摘要
提出了一种由粒子群算法和遗传算法有效结合的混合粒子群算法。以某型轿车前地板线焊接工位机器人的路径规划为例,分别采用混合粒子群算法、遗传算法对机器人的焊点焊接顺序进行求解。2种算法在Matlab中的仿真优化结果表明:混合粒子群算法在求解路径优化问题上能得到更佳的焊接路径。
A new hybrid particle swarm intelligence algorithm was presented based on the particle swarm optimization(PSO)algorithm and genetic algorithm. Taking the welding station robot path planning of the first floor line for a car as an example, the hybrid particle swarm optimization algorithm and genetic algorithm were respectively adopted to solve for the solder welding sequence. The simulation op?timization results of the two algorithms in Matlab show that the hybrid PSO algorithm is more effective to solve the problem of the welding robot path optimization.
作者
周红勋
陈君宝
王生怀
陈育荣
Zhou Hongxun;Chen Junbao;Wang Shenghuai;Chen Yurong(School of Mechanical Engineering, Hubei University of Automotive Technology, Shiyan 442002, China)
出处
《湖北汽车工业学院学报》
2016年第4期43-46,60,共5页
Journal of Hubei University Of Automotive Technology
基金
国家自然科学基金项目(51275159
51475150)
湖北省自然科学基金项目(2013CFB045)
湖北省教育厅科学技术研究重点项目(D20141802)