|本期目录/Table of Contents|

[1]顾平灿,徐月同.基于QPSO的双机器人同步焊接路径规划研究[J].工业仪表与自动化装置,2015,(05):75.
 GU Pingcan,XU Yuetong.Research on path planning of synchronous welding of dual robot based on QPSO[J].Industrial Instrumentation & Automation,2015,(05):75.
点击复制

基于QPSO的双机器人同步焊接路径规划研究(PDF)

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2015年05期
页码:
75
栏目:
出版日期:
2015-10-15

文章信息/Info

Title:
Research on path planning of synchronous welding of dual robot based on QPSO
文章编号:
1000-0682(2015)05-0000-00
作者:
顾平灿1徐月同2
(1.浙江海洋学院 船舶与海洋工程学院,浙江 舟山 316100;2.浙江大学 机械工程系,杭州 310027)
Author(s):
GU Pingcan1XU Yuetong2
(1. School of Shipping and Ocean Engineering, Zhejiang Ocean University,Zhejiang Zhoushan 316100, China;2. School of Machanical Engineering, Zhejiang University, Hangzhou 310027, China)
关键词:
双机器人同步焊接路径规划量子行为粒子群优化多旅行商问题
Keywords:
synchronous double robot weldingpath planningquantum behaved particle swarm optimizationmultiple traveling salesman problem
分类号:
TP274
DOI:
-
文献标志码:
A
摘要:
手动液压搬运车是重要的物流搬运设备,其车架是由异型钣金件焊接而成。为了提高焊接质量和生产效率,降低劳动强度,主焊工位采用双机器人同步焊接加工势在必行。在充分考虑焊接变形和运动干涉的基础上,采用量子行为粒子群优化建立双机器人同步焊接数学模型,仿真求解了全局最优焊接路径的近似解,并将粒子群优化与量子行为粒子群优化做了仿真对比试验。结果表明,量子行为粒子群优化能更好地搜索整个解空间,在一定程度上有效解决搬运车车架主焊工序双机器人同步焊接问题。
Abstract:
Manual hydraulic pallet truck is the important logistics handling equipment, the frames are made of profiled sheet metal welded. In order to improve the elding quality and production efficiency, reduce labor intensity, the main welding stations using synchronous dual robot welding processing be imperative. Based on fully considering the welding deformation and motion interference, The mathematical model of dual robot simultaneous welding is establish by quantum behaved particle swarm optimization, simulation to approximate solution the global optimal solution of welding path, and do the simulation tested particle swarm optimization and quantum behaved particle swarm optimization. The results show that the quantum behaved particle swarm optimization can better search in the whole solution space, effectively solve the problem of dual robot simultaneous welding the truck frame in the main welding process to a certain extent.

参考文献/References:

[1] 俞庆生,林冬梅,王东.多旅行商问题研究综述[J]. 价值工程,2012(02):166-168.

[2] GORENSTEIN S. Printing press scheduling for multi-edition periodicals[J]. Management Science, 1970, 16(6): 373-83.
[3] 任子武,伞冶.自适应遗传算法的改进及在系统辨识中应用研究[J].系统仿真学报,2006(01):41-43+66.
[4] 莫愿斌.粒子群优化算法的扩展与应用[D].杭州:浙江大学, 2006.
[5] STUTZLE T, HOLGER H. MAX-MIN Ant System[J]. Future Generation Computer Systems, 2000,16(8):889-914.
[6] 周永权,谢竹诚.求解TSP的改进人工鱼群算法[J].系统工程与电子技术,2009(06):1458-1461.
[7] KARABOGA D. An idea based on honey bee swarm for numerical optimization, TR06[R]. Kayseri: Erciyes University, 2005.
[8] 黄少荣.粒子群优化算法综述[J].计算机工程与设计, 2009(08):1977-1980.
[9] 王杰文,李赫男.粒子群优化算法综述[J].现代计算机:专业版,2009(02):22-27.
[10] Kennedy J, Eberhart R C. Particle swarm optimization[C]. Proceedings of IEEE International Conference on Neural Networks, 1995, 1942~1948.
[11] Bergh F V d. A new locally convergent particle swarm optimizer[C]. IEEE International Conference on Systems, Man and Cybernetics, 2002.
[12] Bergh F V d. An analysis of particle swarm optimizers[D].University of Pretoria, 2001.
[13] 孙俊.量子行为粒子群优化算法研究[D].无锡:江南大学, 2009.
[14] 杨伟东,檀润华,颜永年,等.遗传算法在快速成形轮廓路径规划中的应用[J].计算机辅助设计与图形学学报, 2005(10):39-43.
[15] Dorigo, M., & Stutzle, T. Ant colony optimization[M]. The MIT Press. 2004.

