Tian Lan , Te Li , Haibo Liu , Shiyu Tian , Kuo Liu , Yongqing Wang
{"title":"薄壁锥形管管内加工机器人的精确定位与环焊缝磨削规划","authors":"Tian Lan , Te Li , Haibo Liu , Shiyu Tian , Kuo Liu , Yongqing Wang","doi":"10.1016/j.rcim.2025.103124","DOIUrl":null,"url":null,"abstract":"<div><div>In-pipe robots have been applied to detection, cleaning, welding, grinding, drilling, etc., which realizes the narrow space operation efficiently and economically. However, intelligent operation is still a problem, especially for high-precision machining of inner welds in thin-walled conical pipes, due to the low stiffness and precision of the robot machining system, uncertain robot position, and poor consistency of target characteristics. To address this problem, an intelligent girth weld grinding method of an in-pipe machining robot for thin-walled conical pipes is proposed. An in-pipe machining robot (named IPMR-I) with adaptive motion ability, controllable stiffness, and high machining precision is designed, which benefits by the designs of controllable contact forces and a high-precision three-axis machining mechanism. A weld locating method based on time-series point clouds, combined with an analytical pose model, is used for robot self-localization, obtaining the accurate pose of the robot relative to the weld region. Furthermore, an intelligent machining path planning method is proposed with the abilities of the weld boundary recognition, machining path generation, and optimization, which adaptively realizes the high machining quality and safety facing the welding irregularity (e.g., deformation and misalignment) inside thin-walled conical pipes. Several weld bead grinding experiments were conducted inside thin-walled conical pipes to verify the proposed methods’ validity. The results proved that IPMR-I with the proposed intelligent girth weld grinding method completed autonomous high-quality machining without manual intervention. Without damaging the base material, the maximum residual weld height is 0.18 mm, with the average residual height controlled at approximately 0.08 mm.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"98 ","pages":"Article 103124"},"PeriodicalIF":11.4000,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Accurate localization and girth weld grinding planning for an in-pipe machining robot of thin-walled conical pipe\",\"authors\":\"Tian Lan , Te Li , Haibo Liu , Shiyu Tian , Kuo Liu , Yongqing Wang\",\"doi\":\"10.1016/j.rcim.2025.103124\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In-pipe robots have been applied to detection, cleaning, welding, grinding, drilling, etc., which realizes the narrow space operation efficiently and economically. However, intelligent operation is still a problem, especially for high-precision machining of inner welds in thin-walled conical pipes, due to the low stiffness and precision of the robot machining system, uncertain robot position, and poor consistency of target characteristics. To address this problem, an intelligent girth weld grinding method of an in-pipe machining robot for thin-walled conical pipes is proposed. An in-pipe machining robot (named IPMR-I) with adaptive motion ability, controllable stiffness, and high machining precision is designed, which benefits by the designs of controllable contact forces and a high-precision three-axis machining mechanism. A weld locating method based on time-series point clouds, combined with an analytical pose model, is used for robot self-localization, obtaining the accurate pose of the robot relative to the weld region. Furthermore, an intelligent machining path planning method is proposed with the abilities of the weld boundary recognition, machining path generation, and optimization, which adaptively realizes the high machining quality and safety facing the welding irregularity (e.g., deformation and misalignment) inside thin-walled conical pipes. Several weld bead grinding experiments were conducted inside thin-walled conical pipes to verify the proposed methods’ validity. The results proved that IPMR-I with the proposed intelligent girth weld grinding method completed autonomous high-quality machining without manual intervention. Without damaging the base material, the maximum residual weld height is 0.18 mm, with the average residual height controlled at approximately 0.08 mm.</div></div>\",\"PeriodicalId\":21452,\"journal\":{\"name\":\"Robotics and Computer-integrated Manufacturing\",\"volume\":\"98 \",\"pages\":\"Article 103124\"},\"PeriodicalIF\":11.4000,\"publicationDate\":\"2025-09-16\",\"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/S0736584525001784\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotics and Computer-integrated Manufacturing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0736584525001784","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}
Accurate localization and girth weld grinding planning for an in-pipe machining robot of thin-walled conical pipe
In-pipe robots have been applied to detection, cleaning, welding, grinding, drilling, etc., which realizes the narrow space operation efficiently and economically. However, intelligent operation is still a problem, especially for high-precision machining of inner welds in thin-walled conical pipes, due to the low stiffness and precision of the robot machining system, uncertain robot position, and poor consistency of target characteristics. To address this problem, an intelligent girth weld grinding method of an in-pipe machining robot for thin-walled conical pipes is proposed. An in-pipe machining robot (named IPMR-I) with adaptive motion ability, controllable stiffness, and high machining precision is designed, which benefits by the designs of controllable contact forces and a high-precision three-axis machining mechanism. A weld locating method based on time-series point clouds, combined with an analytical pose model, is used for robot self-localization, obtaining the accurate pose of the robot relative to the weld region. Furthermore, an intelligent machining path planning method is proposed with the abilities of the weld boundary recognition, machining path generation, and optimization, which adaptively realizes the high machining quality and safety facing the welding irregularity (e.g., deformation and misalignment) inside thin-walled conical pipes. Several weld bead grinding experiments were conducted inside thin-walled conical pipes to verify the proposed methods’ validity. The results proved that IPMR-I with the proposed intelligent girth weld grinding method completed autonomous high-quality machining without manual intervention. Without damaging the base material, the maximum residual weld height is 0.18 mm, with the average residual height controlled at approximately 0.08 mm.
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.