摘要
为有效解决路径冲突和避碰问题,提高多自动导引小车(AGV)系统的作业效率,提出基于冲突预测的多AGV避碰决策优化方法。结合图论提出一种基于顶点属性和实时位姿信息的冲突预测方法,在考虑路网全局状态的基础上建立避碰决策的数学评价模型,提出一种适用于多AGV系统避碰决策优化的改进粒子群优化算法,通过优化粒子运动的速度和方向避免优化算法过早收敛。采用融合遗传算法的变异思想为粒子引入变异操作,改善优化算法的全局搜索能力。最后通过实验测试表明,该优化方法可以有效解决多AGV系统路径冲突问题,还能缩短避碰过程中AGV的等待总时长,提高多AGV系统运行的安全性与效率。
To solve the path conflict and avoidance problem and improve the operational efficiency of multi-AGV system,an optimization method of multi-AGV conflict avoidance decision based on conflict prediction was proposed.A conflict prediction method based on vertex attributes and real-time pose was proposed.Considering the global state of the road network,the mathematical evaluation model of conflict avoidance decision was established,and an Improved Particle Swarm Optimization(IPSO)algorithm for multi-AGV system was proposed.By optimizing the speed and direction of particle motion,the premature convergence of optimization algorithm was avoided.In addition,the mutation operation was introduced into the particle by fusing the mutation idea of Genetic Algorithm(GA)to improve the global search ability of the optimization algorithm.The experimental results showed that the optimization method could solve the multi-AGV system path conflict problem effectively and reduce the total waiting time of AGVs in the process of conflict avoidance.Accordingly,the security and operation efficiency of multi-AGV system were improved.
作者
曹小华
朱孟
CAO Xiaohua;ZHU Meng(School of Logistics Engineering,Wuhan University of Technology,Wuhan 430063,China)
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2020年第8期2092-2098,共7页
Computer Integrated Manufacturing Systems
基金
国家自然科学基金资助项目(61503291)
武汉理工大学优秀硕士学位论文培育资助项目(2018-YS-070)。