相似文献/References:

[1]马学成.机床上下料设备控制系统设计及应用[J].工业仪表与自动化装置,2019,(03):81.[doi:1000-0682(2019)03-0000-00]
 MA Xuecheng.Design and application of control system for machine tool[J].Industrial Instrumentation & Automation,2019,(05):81.[doi:1000-0682(2019)03-0000-00]
[2]孟祥忠,刘 健,李 鹏.多AGV定位和路径规划方法研究[J].工业仪表与自动化装置,2019,(05):7.[doi:1000-0682(2019)05-0000-00]
 MENG Xiangzhong,LIU Jian,LI Peng.Research on multi-AGV location and path planning method[J].Industrial Instrumentation & Automation,2019,(05):7.[doi:1000-0682(2019)05-0000-00]
[3]唐兴贵,和文云,马志艳,等.基于S7-1200PLC和时域分析的工业机器人移动轨迹最优化规划方法[J].工业仪表与自动化装置,2022,(02):51.[doi:10.19950/j.cnki.cn61-1121/th.2022.02.011]
 TANG Xinggui,HE Wenyun,MA Zhiyan,et al.Optimal trajectory planning method of industrial robot based on s7-1200plc and time domain analysis[J].Industrial Instrumentation & Automation,2022,(05):51.[doi:10.19950/j.cnki.cn61-1121/th.2022.02.011]
[4]郭 茜,袁德成.基于改进RRT*算法的可重构机器人路径规划[J].工业仪表与自动化装置,2023,(03):70.[doi:10.19950/j.cnki.cn61-1121/th.2023.03.014]
 GUO Qian,YUAN Decheng.Path planning of reconfigurable robot based on improved RRT* algorithm[J].Industrial Instrumentation & Automation,2023,(05):70.[doi:10.19950/j.cnki.cn61-1121/th.2023.03.014]
[5]高英剑,郭 平.基于改进A*算法的遥控水下机器人路径规划[J].工业仪表与自动化装置,2023,(03):75.[doi:10.19950/j.cnki.cn61-1121/th.2023.03.015]
 GAO Yingjian,GUO Ping.Path planning of remotely operated vehicle based on improved A* algorithm[J].Industrial Instrumentation & Automation,2023,(05):75.[doi:10.19950/j.cnki.cn61-1121/th.2023.03.015]
[6]徐 洁,张 锐,汪志锋.改进蚁群算法在自动导引车路径规划中的应用[J].工业仪表与自动化装置,2023,(03):88.[doi:10.19950/j.cnki.cn61-1121/th.2023.03.018]
 XU Jie,ZHANG Rui,WANG Zhifeng.Application of improved ant colony algorithm in AGV path planning[J].Industrial Instrumentation & Automation,2023,(05):88.[doi:10.19950/j.cnki.cn61-1121/th.2023.03.018]
[7]王俊彭,等.基于蚁群算法的人员疏散机器人路径规划方法[J].工业仪表与自动化装置,2023,(04):77.[doi:10.19950/j.cnki.cn61-1121/th.2023.04.014]
 WANG Junpeng,,et al.Path planning method of personnel evacuation robot based on ant colony algorithm[J].Industrial Instrumentation & Automation,2023,(05):77.[doi:10.19950/j.cnki.cn61-1121/th.2023.04.014]
[8]田 悦,袁德成.基于多策略改进狼群算法的机械臂路径规划[J].工业仪表与自动化装置,2023,(05):76.[doi:10.19950/j.cnki.cn61-1121/th.2023.05.016]
 TIAN Yue,YUAN Decheng.Robot path planning based on multi strategy improved wolf pack algorithm[J].Industrial Instrumentation & Automation,2023,(05):76.[doi:10.19950/j.cnki.cn61-1121/th.2023.05.016]

备注/Memo

备注/Memo:

收稿日期 2014-12-22

作者简介 :顾平灿 (1968) ,男,浙江临海,硕士、副教授,研究方向为机电一体化技术。

更新日期/Last Update: 1900-01-01