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.

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

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