CASIA OpenIR  > 智能制造技术与系统研究中心  > 先进制造与自动化
张好剑1,2; 苏婷婷1,2; 吴少泓1,2; 郑军1,2; 王云宽1,2
Source Publication华南理工大学学报
Other Abstract

By analyzing the production precess of packaging lines ,aiming at the multiple-target problem of the Delta parellel robot sorting with dynamically changing positions under complex julti-constraint conditions,a method to optimize the sorting trajectories of the parallel robot if proposed based on an improbed genetic algorithm and the thought of beats.By analyzing the sorting strategy,the practical problem is transform into a similar traveling saleman problem,and an improved genetic algorithm is put forward according to the particularity of the sorting process.Moreover,the thought of beats is introduced, and the sorting trajectories is every beat are optimized by transforming the constraint conditions into a genetic operator combining the fission and merge operations of chromosemes.The test results show that,as compared with the traditional methods,the proposed method can effectively shorten the average sorting stroke,with an average effective increase of 14.76%.

Keyword分节拍 路径规划 改进遗传算法 Tsp 并联机器人
Document Type期刊论文
Corresponding Author吴少泓
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
张好剑,苏婷婷,吴少泓,等. 基于改进遗传算法的并联机器人分拣路径优化[J]. 华南理工大学学报,2017,2017(10):93.
APA 张好剑,苏婷婷,吴少泓,郑军,&王云宽.(2017).基于改进遗传算法的并联机器人分拣路径优化.华南理工大学学报,2017(10),93.
MLA 张好剑,et al."基于改进遗传算法的并联机器人分拣路径优化".华南理工大学学报 2017.10(2017):93.
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