计算机科学 ›› 2022, Vol. 49 ›› Issue (9): 208-214.doi: 10.11896/jsjkx.210700028
冷典典, 杜鹏, 陈建廷, 向阳
LENG Dian-dian, DU Peng, CHEN Jian-ting, XIANG Yang
摘要： 自动导引车(Automated Guided Vehicle,AGV)在自动化集装箱码头的水平运输中发挥了重要作用,对AGV行驶时间进行准确估计,有利于减少码头各作业环节的资源闲置,提高整体效率。针对AGV在自动化集装箱码头的行驶时间估计问题,提出了一种AGV行驶时间估计方法。首先,根据AGV的行驶模式将目标行驶路径切分为若干段,使用神经网络模型对其进行编码;其次,对该路径出发前后一段时间内的其他路径进行编码并将其作为环境信息,以通过模型预测其是否与目标路径发生冲突作为辅助任务;最后,综合两类信息对行驶时间进行估计。该方法引入了路径间冲突对时间估计造成的影响。基于自动化集装箱码头的历史数据的实验表明,相比AGV场景中常用的静态时间估计方法,所提方法能够将时间估计的误差降低18%以上,可以更准确地估计AGV的行驶时间。
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