Partition Mutation PSO for Welding Robot Path Optimization

被引:1
作者
Wang, Xue-Wu [1 ]
Shi, Ying-Pan [1 ]
Gu, Xing-Sheng [1 ]
Ding, Dong-Yan [2 ]
机构
[1] E China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai 200237, Peoples R China
[2] Shanghai Jiao Tong Univ, Sch Mat Sci & Engn, Inst Microelect Mat & Technol, Shanghai 200240, Peoples R China
来源
ROBOTIC WELDING, INTELLIGENCE AND AUTOMATION, RWIA'2014 | 2015年 / 363卷
基金
上海市自然科学基金;
关键词
PARTICLE SWARM OPTIMIZATION;
D O I
10.1007/978-3-319-18997-0_6
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Many solder joints usually have to be traversed for spot welding robots, and reasonable welding sequence will improve welding efficiency. Intelligent optimization algorithms have been used to study path optimization problems in these years because of their effective optimization abilities. Due to its simplicity, high search accuracy and fast convergence rate, the particle swarm optimization (PSO) algorithm was used to study welding robot path planning. A novel hybrid discrete PSO algorithm was proposed to improve the basic PSO after the partition operation, mutation strategy were combined. Then, the optimization performance of the algorithm was used to solve 3-dimensional welding path planning problem.
引用
收藏
页码:77 / 86
页数:10
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