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Calibration and decoupling of multi-axis robotic Force/Moment sensors
Liang, Qiaokang1,2; Wu, Wanneng1; Coppola, Gianmarc3; Zhang, Dan4; Sun, Wei1,2; Ge, Yunjian5; Wang, Yaonan1,2
2018-02-01
Source PublicationROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
Volume49Issue:Pages:301-308
Abstractforce (Fx, Fy, and Fz), as well as the moments (Mx, My and Mz). This enables them to be frequently used in many robotic applications. Accurate, time-effective calibration and decoupling procedures are critical to the implementation of these sensors. This paper compares the effectiveness of decoupling methods based on Least-Squares (LS), BP Neural Network (BPNN), and Extreme Learning Machine (ELM) methods for improving the performance of multi-axis robotic F/M sensors. In order to demonstrate the effectiveness of the decoupling methods, a calibration and decoupling experiment was performed on a five-axis robotic F/M sensor. The experiments demonstrate that the ELM based decoupling method is superior to LS and BPNN based methods. The presented theoretical and experimental demonstrations provide a comprehensive description of the calibration and decoupling procedures of multi -axis robotic F/M sensors. This work reveals that the ELM method is an appropriate and high performing decoupling procedure for multi -axis robotic F/M sensors. (C) 2017 Elsevier Ltd. All rights reserved.
SubtypeArticle
KeywordRobotic Sensory System Multi-axis Force/moment Sensors Calibration And Decoupling Extreme Learning Machine
WOS HeadingsScience & Technology ; Technology
Funding OrganizationNational Nature Science Foundation of China(NSFC 61673163) ; Hunan provincial natural science foundation of China(2016JJ3045) ; National Nature Science Foundation of China(NSFC 61673163) ; Hunan provincial natural science foundation of China(2016JJ3045)
DOI10.1016/j.rcim.2017.08.008
WOS Keyword6-AXIS FORCE/TORQUE SENSOR ; FORCE SENSOR ; TOUCH ; TRANSDUCER ; MACHINE ; DESIGN
Indexed BySCI
Language英语
Funding OrganizationNational Nature Science Foundation of China(NSFC 61673163) ; Hunan provincial natural science foundation of China(2016JJ3045) ; National Nature Science Foundation of China(NSFC 61673163) ; Hunan provincial natural science foundation of China(2016JJ3045)
WOS Research AreaComputer Science ; Engineering ; Robotics
WOS SubjectComputer Science, Interdisciplinary Applications ; Engineering, Manufacturing ; Robotics
WOS IDWOS:000412957500027
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.hfcas.ac.cn:8080/handle/334002/33785
Collection中科院合肥智能机械研究所
Affiliation1.Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China
2.Hunan Univ, Natl Engn Lab Robot Vision Percept & Control, Changsha 410082, Hunan, Peoples R China
3.Univ Ontario, Inst Technol, Fac Engn & Appl Sci, Oshawa, ON L1H 7K4, Canada
4.York Univ, Dept Mech Engn, Toronto, ON M3J 1P3, Canada
5.Chinese Acad Sci, Inst Intelligent Machines, Hefei 230031, Anhui, Peoples R China
Recommended Citation
GB/T 7714
Liang, Qiaokang,Wu, Wanneng,Coppola, Gianmarc,et al. Calibration and decoupling of multi-axis robotic Force/Moment sensors[J]. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING,2018,49(无):301-308.
APA Liang, Qiaokang.,Wu, Wanneng.,Coppola, Gianmarc.,Zhang, Dan.,Sun, Wei.,...&Wang, Yaonan.(2018).Calibration and decoupling of multi-axis robotic Force/Moment sensors.ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING,49(无),301-308.
MLA Liang, Qiaokang,et al."Calibration and decoupling of multi-axis robotic Force/Moment sensors".ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 49.无(2018):301-308.
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