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Multi-objective global optimum design of collaborative robots
Hu MW(胡明伟)1,2,3; Wang HG(王洪光)1,2; Pan XA(潘新安)1,2
Department工艺装备与智能机器人研究室
Source PublicationSTRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
ISSN1615-147X
2020
Volume62Issue:3Pages:1547–1561
Indexed BySCI ; EI
EI Accession number20202208717984
WOS IDWOS:000534834900001
Contribution Rank1
Funding OrganizationNational Natural Science Foundation of ChinaNational Natural Science Foundation of China [51535008] ; State Key Laboratory of Robotics [2014-Z09] ; Key Program of the Chinese Academy of SciencesChinese Academy of Sciences [KGZD-EW-608-1]
KeywordFinite element substructure method Orthogonal design Collaborative robots Optimum design Gray relational analysis method
Abstract

Optimum design is proven significant for improving task performances of robotic manipulators under certain constraints. However, when it is utilized for collaborative robots (Cobots), there are still many challenges such as complex smooth surface links, time-varying kinematic configurations, computational expensiveness, and nonstructural parameter optimization. Therefore, based on orthogonal design experiment (ODE) and finite element substructure method (FESM), a multi-objective optimum design method of Cobots is proposed with the structural dimensions and parameterized joint components as the optimization variables and the natural frequency, the Cartesian stiffness, and the mass of the robot as optimization objectives. Firstly, to obtain multiple global performance indexes (GPIs) of robots in real-time and efficiently, the FESM model of Cobots is established which can preserve the accuracy of the finite element method (FEM) while ensuring the computational efficiency. Then, the gray relational analysis method (GRAM) is used to construct the multi-objective optimization function which includes the global first-order natural frequency index (GFNFI), the global elastic deformation index (GEDI), and the mass of robots. The ODE is constructed, and the structural dimensions and parameterized joint components are taken as influencing factors. According to the orthogonal array (OA), the degree of gray incidence under different levels of influencing factors is solved. And the optimal combination of influencing factor levels is obtained by range analysis (RA), which is used to guide the design of Cobots. Finally, a Cobot SHIR5-I is taken as an illustrative example to perform optimum design in this paper.

Language英语
WOS SubjectComputer Science, Interdisciplinary Applications ; Engineering, Multidisciplinary ; Mechanics
WOS KeywordLIGHTWEIGHT ROBOT ; OPTIMIZATION ; PARAMETERS ; STIFFNESS
WOS Research AreaComputer Science ; Engineering ; Mechanics
Funding ProjectNational Natural Science Foundation of China[51535008] ; State Key Laboratory of Robotics[2014-Z09] ; Key Program of the Chinese Academy of Sciences[KGZD-EW-608-1]
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/26934
Collection工艺装备与智能机器人研究室
Corresponding AuthorWang HG(王洪光)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
3.University of Chinese Academy of Sciences, Beijing 100049, China
Recommended Citation
GB/T 7714
Hu MW,Wang HG,Pan XA. Multi-objective global optimum design of collaborative robots[J]. STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION,2020,62(3):1547–1561.
APA Hu MW,Wang HG,&Pan XA.(2020).Multi-objective global optimum design of collaborative robots.STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION,62(3),1547–1561.
MLA Hu MW,et al."Multi-objective global optimum design of collaborative robots".STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 62.3(2020):1547–1561.
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