{"title":"基于局部POE的串联机器人高阶关节相关运动误差建模与标定","authors":"Yujie Zhang, Jing Cui, Yang Li, Zhongyi Chu","doi":"10.1108/ir-11-2022-0284","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThis paper aims to address the issue of model discontinuity typically encountered in traditional Denavit-Hartenberg (DH) models. To achieve this, we propose the use of a local Product of Exponentials (POE) approach. Additionally, a modified calibration model is presented which takes into account both kinematic errors and high-order joint-dependent kinematic errors. Both kinematic errors and high-order joint-dependent kinematic errors are analyzed to modify the model.\n\n\nDesign/methodology/approach\nRobot positioning accuracy is critically important in high-speed and heavy-load manufacturing applications. One essential problem encountered in calibration of series robot is that the traditional methods only consider fitting kinematic errors, while ignoring joint-dependent kinematic errors.\n\n\nFindings\nLaguerre polynomials are chosen to fitting kinematic errors and high-order joint-dependent kinematic errors which can avoid the Runge phenomenon of curve fitting to a great extent. Levenberg–Marquard algorithm, which is insensitive to overparameterization and can effectively deal with redundant parameters, is used to quickly calibrate the modified model. Experiments on an EFFORT ER50 robot are implemented to validate the efficiency of the proposed method; compared with the Chebyshev polynomial calibration methods, the positioning accuracy is improved from 0.2301 to 0.2224 mm.\n\n\nOriginality/value\nThe results demonstrate the substantial improvement in the absolute positioning accuracy achieved by the proposed calibration methods on an industrial serial robot.\n","PeriodicalId":54987,"journal":{"name":"Industrial Robot-The International Journal of Robotics Research and Application","volume":"2 1","pages":"753-764"},"PeriodicalIF":1.9000,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Modeling and calibration of high-order joint-dependent kinematic errors of serial robot based on local POE\",\"authors\":\"Yujie Zhang, Jing Cui, Yang Li, Zhongyi Chu\",\"doi\":\"10.1108/ir-11-2022-0284\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThis paper aims to address the issue of model discontinuity typically encountered in traditional Denavit-Hartenberg (DH) models. To achieve this, we propose the use of a local Product of Exponentials (POE) approach. Additionally, a modified calibration model is presented which takes into account both kinematic errors and high-order joint-dependent kinematic errors. Both kinematic errors and high-order joint-dependent kinematic errors are analyzed to modify the model.\\n\\n\\nDesign/methodology/approach\\nRobot positioning accuracy is critically important in high-speed and heavy-load manufacturing applications. One essential problem encountered in calibration of series robot is that the traditional methods only consider fitting kinematic errors, while ignoring joint-dependent kinematic errors.\\n\\n\\nFindings\\nLaguerre polynomials are chosen to fitting kinematic errors and high-order joint-dependent kinematic errors which can avoid the Runge phenomenon of curve fitting to a great extent. Levenberg–Marquard algorithm, which is insensitive to overparameterization and can effectively deal with redundant parameters, is used to quickly calibrate the modified model. Experiments on an EFFORT ER50 robot are implemented to validate the efficiency of the proposed method; compared with the Chebyshev polynomial calibration methods, the positioning accuracy is improved from 0.2301 to 0.2224 mm.\\n\\n\\nOriginality/value\\nThe results demonstrate the substantial improvement in the absolute positioning accuracy achieved by the proposed calibration methods on an industrial serial robot.\\n\",\"PeriodicalId\":54987,\"journal\":{\"name\":\"Industrial Robot-The International Journal of Robotics Research and Application\",\"volume\":\"2 1\",\"pages\":\"753-764\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2023-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Industrial Robot-The International Journal of Robotics Research and Application\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1108/ir-11-2022-0284\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Industrial Robot-The International Journal of Robotics Research and Application","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1108/ir-11-2022-0284","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
Modeling and calibration of high-order joint-dependent kinematic errors of serial robot based on local POE
Purpose
This paper aims to address the issue of model discontinuity typically encountered in traditional Denavit-Hartenberg (DH) models. To achieve this, we propose the use of a local Product of Exponentials (POE) approach. Additionally, a modified calibration model is presented which takes into account both kinematic errors and high-order joint-dependent kinematic errors. Both kinematic errors and high-order joint-dependent kinematic errors are analyzed to modify the model.
Design/methodology/approach
Robot positioning accuracy is critically important in high-speed and heavy-load manufacturing applications. One essential problem encountered in calibration of series robot is that the traditional methods only consider fitting kinematic errors, while ignoring joint-dependent kinematic errors.
Findings
Laguerre polynomials are chosen to fitting kinematic errors and high-order joint-dependent kinematic errors which can avoid the Runge phenomenon of curve fitting to a great extent. Levenberg–Marquard algorithm, which is insensitive to overparameterization and can effectively deal with redundant parameters, is used to quickly calibrate the modified model. Experiments on an EFFORT ER50 robot are implemented to validate the efficiency of the proposed method; compared with the Chebyshev polynomial calibration methods, the positioning accuracy is improved from 0.2301 to 0.2224 mm.
Originality/value
The results demonstrate the substantial improvement in the absolute positioning accuracy achieved by the proposed calibration methods on an industrial serial robot.
期刊介绍:
Industrial Robot publishes peer reviewed research articles, technology reviews and specially commissioned case studies. Each issue includes high quality content covering all aspects of robotic technology, and reflecting the most interesting and strategically important research and development activities from around the world.
The journal’s policy of not publishing work that has only been tested in simulation means that only the very best and most practical research articles are included. This ensures that the material that is published has real relevance and value for commercial manufacturing and research organizations. Industrial Robot''s coverage includes, but is not restricted to:
Automatic assembly
Flexible manufacturing
Programming optimisation
Simulation and offline programming
Service robots
Autonomous robots
Swarm intelligence
Humanoid robots
Prosthetics and exoskeletons
Machine intelligence
Military robots
Underwater and aerial robots
Cooperative robots
Flexible grippers and tactile sensing
Robot vision
Teleoperation
Mobile robots
Search and rescue robots
Robot welding
Collision avoidance
Robotic machining
Surgical robots
Call for Papers 2020
AI for Autonomous Unmanned Systems
Agricultural Robot
Brain-Computer Interfaces for Human-Robot Interaction
Cooperative Robots
Robots for Environmental Monitoring
Rehabilitation Robots
Wearable Robotics/Exoskeletons.