基于蚁群算法-粒子群算法的白车身侧围点焊机器人路径规划

摘要/Abstract

摘要： 针对白车身侧围点焊多机器人协调焊接任务，对焊接路径规划算法进行了研究。提出了一种适用于该任务的蚁群粒子群混合算法，以实现多机器人焊点分配均匀和单机器人焊接路径最优的焊接要求。通过分析白车身侧围焊点分布特点及多机器人协调焊接要求，建立白车身侧围点焊多机器人协调焊接任务数学模型。设计了基于蚁群粒子群混合算法的路径规划方案，在MATLAB中得到规划结果。利用机器人离线编程软件Robotstudio建立白车身侧围多机器人协调焊接工作站，对规划结果进行仿真实验。结果表明，该算法可实现焊点均匀分配，缩短焊接路径，有效提高焊接效率。

关键词: 白车身, 点焊, 蚁群算法, 粒子群算法, 路径规划

Abstract: A welding path planning algorithm was studied based on the tasks of multi-robot spot welding coordination in sides of BIW. An ant colony particle swarm hybrid algorithm was proposed for the tasks, to achieve the average distribution of multi-robot welding points and the optimal soldering path of single robot. Based on the analyses of the distribution characteristics of the sides of BIW welding points and the requirements of multi-robot coordination welding, a mathematical model of multi-robot coordination welding for the sides of BIW welding was established. A path planning scheme was designed based on ant colony particle swarm hybrid algorithm, and the planning results were obtained in MATLAB. Robot offline programming software ‘Robotstudio’ was used to build a multi-robot coordination welding workstations for the sides of BIW welding, and simulation tests were carried out on the planning results. The results show that the algorithm may realize the average distribution of welding points, shorten the welding paths and improve the welding efficiency effectively.

Key words: body in white（BIW）, spot welding, ant colony optimization(ACO), particle swarm optimization(PSO), path planning

中图分类号:

TH181
TG409

侯仰强1;王天琪1;李亮玉1;张志臣1;赵娜2. 基于蚁群算法-粒子群算法的白车身侧围点焊机器人路径规划[J]. 中国机械工程.

HOU Yangqiang1;WANG Tianqi1;LI Lianyu1;ZHANG Zhichen1;ZHAO Na2. Path Planning of Spot Welding Robots in Sides of BIW Based on ACO-PSO[J]. China Mechanical Engineering.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: http://www.cmemo.org.cn/CN/

