Yusheng Zang , Changsheng Li , Jiajun Tang , Zhaoxiang Chen , Jianjun Ding , Shuming Yang , Zhuangde Jiang
{"title":"一种基于ICP粗配准和PSO精细配准的自由曲面评价复合配准方法","authors":"Yusheng Zang , Changsheng Li , Jiajun Tang , Zhaoxiang Chen , Jianjun Ding , Shuming Yang , Zhuangde Jiang","doi":"10.1016/j.optlaseng.2025.109079","DOIUrl":null,"url":null,"abstract":"<div><div>The assessment of form error for freeform surfaces is crucial for ensuring the machining accuracy of optical components and performing potential subsequent error correction. Although the traditional iterative closest point (ICP) algorithm is widely used for surface registration due to its simplicity and broad applicability, it has limitations such as sensitivity to initial optimization positions, which seriously affect the accuracy of registration. For this reason, this paper proposes a composite surface registration method based on ICP for coarse registration and particle swarm optimization (PSO) for fine registration. First, the influence of six mounting errors on the form accuracy is discussed through error sensitivity analysis. Second, the characteristics of the ICP algorithm and the PSO algorithm in surface registration are comparatively analyzed in aspects of accuracy and efficiency. Finally, the composite registration method is successfully applied to the surface registration of the freeform surfaces. The results show that the composite registration method has achieved 88.4 % and 1.4 % decrease in registration error compared to the ICP algorithm when processing the freeform suction cup and silicon mirror, respectively. Additionally, the computational time is reduced by 40 % and 20 % compared to the PSO algorithm, respectively. Even when compared to advanced hybrid registration algorithms combining genetic algorithms (GA) and ICP algorithms, the proposed method in this paper still maintains advantages in terms of registration accuracy and efficiency.</div></div>","PeriodicalId":49719,"journal":{"name":"Optics and Lasers in Engineering","volume":"193 ","pages":"Article 109079"},"PeriodicalIF":3.5000,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A composite surface registration method for freeform surface evaluation based on ICP coarse registration and PSO fine registration\",\"authors\":\"Yusheng Zang , Changsheng Li , Jiajun Tang , Zhaoxiang Chen , Jianjun Ding , Shuming Yang , Zhuangde Jiang\",\"doi\":\"10.1016/j.optlaseng.2025.109079\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The assessment of form error for freeform surfaces is crucial for ensuring the machining accuracy of optical components and performing potential subsequent error correction. Although the traditional iterative closest point (ICP) algorithm is widely used for surface registration due to its simplicity and broad applicability, it has limitations such as sensitivity to initial optimization positions, which seriously affect the accuracy of registration. For this reason, this paper proposes a composite surface registration method based on ICP for coarse registration and particle swarm optimization (PSO) for fine registration. First, the influence of six mounting errors on the form accuracy is discussed through error sensitivity analysis. Second, the characteristics of the ICP algorithm and the PSO algorithm in surface registration are comparatively analyzed in aspects of accuracy and efficiency. Finally, the composite registration method is successfully applied to the surface registration of the freeform surfaces. The results show that the composite registration method has achieved 88.4 % and 1.4 % decrease in registration error compared to the ICP algorithm when processing the freeform suction cup and silicon mirror, respectively. Additionally, the computational time is reduced by 40 % and 20 % compared to the PSO algorithm, respectively. Even when compared to advanced hybrid registration algorithms combining genetic algorithms (GA) and ICP algorithms, the proposed method in this paper still maintains advantages in terms of registration accuracy and efficiency.</div></div>\",\"PeriodicalId\":49719,\"journal\":{\"name\":\"Optics and Lasers in Engineering\",\"volume\":\"193 \",\"pages\":\"Article 109079\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2025-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Optics and Lasers in Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0143816625002659\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"OPTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optics and Lasers in Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0143816625002659","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OPTICS","Score":null,"Total":0}
A composite surface registration method for freeform surface evaluation based on ICP coarse registration and PSO fine registration
The assessment of form error for freeform surfaces is crucial for ensuring the machining accuracy of optical components and performing potential subsequent error correction. Although the traditional iterative closest point (ICP) algorithm is widely used for surface registration due to its simplicity and broad applicability, it has limitations such as sensitivity to initial optimization positions, which seriously affect the accuracy of registration. For this reason, this paper proposes a composite surface registration method based on ICP for coarse registration and particle swarm optimization (PSO) for fine registration. First, the influence of six mounting errors on the form accuracy is discussed through error sensitivity analysis. Second, the characteristics of the ICP algorithm and the PSO algorithm in surface registration are comparatively analyzed in aspects of accuracy and efficiency. Finally, the composite registration method is successfully applied to the surface registration of the freeform surfaces. The results show that the composite registration method has achieved 88.4 % and 1.4 % decrease in registration error compared to the ICP algorithm when processing the freeform suction cup and silicon mirror, respectively. Additionally, the computational time is reduced by 40 % and 20 % compared to the PSO algorithm, respectively. Even when compared to advanced hybrid registration algorithms combining genetic algorithms (GA) and ICP algorithms, the proposed method in this paper still maintains advantages in terms of registration accuracy and efficiency.
期刊介绍:
Optics and Lasers in Engineering aims at providing an international forum for the interchange of information on the development of optical techniques and laser technology in engineering. Emphasis is placed on contributions targeted at the practical use of methods and devices, the development and enhancement of solutions and new theoretical concepts for experimental methods.
Optics and Lasers in Engineering reflects the main areas in which optical methods are being used and developed for an engineering environment. Manuscripts should offer clear evidence of novelty and significance. Papers focusing on parameter optimization or computational issues are not suitable. Similarly, papers focussed on an application rather than the optical method fall outside the journal''s scope. The scope of the journal is defined to include the following:
-Optical Metrology-
Optical Methods for 3D visualization and virtual engineering-
Optical Techniques for Microsystems-
Imaging, Microscopy and Adaptive Optics-
Computational Imaging-
Laser methods in manufacturing-
Integrated optical and photonic sensors-
Optics and Photonics in Life Science-
Hyperspectral and spectroscopic methods-
Infrared and Terahertz techniques