Knowledge Management System of Shenyang Institute of Automation, CAS
Multi-objective global optimum design of collaborative robots | |
Hu MW(胡明伟)1,2,3![]() ![]() ![]() | |
Department | 工艺装备与智能机器人研究室 |
Source Publication | STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
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ISSN | 1615-147X |
2020 | |
Volume | 62Issue:3Pages:1547–1561 |
Indexed By | SCI ; EI |
EI Accession number | 20202208717984 |
WOS ID | WOS:000534834900001 |
Contribution Rank | 1 |
Funding Organization | National 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] |
Keyword | Finite 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 Subject | Computer Science, Interdisciplinary Applications ; Engineering, Multidisciplinary ; Mechanics |
WOS Keyword | LIGHTWEIGHT ROBOT ; OPTIMIZATION ; PARAMETERS ; STIFFNESS |
WOS Research Area | Computer Science ; Engineering ; Mechanics |
Funding Project | National 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 |
Identifier | http://ir.sia.cn/handle/173321/26934 |
Collection | 工艺装备与智能机器人研究室 |
Corresponding Author | Wang HG(王洪光) |
Affiliation | 1.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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Multi-objective glob(1315KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | View Application Full Text |
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