http://www.cmemo.org.cn/CN/Y2017/V28/I24/2990

参考文献

[1]聂昕，郭志福，何智成. 基于时频特征的汽车点焊质量自动化超声评价[J].中国机械工程，2016, 27（8）：1102-1106.
NIE Xin， GUO Zhifu， HE Zhicheng. Automatic Ultrasonic Evaluation of Vehicle Spot Welding Quality Based on Time-frequency Characteristics [J]. China Mechanical Engineering，2016，27(8) : 1102-1106.
[2]刘海江，张春伟，徐君杰，等. 基于遗传算法的白车身焊接机器人焊点分配[J].同济大学学报（自然科学版），2010，38( 5) : 725-729.
LIU Haijiang, ZHANG Chunwei, XU Junjie, et al.Assigning Welding Point of Car-body-in-white to Multi-robots Based on Genetic Algorithm[J]. Journal of Tongji University (Natural Science), 2010, 38( 5) : 725-729.
[3]邓乾旺，罗正平，张丽科，等. 点焊机器人轨迹能耗模型及其优化算法研究[J].中国机械工程，2016, 27（1）：14-19.
DENG Qianwang， LUO Zhengping， ZHANG Like，et al. Study on Energy Consumption Model and Its Optimization Algorithm for Spot Welding Robot Trajectory [J]. China Mechanical Engineering，2016，27(1) : 14-19.
[4]林巨广，陈甦欣，戴淮初，等. 蚁群算法在白车身底板焊接路径规划中的应用[J]. 焊接学报,2015, 36(1) : 5-9.
LIN Juguang, CHEN Suxin, DAI Huaichu , et al. Application of Ant Colony Algorithm to Process Planning of Welding Path in BIW [J]. Transactions of the China Welding Institution, 2015, 36(1) : 5-9.
[5]赵欣，张延松，陈关龙，等. 基于神经网络优化的车身镀锌板点焊性能预测[J]. 焊接学报，2006，27(12) : 77-80,84.
ZHAO Xin, ZHANG Yansong, CHEN Guanlong , et al. Performance Prediction in Spot Welding of Body Galvanized Steel Sheets Based on Artificial Neural Network and Its Optimization [J]. Transactions of The China Welding Institution, 2006，27(12) : 77-80, 84.
[6]林忠钦，胡敏，米新民, 等. 轿车白车身点焊装配过程有限元分析[J].焊接学报，2001，22(1) : 36-40.
LIN Zhongqin, HU Min, MI Xinmin, et al. FEM Analysis or Spot Welding Process in Autobody Manufacturing [J]. Transactions of the China Welding Institution, 2001，22(1) : 36-40.
[7]陈波，潘海鹏，邓志辉.基于PSO优化RBF神经网络的反应釜故障诊断[J].中国机械工程，2012, 23（18）：2204-2207.
CHEN Bo， PAN Haipeng， DENG Zhihui. Fault Diagnosis of RBF Neural Network Based on PSO [J]. China Mechanical Engineering，2012，23(18) : 2204-2207.
[8]BADR A, FAHMY A. A Proof of Convergence for Ant Algorithms [J]. Intenational Journal of Intelligent Conputing and Information, 2003, 3(1): 22-32.
[9]李世勇. 蚁群算法及其应用[M]. 哈尔滨：哈尔滨工业大学出版社，2004.
LI Sinyong. Ant Colony Algorithms with Applications[M].Harbin: Harbin Institute of Technology Press,2004.
[10]袁彬，韩江，吴路路，等. 基于粒子群算法的滚削齿面综合轮廓误差预测模型与试验研究[J]. 中国机械工程，2016, 27（20）：2705-2710.
YUAN Bin， HAN Jiang， WU Lulu，et al. A Prediction Model and Experimental Study of Gear Hobbing Profile Errors Based on Particle Swarm Optimization [J]. China Mechanical Engineering，2016，27(20) : 2705-2710.
[11]李荣钧，刘小龙. 基于微生物行为机制的粒子群优化算法[M]. 广州：华南理工大学出版社, 2015.
LI Rongjun, LIU Xiaolong. Particle Swarm Optimization Algorithm Based on Microbiological Behavior Mechanism[M].Guangzhou: South China University of Technology Press,2015.
[12]晁永生，刘海江.白车身焊接机器人加工路径优化和仿真[J].中国机械工程，2010，21(4) : 442-445.
CHAO Yongsheng， LIU Haijiang. Welding Robot Path Optimization for Body in White [J].China Mechanical Engineering，2010，21(4) : 442-445.
[13]乔良,宋小欣,谢延敏,等.基于PSO-RBF代理模型的板料成形本构参数反求优化研究[J]. 中国机械工程，2014, 25（19）：2680-2685.
QIAO Liang， SONG Xiaoxin， XIE Yanmin，et al. Study on the Optimization of Constitutive Parameters of Sheet Metal Forming Based on PSO-RBF Proxy Model [J]. China Mechanical Engineering，2014，25 (19) : 2680-2685.
[14]TIMAC G，BRAUT S，ZIGULI R. Comparative Analysis of PSO Algorithms for PID Controller Tuning [J]. Journal of Mechanical Engineering，2014,27（5）：928-936.
[15]康浩博. 基于改进蚁群算法的机器人双臂无碰撞路径规划[D]. 沈阳：东北大学, 2010.
KANG Haobo. Double Arm Collision-free Path Planning of Robot Based on Improved Ant Colony Algorithm[D].Shenyang: Northeastern University,2010.