Abstract: To optimize the RGV scheduling under uncertainty environments，a kind of scheduling rule was proposed based on CCPP. Taking the RGV scheduling system in an intelligent workshop as research object，considering that the CNC machines might stop working due to a series of uncertainty factors such as tool replacement，machine faults，etc.,the scheduling rule was proposed to optimize the feeding sequence of RGV  in real time based on CCPP.Additionally，the nearest rule was presented to verify the superiority of CCPP scheduling rule. Results demonstrate that the capacity of intelligent workshops may be improved effectively by conducting CCPP scheduling rule，and the walking distance of RGV is reduced.

Key words: rail guided vehicle(RGV), uncertain environment, complete coverage path planning(CCPP), nearest rule

摘要： 为优化不确定性环境下轨道自动导引车(RGV)调度问题，提出了一种基于完全遍历路径规划(CCPP)的调度规则。以某智能车间RGV调度系统为研究对象，考虑刀具更换、机器故障等一系列不确定性因素导致的计算机数字控制机台停机问题，运用CCPP调度规则对RGV的上下料顺序进行实时调度优化，并与车间现行的就近调度规则进行对比分析。实验结果表明，CCPP调度规则能够有效提高智能车间产能，减少RGV行走距离。

关键词: 轨道自动导引车, 不确定性环境, 完全遍历路径规划, 就近规则