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A study on large parts precision docking method based on 6-axis industrial robot
Guo R(郭锐); Du JS(杜劲松); Zheng DC(郑德超); Lu BL(鲁伯林); Yin J(尹健)
Department智能检测与装备研究室
Conference Name2nd International Conference on Mechanical, Electric and Industrial Engineering, MEIE 2019
Conference DateMay 25-27, 2019
Conference PlaceHangzhou, China
Source Publication2nd International Conference on Mechanical, Electric and Industrial Engineering
PublisherIOP
Publication PlaceBristol, UK
2019
Pages1-10
Indexed ByEI
EI Accession number20193907471141
Contribution Rank1
ISSN1742-6588
AbstractIn view of the docking assembly difficulties of spacecraft large parts, resulting from the irregular contour and the inadequacy of process clamping points, this paper puts forward a method fitting the attitude relations of the docking parts based on the coordinates of the feature points, obtaining the target attitude of the docking parts based on the process constraints, and controlling 6-axis industrial robot achieves precise docking of large parts. Firstly, the composition of the large parts docking system is introduced, and the docking model is described by the selection of the measurement feature points and the establishment of the coordinate system. After that, a docking control algorithm based on the attitude constraints of large parts is established. Finally, In the RobotStudio and Matlab co-simulation environment, the attitude adjustment process of the large parts is simulated. The simulation results show that this study provides an effective method for precision docking of spacecraft engine large parts based on feature points, which is completed by 6-axis industrial robot.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/25659
Collection智能检测与装备研究室
Corresponding AuthorGuo R(郭锐)
AffiliationShenyang Institute of Automation, Chinese Academy of Science, Shenyang 110016, China
Recommended Citation
GB/T 7714
Guo R,Du JS,Zheng DC,et al. A study on large parts precision docking method based on 6-axis industrial robot[C]. Bristol, UK:IOP,2019:1-10.
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