汽车白车身点焊作业多机器人路径规划研究
Research on Multi-Robot Path Planning for Automobile Body-in-White Spot Welding Operation
张邦成 1单玉升 2赵航 2董雷 3尹晓静2
作者信息
- 1. 长春工业大学机电工程学院,长春 130012;长春工程学院机电工程学院,长春 130103
- 2. 长春工业大学机电工程学院,长春 130012
- 3. 一汽模具制造有限公司焊装开发部,长春 130013
- 折叠
摘要
针对白车身焊装生产线多机器人焊接工作量大、焊接工作复杂的问题,提出了一种自适应精英蚁群算法的多机器人焊接路径规划方法.在蚁群算法的基础上,对算法核心参数进行调整,再将自适应更新策略和精英蚂蚁系统加入到蚁群算法中,增强算法全局搜索能力,提高算法收敛速度,并通过TSP模型检验了算法的性能;最后,以白车身焊装生产线某车型主拼工位的焊接作业为例,对方法的有效性进行了验证.结果表明,改进后的蚁群算法具有较好的搜索效率和搜索能力,多机器人焊接路径间不相交,符合焊接的工艺要求,为多机器人焊接路径规划问题提供了一种新的方法.
Abstract
Aiming at the problem of large welding workload and complex welding work in multi-robot welding production lines for body-in-white,a multi-robot welding path planning method based on adaptive elite ant colony algorithm was proposed.Based on the ant colony algorithm,the core parameters of the algo-rithm are adjusted,and then an adaptive update strategy and an elite ant system are added to the ant colony algorithm to enhance the algorithm's global search ability and improve the algorithm's convergence speed,and the performance of the algorithm is tested through the TSP model.Finally,the effectiveness of the method is verified by taking the welding operation of the total assembly station of a vehicle in the body-in-white welding production line as an example.The results show that the improved ant colony algorithm has better search efficiency and search ability,and the multi-robot welding paths do not intersect,which meets the welding process requirements,and provides a new method for multi-robot welding path planning.
关键词
路径规划/旅行商问题/蚁群算法/多焊接机器人Key words
path planning/travelling salesman problem/ant colony algorithm/multi-welding robot引用本文复制引用
基金项目
吉林省科技厅中青年科技创新领军人才及团队项目(20200301038RQ)
吉林省科技厅重点研发项目(20210201050GX)
吉林省科技厅重点研发项目(20200401114GX)
吉林省科技厅重点研发项目(20220201041GX)
出版年
2024
NETL
NSTL
维普
万方数据