into a singular global framework, the spatial relationship between the scanners and the robot’s reference frame is required. Traditional hand–eye calibration techniques typically necessitate specific calibration artifacts or extraneous positional sensors, and the process is either manually executed or only partially automated, demanding considerable time and effort. This paper introduces an innovative, closed-form approach to hand–eye calibration that can be applied to a single scanner or an array of multiple scanners. Our method circumvents the requirements for initial parameter estimates or specialized calibration implements, instead employing a flat plane for hand–eye calibration. This method paves the way for a fully automated calibration sequence comprising only three rotational and three translational poses, reducing the total calibration duration. This streamlined process has undergone strict experimental validation utilizing a calibrated sphere, proving its effectiveness not only with a solitary scanner setup but also with an ensemble of three scanners.
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来源期刊
Robotics and Computer-integrated Manufacturing
Robotics and Computer-integrated Manufacturing 工程技术-工程:制造
CiteScore
24.10
自引率
13.50%
发文量
160
审稿时长
50 days
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.
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